MEASURING RADIATION DOSE IN COMPUTED TOMOGRAPHY USING ELLIPTIC PHANTOM AND FREE-IN-AIR, AND EVALUATING ITERATIVE METAL ARTIFACT REDUCTION ALGORITHM

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1 MEASURING RADIATION DOSE IN COMPUTED TOMOGRAPHY USING ELLIPTIC PHANTOM AND FREE-IN-AIR, AND EVALUATING ITERATIVE METAL ARTIFACT REDUCTION ALGORITHM ASHRAF MORGAN Bachelor of Science in Physics Cleveland State University May 2005 Master of Science in Medical Physics Cleveland State University May 2007 Submitted in partial fulfillment of the requirement for the degree of DOCTOR OF ENGINEERING IN APPLIED BIOMEDICAL ENGINEERING at the CLEVELAND STATE UNIVERSITY May 2016

2 We hereby approve this dissertation for Ashraf Morgan Candidate for the Doctor of Engineering degree for the Department of Chemical and Biomedical Engineering g and CLEVELAND STATE UNIVERSITY College of Graduate Studies Frank Dong, Ph.D, Dissertation Committee Chairperson, Department of Chemical and Biomedical Engineering Date Nolan Holland, Ph.D, Dissertation Committee Member Department of Chemical and Biomedical Engineering Date Bill Davros, Ph.D, Dissertation Committee Member Department of Chemical and Biomedical Engineering Date Xiang Li, PhD, Dissertation Committee Member Department Physics Date Miron Kaufman Ph.D, Dissertation Committee Member Department Physics Department of Physics Date Date of Defense: 5/5/2016

3 The God of heaven, he will prosper us; therefore we his servants will arise and build.

4 This dissertation is dedicated to my dearest wife Myriam for her unwavering love and support to help me finish this work. It would not have been possible without her.

5 ACKNOWLEDGEMENTS First, I would like to express my deepest appreciation and gratitude to my advisor Dr. Frank Dong for all of his support and motivation for my research. His encouragement and wealth of knowledge made it possible. I will never forget how much his support and advice helped me accomplish this work. I would also like to thank Dr. Bill Davros, my former supervisor and mentor, who was the first person to encourage me to go back to school to start working on my PhD, providing me with all of the needed support to make it possible with my full-time work. I would like to thank my committee members, Dr. Xiang Li, Dr. Miron Kaufman and Dr. Nolan Holland for helping through the years with their advice, encouragement and support. I would also like to thank my current supervisor, Paul Johnson, for his support that played a significant role in accomplishing this work.

6 MEASURING RADIATION DOSE IN COMPUTED TOMOGRAPHY USING ELLIPTIC PHANTOM AND FREE-IN-AIR, AND EVALUATING THE ITERATIVE METAL ARTIFACT REDUCTION ALGORITHM ASHRAF MORGAN ABSTRACT The need for an accurate and reliable way for measuring patient dose in multi-row detector computed tomography (MDCT) has increased significantly. This research was focusing on the possibility of measuring CT dose in air to estimate Computed Tomography Dose Index (CTDI) for routine quality control purposes. New elliptic CTDI phantom that better represent human geometry was manufactured for investigating the effect of the subject shape on measured CTDI. Monte Carlo simulation was utilized in order to determine the dose distribution in comparison to the traditional cylindrical CTDI phantom. This research also investigated the effect of Siemens health care newly developed imar (iterative metal artifact reduction) algorithm, arthroplasty phantom was designed and manufactured that purpose. The design of new phantoms was part of the research as they mimic the human geometry more than the existing CTDI phantom. The standard CTDI phantom is a right vi

7 cylinder that does not adequately represent the geometry of the majority of the patient population. Any dose reduction algorithm that is used during patient scan will not be utilized when scanning the CTDI phantom, so a better-designed phantom will allow the use of dose reduction algorithms when measuring dose, which leads to better dose estimation and/or better understanding of dose delivery. Doses from a standard CTDI phantom and the newly-designed phantoms were compared to doses measured in air. Iterative reconstruction is a promising technique in MDCT dose reduction and artifacts correction. Iterative reconstruction algorithms have been developed to address specific imaging tasks as is the case with Iterative Metal Artifact Reduction or imar which was developed by Siemens and is to be in use with the company s future computed tomography platform. The goal of imar is to reduce metal artifact when imaging patients with metal implants and recover CT number of tissues adjacent to the implant. This research evaluated imar capability of recovering CT numbers and reducing noise. Also, the use of imar should allow using lower tube voltage instead of 140 KVp which is used frequently to image patients with shoulder implants. The evaluations of image quality and dose reduction were carried out using an arthroplasty phantom. vii

8 TABLE OF CONTENTS ABSTRACT... vi LIST OF TABLES... xiii LIST OF FIGURES...xv CHAPTER I INTRODUCTION... 1 CHAPTER II BASICS OF X-RAY Interaction of Radiation with Matter Rayleigh Scattering Compton Scattering The Photoelectric Effect Linear Attenuation X-ray Production Bremsstrahlung Radiation Characteristic Radiation X-ray Tube The Cathode The Anode The Tube voltage and Current CHAPTER III COMPUTED TOMOGRAPHY Introduction Computed Tomography Development viii

9 3.2.1 Multi-Detector Computed Tomography Data Acquisition Modes Sequential Mode Spiral Mode Acquisition Parameters Tube Voltage Tube Current Pitch Reconstruction Parameters Scan Field-of-view Collimator detector-raw width Reconstruction Kernels Reconstructed Slice Thickness Water Number and Hounsfield Unit CT Artifacts Beam Hardening Partial Volume Metal Artifact Motion Artifact Noise CHAPTER IV BACKGROUND AND LITERATURE Computed Tomography Dose Index, CTDI Helical or Spiral Mode Dose Length Product, DLP CTDI and DLP Limitations New Approach to CT Dose Metal Implants ix

10 4.6.1 Imaging Metal Implants Metal Artifact Reduction Algorithm Evaluation CHAPTER V PRELIMINARY DATA Development of scan protocol (CTDI) Effect of tube current and study of linearity of the system Effect of tube voltage on dose with different phantom sizes Effect of nominal beam width Effect of chamber position, 12 o clock versus 3 o clock position Development of scan protocol (Metal Artifact) imar Initial Evaluation CHAPTER VI POTENTIAL FOR REPLACING CTDI PHANTOM WITH MORE REALISTICLY SHAPED PHANTOM TO ADJUST FOR SHAPE INACURACY OF THE CTDI PHANTOM Abstract Purpose Methods and Materials Phantoms Geometry Imaging Protocols CTDI Measurement Statistical Analysis Results Linearity and Reproducibility CTDI in Elliptic Phantom Comparison of Radiation Dose in Elliptic and Cylindrical Phantom CTDI versus Tube voltage in Cylindrical and Elliptic Phantoms x

11 6.5.5 Comparison of Measurements Made With and Without Utilizing Tube Modulation Discussion and Conclusion CHAPTER VII USING CT FREE-IN-AIR DOSE TO ESTIMATE COMPUTED TOMOGRAPHY DOSE INDEX (CTDI) Abstract Purpose Methods Experimental Setup and Parameter Measurements and Data Analysis Discussion and Conclusion CHAPTER VIII EVALUATION OF ITERATIVE METAL ARTIFACT REDUCTION (imar) Vs. FILTERED BACK PROJECTION (FBP) IN CLINICAL AND PHANTOM STUDIES Abstract Introduction Methods Patient Information and Scanning Parameter Phantom Information and Scanning Parameter Iterative Metal Artifact Reduction (imar) Data Analysis Patients Scans Analysis and Statistic Phantom Scans Analysis and Statistic Results Patients Data analysis results Phantom Data Analysis Results Discussion and Conclusion xi

12 CHAPTER IX CONCLUSION REFERENCES xii

13 LIST OF TABLES Table 3-1 List of the most common types of tissue and their CT numbers Table 5-1 CTDI100 measurement in mgy for 4-edge positions using 32-cm CTDI body phantom Table 5-2 Region of Interest (ROI) measurement before and after imar correction using same position and same size ROI Table 6-1 Calculated CTDIw (in mgy) values for a large elliptic phantom using various tube potentials and utilizing two different sets of coefficients, newly simulated coefficients and conventional CTDI coefficients. Data shows a significant difference between both cases. Measurements were made using Siemens Definition Flash scanner Table 6-2 Calculated CTDI w (in mgy) values for a small elliptic phantom using various tube potentials and utilizing two different sets of coefficients, newly simulated coefficients and conventional CTDI coefficients. Data shows less significant difference in comparison to the large phantom. Measurements were made using Siemens Definition Flash...78 Table 6-3 Reproducibility error for with lareg phantom and different positions measurments, center, 12 O clock, and 3 O clock. Data shows calculated error with and without utilizing the tube modulation 81 Table 7-1 Measured exposure and exposure per mas for 12mm and 24mm collimation at 120 KVp tube potential (Philips Brilliance) xiii

14 Table 7-2 Measured exposure and exposure per mas for 10- and 16-mm collimation at 120 kvp tube potential (Siemens Emotion) Table 7-3 Measured exposure and exposure per mas for 20-mm and collimations at 120 KVp tube potential (GE LightSpeed VCT 32 ) Table 7-4 Maximum error in linearity for Philips, Siemens and GE scanners at different collimations Table 7-5 Annual change in CTDI measurement for adult head protocol, includes Siemen, GE, and Philips scanners including PET/CT and SPECT CT Table 7-6 Number of failures in daily QC per year; data shows extremely stable performance with regard to CT number, noise and image artifacts Table 7-7 Number of failures in daily QC for a total of 70 scanners over a 4-year period Table 7-8 Conversion factors for 2 Philips brilliance 16 scanners, using all available KVp at four different collimations using abdomen protocol and 32-cm CTDI phantom Table 7-9 Conversion factors for 2 Siemens Emotion 16 scanners, using all available KVp at four different collimations for 32- and 16-cm CTDI phantoms (adult and Table 7-10 Conversion factors for 2 GE BrightSpeed 16 scanners, using all available KVp at three different collimations for 32- and 16-cm CTDI phantoms (adult and pediatric) xiv

15 LIST OF FIGURES Figure 2-1 Diagram of Rayleigh scattering, low energy photon interacts with the atom and the result is a scattered photon with the same energy in a different direction. Adapted from Bushberg et al (12)... 6 Figure 2-2 Diagram of Compton scattering, photon interacts with outer shell electrons producing free electron and scattered photon. Adapted from Bushberg et al (12) Figure 2-3 Graph showing significant amount of energy preserved at large scattering angle. Adapted from Bushberg et al (12)... 9 Figure 2-4 Diagram of Photoelectric effect. The incident photon interacts with the k-shell electron resulting in free electron and ionized atom. Electrons from the outer shell fill up the vacancy left by the electron space emitting radiation with energy equal to the difference between the two energy levels. Adapted from Bushberg et al (1) Figure 2-5 Mass attenuation vs. x-ray energy showing k-edge effect. Adapted from Bushberg et al (12) Figure 2-6 The diagram shows Bremsstrahlung Radiation with different energies based on the amount of energy which the incident electron lost. Adapted from Bushberg et al (12) Figure 2-7 Bremsstrahlung continuous spectrum for 90 KVp beam; (a) is unfiltered spectrum; (b) is filtered spectrum where low energy photons were filtered out. Adapted from Bushberg et al (12) xv

16 Figure 2-8 : (A) Characteristic radiation is generated as the electron interacts with inner shell electron removing it, then electron from outer shell falls to fill the gap. (B) Characteristic radiation spikes take a specific value for each element. Adapted from Bushberg et al (1) Figure 2-9 X-ray tube major components. Adapted from Bushberg et al (12) Figure 3-1 Example of conventional chest x-ray; information and contrast along the direction of the beam is greatly compromised Figure 3-2 Schematic of computed tomography system Figure 3-3 How image data is collected. Figure adapted from Kalender (27) Figure 3-4 Spiral CT; CT tube is on for the entire scan as the table is translated into the gantry. Figure adapted from Kalender (27) Figure 3-5 Automatic tube current modulation, (a) adjusting overall current based on the patient size, (b) adjusting overall current based on attenuation change in the z direction, (c) adjusting overall current based on the attenuation change for each rotation. Adapted from Lewis. (6) Figure 3-6 Linear attenuation coefficient muscle, bone and water. Adapted from Hsieh (27) Figure 3-7 Cupping artifact manifested as low attenuation region in the middle of a uniform water phantom (left); same image after applying software correction (right) (20) Figure 3-8 Streaks between dense bones (arrow left); same image after applying beam hardening artifact reduction (right) (14) xvi

17 Figure 3-9 Partial volume; object is off-center and partially protrudes into the slice when the tube is at one side and not the other (14) Figure 3-10 Posterior Cranial Fossa; streaks of dark and light produced due to partial volume (20) Figure 3-11 Metal artifact result of dental filing (left) and shoulder prosthesis (right) Figure 3-12 Shows motion artifact due to respiratory motion (left); corrected image with motion artifact correction algorithm (right) (14) Figure 4-1 Monte Carlo Simulation of radiation dose distribution in 32-cm CTDI phantom shows the increased dose in the edges compared to the middle portion of the phantom Figure 4-2 (A) 32-cm CTDI phantom for measuring abdominal dose. ( B) 16-cm CTDI phantom is used for measuring head dose and some CT vendors use it for measuring pediatric abdominal dose. (C) Integrating Electrometer. (D) 10-cm pencil chamber for measuring dose in CTDI phantom (42) Figure 4-3 Dose profile graph shows the over-beaming (blue arrows); the tail of the dose profile is due to scatter radiation. NT is nominal beam width (43) Figure 4-4 Helical trajectory due to movement of scanner table while tube is rotating. In this example, table speed is faster than tube rotation time, resulting in gaps (red arrow) (43) Figure 4-5 Slip ring technology allowed continuous rotation of gantry; data and power are transferred using slip brushes Figure 4-6 Graph showing the ED/DLP value as a function of position in the z axis of the scanner; graph shows higher ratio for radio sensitive organs (43) xvii

18 Figure 4-7 Graph showing, (A) 45-cm long phantom (water or PMMA) with 32-cm diameter. (B) 0.6 cm3 farmer type ion chamber (52) Figure 4-8 Graph showing data collected for different scan length, Data gathered until equilibrium is reached (52) Figure 4-9 (A) MRI of hip implant shows susceptibility artifact due to magnetic field inhomogeneity. (B) Radiograph of hip joint implant shows lost information due to the massive attenuation of x-ray by the high Z implant (53) Figure 4-10 Water filled phantom including hip prostheses placed on a slab of PMMA (56) Figure 4-11 Phantom containing two spin screws, two sausages to mimic retroperitoneal lymph nodes, and sticks of rice cake mimicking larger vessels (57) Figure 5-1 Dose in mgy vs mas graph using 32-cm CTDI phantom and large elliptic phantom with 120 KVp setting shows the linearity relation Figure 5-2 Dose vs tube voltage graph shows the non-linear relation Figure 5-3 Graph shows the inverse relation between dose and nominal beam width, same protocol settings for 19.2 and 38.4 mm. Dose using 19.2 mm collimation is greater Figure 5-4 Due to the finite size of the focal spot, geometric penumbra is formed (62).. 62 Figure 5-5 CT image of patient with metal shoulder implant without any correction algorithm (A) and with imar correction (B) Figure 6-1 Elliptic phantoms. (A) 16 cm equivalent small phantom. (B) 32 cm equivalent large phantom Figure 6-2 Monte-Carlo Simulation showing the relative dose distribution in Elliptic and cylindrical phantoms. Areas with the same color represent areas with same average dose. xviii

19 (A) 16cm equivalent elliptic pediatric abdomen phantom. (B) Conventional 16cm CTDI pediatric body phantom (C) 32 cm equivalent elliptic adult abdomen phantom. (D) Conventional 32cm CTDI adult body phantom Figure 6-3 Image of large elliptic phantom used in the study with the minor and major radii used in CTDI calculation Figure 6-4 : (A) Graph shows dose as a function of tube voltage using cylindrical phantom for three different scanners. (B) Graph shows dose as function of voltage for the same scanners using elliptic phantom Figure 7-1 Head CTDI phantom placed in the head holder with the pencil chamber in the center position for measuring system linearity Figure mm pencil ion chamber suspended in air at isocenter for free-in-air dose measurement Figure 7-3 Exposure as a function of mas (Philips Brilliance) Figure 7-4 Exposure as a function of mas (Siemens Emotion) Figure 7-5 Exposure as a function of mas (GE Light Speed) Figure 8-1 Phantom (CIRS, Computerized Imaging Reference Systems). (A) Top view of the phantom with two 100-mm diameter holes for the shoulder inserts. (B) Side view of the phantom showing with standard patient size dimension of 300-mm width and 100- mm height to cover. (C) Body phantom with two bone and two metal implants inserts. (D) Phantom setup for unilateral metal implant test scan with one bone insert and one metal implant insert Figure 8-2 Metal implant insert (A) Top view of insert with 45-mm diameter Cobalt Chrome Sphere. (B) Side view of the insert showing Cobalt Chrome Sphere with xix

20 titanium rod attached to it and surrounded by cortical bone embedded in soft tissue material. (C) Side v view showing the position of contrast targets in both sections of the insert. (D) Top view of the soft tissue section. (E) Top view of the trabecular bone section Figure 8-3 Bone insert (A) Top view of insert showing low-contrast targets. (B) Side view of the insert upper section with trabecular background and low-contrast targets and lower section with trabecular bone stem surrounded by cortical bone and low-contrast targets impeded in the background s soft tissue material. (C) Top view of the trabecular bone section Figure 8-4 Example of CT image of shoulder implant (A) Left, shoulder CT image for patient with shoulder implant using FBP; Right, same image after being imar processed. (B) Image of patient with bilateral shoulder implants (extreme case of artifact). Left, shoulder CT image using FBP, Right, same image after being imar reconstructed. (C) Image away from hardware with FBP (left), and with imar reconstruction (right) Figure 8-5 Example muscle tissue CT number measurement (A) Preoperative Shoulder CT image FBP reconstructed, (B) Post-operative shoulder CT image FBP reconstructed, (C) Same image B reconstructed with imar Figure 8-6 Example arthroplasty phantom scan (A) Preoperative phantom scan without any metal implants. (B) Post-operative phantom scan with unilateral implant, FBP reconstructed. (C) Post-operative phantom scan with unilateral implant, imar reconstructed. (D) Post-operative phantom scan with bilateral implant, FBP reconstructed. (E) Post-operative phantom scan with bilateral implant, imar reconstructed xx

21 Figure 8-7 (A) histogram for muscle tissue pre-imar, (B histogram for muscle tissue post-imar. 122 xxi

22 CHAPTER I INTRODUCTION According to the National Council on Radiation Protection and Measurements (NCRP) Report 160, radiation from computed tomography comprises 24% of the total collective effective dose in the United States (1,2). That shows how critical it is to have a method for estimating radiation dose in computed tomography. Also, it is crucial to establish reference levels for radiation dose in CT, as it is difficult to discover overexposure in such modality. Contrary to traditional screen film, over-exposure in CT results in a better image at the expense of patient dose. Another property that is specific to computed tomography is the dose distribution. In traditional projection radiography, entrance skin dose is much higher than exit skin dose; however, the rotational motion of the x-ray tube/detector combination makes it more difficult to understand dose distribution (3-7). Currently, the radiation dose associated with a CT scan is described by CT dose index (CTDI). CTDI was first introduced in 1981 by Shope et al (8). It was defined as 1

23 the integral of a single scan profile over a volume scanned along z axis, and so CTDI can be used to estimate MSAD (multiple scan average dose). The dose required to form a single scan can be determined by measuring surface dose or by measuring in-plane dose average within a dosimetry phantom. Using an ion chamber to measure CTDI in a dosimetry phantom is the predominant technique (9). Given the large number of diseases diagnosed with CT, the study of CT image quality as well as its relationship to radiation dose is also of high importance. Metal artifact reduction has been the focus of multiple studies since the introduction of computed tomography, so the issue of metal artifacts in CT is as old as the computed tomography imaging itself. With the introduction of computed tomography, it was noticed that the presence of metal with high Z in the scan field results in severe artifacts due to photon starvation and beam hardening. Metal artifacts can be caused by a small dental filling or large orthopedic implants. Metal artifacts are usually identified with the presence of dark and bright streaks and shadows that obscure anatomical information and that prevent the radiologist from making correct interpretations. There had been many attempts to reduce the metal artifact severity in MDCT, however, as of yet, there has not been one widelyaccepted solution (10). Therefore, the development of improved metal artifact reduction (MAR) algorithms is still among the top research priorities. (11-13). The other challenge when imaging patients with metal implants is reducing the patient dose. Many metal implants are large in size where the use of higher energy beam is needed in an effort to penetrate the implant and produce an image with diagnostic quality. However, increasing the tube voltage may result in a significant increase in patient dose (14). 2

24 The goal of this work is to investigate the hypothesis: Better designed phantom yields more realistic dose distribution. Computed tomography dose index can be estimated from CT dose measured free in air. Iterative Metal Artifact Reduction (imar) algorithm allows better CT number recovery and reduces image noise in patients with shoulder implants. This dissertation is ordered as background (chapters II-IV), preliminary work (chapter V) and specific aims (chapters VI- VIII). Chapter II includes background on the basics of x-ray how it is produced. Chapter III describes the modern CT technology and image reconstruction. Chapter IV describes the research topics back ground including Computed Tomography Dose Index (CTDI), Dose Length Product (DLP). This chapter also discusses some previous research work in the area of metal implant imaging. Chapter VI includes preliminary studies that were used to develop the proper protocols and research methods. Iterative Meta Artifact reduction is preliminary analysis is also included in chapter VI. Chapter VI describes the potential for replacing the conventional CTDI phantom with elliptic phantom (specific aim1). The experimental methods, results and discussion of the fining are included The feasibility of replacing CTDI with free-in-air technique (specific aim 2) is discussed in chapter VII. Chapter VIII describes the capability of imar of recovering CT numbers of the tissues within the affected region of the image (specific aim 3), phantom and clinical studies used in the imar research are analyzed and discussed in this chapter. 3

25 The conclusion of this dissertation that include brief summary of findings and the future work that was proposed are in summarized in chapter IX 4

26 CHAPTER II BASICS OF X-RAY Medical Imaging started with the discovery of x-ray by Wilhelm Roentgen on November of The first image of human anatomy was taken by Roentgen, which was an x-ray of his wife s hand. That famous image represented the start of diagnostic radiology. Imaging human anatomy using x-ray has been under constant development since the discovery of x-ray. X-ray imaging is done with the x-ray source at one side of the patient and the x-ray detector at the other side. X-ray interaction with patient anatomy results in the heterogeneous intensity of the x-ray exiting the patient, which is then detected by a specific detector based on the type of imaging used (e.g., radiography, fluoroscopy, computed tomography (12, 13). 2.1 Interaction of Radiation with Matter When x-ray photons travel through a medium, it is absorbed, scattered or penetrated without interaction. Photons can interact with a medium in five different ways based on the photon energy and properties of the medium. Rayleigh scattering, Compton 5

27 scattering and photoelectric absorption are the types of interactions encountered in diagnostic radiology range of energies (< 150 KeV), pair production and photodisintegration are encountered with photons with high energy than that employed in diagnostic radiology (12-5) Rayleigh Scattering In Rayleigh scattering, photons interact with the entire atom (Figure 2-1). The electric field of the electromagnetic wave of the photon causes the atoms electrons to oscillate in phase. The electron could emit the energy that it absorbed in the form of a photon with the same energy of the incident photon, but in a different direction (scattered photon) (12, 15,16,17). Figure 2-1: Diagram of Rayleigh scattering, low energy photon interacts with the atom and the result is a scattered photon with the same energy in a different direction. Adapted from Bushberg et al (12). 6

28 2.1.2 Compton Scattering Compton scattering is the predominant interaction of x-ray photons with soft tissue in the diagnostic range of energy. In Compton scattering, the x-ray photon interacts with the outer shell electrons causing removal of one of the valence electrons from the atom (12, 18, 19) (Figure 2-2). Compton interaction results in a scattered photon with energy E sc and an ejected electron with kinetic energy E - e, the energy of the incident photon E o is the sum of the scattered photon energy and the ejected electron kinetic energy (Equation 2-1). E o = E - e + E sc Equation (2-1) Figure 2-2: Diagram of Compton scattering, photon interacts with outer shell electrons producing free electron and scattered photon. Adapted from Bushberg et al (12). 7

29 The scattered photon may encounter more interactions as it travels through the medium because it maintains a significant amount of energy that enables it to traverse into the medium and interact further. The energy of the scattered photon is calculated using equation 2-2, where θ is the angle of the scattered photon. E sc = 1+ E o E o 511 KeV (1-cosθ) (Equation 2-2) In the diagnostic range of energy, scattered photon will maintain relatively high energy even at a large scattering angle (Figure 2-3). For example, 100 KeV photon with a scattering angle of 60 Ο will maintain 90 % of the incident photon energy E o. The scattered photon can reach the image receptor resulting in image degradation and loss of contrast, as scattered photons do not carry any useful spatial information. Another problem encountered with Compton scattering is that scattered photons with relatively high energy result in increased occupational dose to personnel working in proximity to the patient during a scan, as is the case for fluoroscopy procedures. The incident photon must have an energy that exceeds the binding energy of the valence electrons in order to be able to ionize the atom, causing the release of electrons and scatter of the incident photon. As the incident photon s energy increases, the probability of Compton interaction increases (12); however, Compton interaction probability is independent of the medium s atomic number Z. Compton interaction increases with the increase in electron density in the medium. The number of electrons/g 8

30 is almost constant in tissue except for hydrogen-rich tissues (hydrogenous) that have twice the electron density compared to ahydrogenous one. Figure 2-3: Graph showing significant amount of energy preserved at large scattering angle. Adapted from Bushberg et al (12) The Photoelectric Effect In photoelectric effect, the x-ray photon interacts with inner shell electrons. X-ray photon in photoelectric effect transfers all of its energy to a target electron causing electron ejection of its shell. The ejected electron will have a kinetic energy E e equal to the difference between the photon s energy E o and the electron binding energy E b (Equation 2-3). 9

31 E e = E o E b (Equation 2-3) The Photon s energy must be greater than the binding energy of the electron to be capable of removing it from its shell. The photoelectric interaction probability is higher when the photon s energy is slightly higher than the binding energy of the electron. When the electron is removed from its shell, a vacancy is created and another outer shell electron will fall to fill the gap. The same process will happen with the vacancy as another electron from a lower binding energy level will fill the new gap (Figure 2-4). The difference in energy between the two energy levels is released in the form of x-ray photon (characteristic x-ray) or Auger electron, which is the predominant one in soft tissue (12, 15, 20, 21). Figure 2-4: Diagram of Photoelectric effect. The incident photon interacts with the k- shell electron resulting in free electron and ionized atom. Electrons from the outer shell fill up the vacancy left by the electron space emitting radiation with energy equal to the difference between the two energy levels. Adapted from Bushberg et al (1). 10

32 The incident photon interacts with the k-shell electron resulting in free electron and ionized atom. Electrons from the outer shell fill up the vacancy left by the electron space emitting radiation with energy equal to t The probability of the photoelectric interaction is proportional to Z 3 /E 3, where Z is the atomic number of the target material and E is the photon energy. Photoelectric effect does not produce scattered photons as previous interactions; hence, it does not degrade image quality (12, 15). Photoelectric absorption is the major principle for contrast media in medical imaging. High Z contrast elements, such as iodine (Z=53), will absorb x-ray photons significantly better than soft tissue, allowing for better visualization of contrast-rich areas in the image. In addition to contrast media, a small difference in the atomic number Z between two different tissues is magnified, as photoelectric absorption is proportional to Z 3, which gives rise to better overall contrast in the image (12, 13, 15) Linear Attenuation The removal of x-ray photons from the beam as it travels through material is defined as attenuation (12). Attenuation of the x-ray beam passing through matter is the result of one or more of the interactions discussed previously. The linear attenuation coefficient for material is the percentage of photons removed from the main beam per unit length of material. Three (four???) factors affect linear attenuation of a material: 11

33 atomic number, density, electron density and beam energy (12,13, 22). attenuation increases with the increase in the material s atomic number. Linear High-Z materials are used in applications that require high linear attenuation (e.g. room shielding and contrast medium). Also, linear attenuation of a material increases with increases in electron density of the material. Thus, the physical state of material, be it gas, liquid or solid, is an important factor. Likewise, linear attenuation decreases as the beam energy increases. However, sudden increases in the attenuation coefficient result when the beam energy is higher than the inner shell electrons binding energy (Figure 2-4). If the photons energy is lower than the binding energy, absorption does not occur. N = N o e -µx (Equation 2-4) where N o is the number of photons entering through material with thickness X, and N is the number of photons exiting the material and µ is the attenuation coefficient of the material. 12

34 Figure 2-5: Mass attenuation vs. x-ray energy showing k-edge effect. Adapted from Bushberg et al (12). 2.2 X-ray Production X-rays are generated by accelerating electrons to very high energy and colliding with high Z material; electrons convert their kinetic energy to x-ray photons. The electrons acceleration is achieved by the high potential difference between the electron source and the target material (12,13,16,23). The X-ray tube is the device that houses the needed parts to generate x-rays. 13

35 2.2.1 Bremsstrahlung Radiation Bremsstrahlung is German for braking radiation. This term is used to define the process of x-ray production when fast-traveling electrons encounter the positivelycharged nucleus. Electrons lose energy as they change direction and decelerate due to the effect of the nucleus positive charge. The resulting loss in kinetic energy is radiated in the form of x-ray photons (Figure 2-5). Figure 2-6: Diagram shows Bremsstrahlung Radiation with different energies based on the amount of energy which the incident electron lost. Adapted from Bushberg et al (12). X-ray generated by Bremsstrahlung has a wide spectrum of photon energies. The energy of the generated photon will change based on how far or close the electron is to the nucleus. When the electron passes near the nucleus, it decelerates and sharply deflects, which results in significant loss of kinetic energy in the form of photon. On the other hand, the loss in energy is not too large when the electron passes far from the 14

36 nucleus (Figure 2-5). Bremsstrahlung is a continuous spectrum where photons can have any energy. In clinical application, Bremsstrahlung spectrum is filtered to remove the low energy photons. Figure 2-6 shows the filtered and unfiltered spectrum with the maximum energy of 90 KeV. Maximum energy is achieved by setting the tube potential to that desired maximum (12,13,24,25). Figure 2-7: Bremsstrahlung continuous spectrum for 90 KVp beam; (a) is unfiltered spectrum; (b) is filtered spectrum where low energy photons were filtered out. Adapted from Bushberg et al (12) Characteristic Radiation Characteristic radiation is discrete peaks of energy that depend on the target material used in generating x-ray (12). It is produced when high-energy electrons interact with one of the orbital electrons in the target atom. If the photon has sufficient energy to remove the electron from its shell (ionizing the atom), then a vacancy is created in that energy shell. The vacancy is filled by one of the upper shells electrons; during that 15

37 transition the electron will give its excess energy in the form of photon (12,13,16,23). The energy of the emitted photon depends on the difference in the two shells binding energy (Equation 2-5). The binding energy of each shell s electrons is characteristic to that atom, and the difference between the energy levels is a signature of each element. C haracteristic = E binding E of vacant - E binding E of transition Equation 2-5 Energy released in the form of photons when electron falls from one shell to another, and it appears as peaks of energy overlap with the Bremsstrahlung spectrum (Figure 2-7 B). Characteristic radiation can only be generated if the potential difference between the electron source and the target is greater than the binding energy of the desired shell. The ratio between characteristic radiation and Bremsstrahlung radiation intensities increases with the increase in energy. A B 16

38 Figure 2-8: (A) Characteristic radiation is generated as the electron interacts with inner shell electron removing it, then electron from outer shell falls to fill the gap. (B) Characteristic radiation spikes take a specific value for each element. Adapted from Bushberg et al (1). 2.3 X-ray Tube X-ray tube (Figure 2-8) is the device that is designed for the Bremsstrahlung radiation and characteristic radiation processes to occur when voltage potential is applied. Applying external voltage across the tube accelerates the electrons from the cathode to high kinetic energy towards the anode. Figure 2-9: X-ray tube major components. Adapted from Bushberg et al (12). 17

39 2.3.1 The Cathode The cathode is the negative electrode of the tube. It is the source of electrons and it consists of a tungsten filament wire that heats up and emits electrons when electric current passes through it. The amount of electrons liberated is controlled by controlling the current that goes through the filament. The tube current is the electron current that flows from the cathode to the anode (12,13,26) The Anode The anode is the positive electrode of the tube. It is the target that electrons are accelerated towards. Tungsten is the most common element used in making x-ray tube target. It has a very high melting point and a high atomic number, which makes it an ideal element for the application. The X-ray tube used in CT utilizes rotating target design that allows for heat dissipation, as CT demands high output and continuous emission over several seconds The Tube voltage and Current The tube voltage is defined as the potential difference between the cathode and the anode that allows the electrons to flow from the cathode to the anode with high enough energy to generate x-ray. Tube voltage is usually expressed in peak voltage in kilo volt. The most common setting in CT tube are 70, 80, 90, 100, 110, 120 and 140 KVp with 120 KVp being the most commonly used. Increasing tube voltage allows for 18

40 better penetration. Examples for situations requiring high tube voltages include scanning large patients and patients with large metallic implants. Tube current is the number of electrons flowing across the tube from the cathode to the anode per second. Tube current is usually measured in milliamperes (ma). The increase in tube current results in an increase in photons or x-ray intensity. Increasing tube current will result in an increase in dose by the same factor. Doubling the tube current will double the dose, however, this will increase the signal to noise ratio by 40 % only. 19

41 CHAPTER III COMPUTED TOMOGRAPHY 3.1 Introduction Conventional radiography compresses the three dimensions of the human body to two dimensions (11,12,13). Information along the x-ray direction is greatly compromised or lost, and different tissues overlapping in the x-ray direction are superimposed, resulting in a significant decrease in contrast (Figure 3-1). Figure 3-1: Example of conventional chest x-ray; information and contrast along the direction of the beam is greatly compromised. 20

42 Computed tomography utilizes a narrow beam of x-ray to make multiple projections of the anatomical region of interest. A cross sectional image is formed as both x-ray tube and detector rotate around the patient (11,12,27). Many projections are taken per each gantry rotation (Figure 3-2). The information gathered from all the projections and views acquired are used to calculate the average linear attenuation coefficient of the body section imaged. X-ray Table Detect Figure 3-2: Schematic of computed tomography system 21

43 3.2 Computed Tomography Development Hounsfield s setup which was used experimentally is considered the firstgeneration computed tomography (11,12). A pencil beam was used along with a single detector using the translation-rotation principle (Figure 3-3), in which the detector aligned with the x-ray beam, scanning the object. The same process is repeated several times before both the radiation source and the detector rotate to repeat the same scan process at different view angles. Second generation utilized a fan beam with the addition of more detectors and the same translation-rotation principle. First and second generation required very long scan times, which gives rise to severe motion artifact. The development of slip ring technology allowed for continuous tube rotation, which results in a significant decrease in scan time. The first continuous rotation scanner was introduced in 1987 (11, 27). Figure 3-3: How image data is collected, adapted from Kalender (27). 22

44 Slip ring technology allowed for the introduction of spiral scanning, which is the continuous scanning of a volume as the table is translated into the gantry. Modern CT scanners with multi-detectors scan the entire region of interest in a few seconds. Abdomen scan can be performed within one breath-hold. Moreover, motion artifact and patient comfort have drastically improved as a result of spiral CT application Multi-Detector Computed Tomography The detector is one of the most important components in the CT system. The function of the CT detector is to convert the incident x-ray to an electrical signal. The detector system also amplifies the signal and digitizes it (11). Early CT scanners that were developed in the 1970s utilized two-detector-rows technology, which enabled the systems to scan two slices simultaneously. By the year 2008, 320-rows with 320-slices scanner was developed. The rapid increase in scanners detector rows number allowed for much faster scanning and reduction of motion artifact (Figure 3-4). 23

45 Figure 3-4: Spiral CT; CT tube is on for the entire scan as the table is translated into the gantry, adapted from Kalender (27). 3.3 Data Acquisition Modes All modern CTs employ two modes of acquisition, sequential or spiral Sequential Mode Also known as step and shoot, where the tube rotates 180 Ο or 360 Ο, acquiring data while the table is stationary. Once the first scan is done, the table then moves into the gantry bore in increments equal to the collimation width to scan the next section of the desired anatomy. The step and shoot process is repeated until the entire volume of interest is scanned. Using sequential mode in routine examination has been largely replaced by spiral mode. However, the use of sequential mode will remain in use for certain applications, such as in some lung and dynamic CT exams (11,27). 24

46 3.3.2 Spiral Mode Also known as helical mode, in spiral CT, the patient is scanned continuously as the patient table travels into the gantry. The speed of the table traveling into the gantry is usually one to two times the collimation width per each tube-detector rotation (27). More detailed discussion on spiral CT scan is included in chapter Acquisition Parameters Tube Voltage Tube voltage is the difference in potential applied across the tube. The potential difference between the cathode and anode of the tube determines the average photon energy spectrum. Tube voltage in diagnostic radiology is usually in the range of 20 to 140 Kilovolts (KV). Tube voltage is the maximum energy that any produced photon can have, and the average photon energy is around 60% of the maximum voltage applied (Tub Voltage). The quality of the x-ray is determined by the tube voltage. When tube voltage is increased, the average photon energy increases, which results in better penetrability or higher-quality photon. Tube voltage is determined based on the task at hand. For routine abdomen CT for an average patient size, the usually setup is 120 KVp. Large-size patients may require increasing the tube output to 140 KVp. Also scanning patients with larger implants may require using higher tube voltage. For instance, in scanning patients with shoulder implants, the large metal shoulder implant requires the use of 140 KVp to penetrate the metal implant and form an acceptable image. One setback for using high tube voltage is that patient radiation dose increases with the 25

47 increase in tube voltage. Also, the increase in tube voltage diminishes contrast resolution in the image (12-27) Tube Current Tube current is the number of electrons accelerated from the cathode toward the anode. Tube current is measured in milliamperes (ma). The tube current determines the number of photons created in the tube (x-ray quantity). Image signal-to-noise ratio is proportional to the tube current. Increasing tube current also results in an increase in patient dose. Modern CT utilizes automatic tube current modulation (auto ma). The goal of this development was to maintain consistent image quality from one patient to another and to assist in reducing patient dose. The attenuation of x-ray beam increases with patient size or the thickness and composition of material it passes through. X-ray beam loses 50% of its intensity for each 4 cm of tissue it passes through, so to maintain the same noise level, ma needs to be modified or changed as the patient size changes. By using the attenuation information gathered from the localizer scan, tube current modulation will change the tube current to optimize the intensity reaching the detector, which allows for noise level consistency and reduces the amount of radiation used to form the image (Figure 3-5). Tube modulation is done in three levels; however, it usually utilizes all three together. Level one is adjusting the current based on the overall patient size, the second level is modulating the current based on the change in attenuation in the z direction, and the third level is modulating the tube current based on the change in attenuation within the xy plane as the tube rotates and the x-ray beam encounters different attenuations at different angles (11,27,28,29). 26

48 Figure 3-5: Automatic tube current modulation, (a) adjusting overall current based on the patient size, (b) adjusting overall current based on attenuation change in the z direction, (c) adjusting overall Pitch current based on the attenuation change for each rotation. Adapted from Lewis. (6) Pitch In Spiral scan, the table feed d in mm per 360 Ο rotation to the total beam collimation is termed Pitch (P). The total beam collimation is the product of the number of slices (N) and nominal slice width (T): P = d N. T Equation 3-1 Pitch is a dimensionless quantity. It is a very important determining factor in image quality, and it also plays a significant role in impacting patient dose. Pitch value 27

49 determines the overlap or separation of acquired data in the Z direction (12, 13). Routine pediatric abdomen scans usually done using pitch greater than one to reduce the dose. dose = 1 pitch Equation 3-2 Spiral scan has eliminated the repeat scan that used to be frequently required when using sequential technique if the patient moved between scans. Repeat scans were routinely required when sequential mode was used to collect data for 3D acquisition. Such improvement resulted in a reduction in average patient dose. 3.5 Reconstruction Parameters Scan Field-of-view The scan field of view is the largest field that can be imaged; it extends to cover the entire x-ray beam. Reconstructed field of view is the portion of scan field of view that is chosen based on the size of the body region imaged. The reconstructed field of view is usually 512 x 512 matrix, and so it determines the pixel resolution Collimator detector-raw width In multi-detector CT, the collimator width is the thickness or the width of the beam at the isocenter. The minimum thickness is defined as the thickness of a single detector row. Patient dose is inversely proportional to collimated width. In both spiral and axial mode, using wider beam collimation results in a lower dose to the patient (this will be discussed in detail in the CTDI chapter). A thinner slice results in improved 28

50 spatial resolution in the Z direction. However, the thinner slice also results in lower SNR. Consequently, mas is increased to compensate for the degradation in SNR which leads to a higher patient dose (11,12,27) Reconstruction Kernels The kernel choice is based on the image property that is important for the type of study. In studies where details are of great diagnostic importance, low frequency cut-off kernel is used to preserve the details and edge definition. Such kernel will preserve details; however, it will result in a grainy image with low signal-to-noise ratio and loss of contrast. Such kernel is often called bone or sharp Kernel (11,30). In studies where contrast is important, such as in abdominal imaging, high frequency cut-off kernel is utilized in order to preserve high signal-to-noise ratio??, which results in better image contrast and smoother appearance. High contrast kernel is often referred to as soft tissue kernel or smooth kernel Reconstructed Slice Thickness The width of detector row in computed tomography dictates the thinnest slice width that can be achieved. The reconstructed slice thickness choice is based on the desired image quality and anatomy of interest. Reconstructed slice thickness defines the resolution in the Z direction. Reconstructing thicker images is usually performed when higher signal-to-noise ratio is required, and the result is better contrast. 29

51 3.6 Water Number and Hounsfield Unit CT measures the spatial distribution of the linear attenuation coefficient µ(x,y) (3). Even though µ is what is measured, displaying it as a function of spatial distribution will not render enough useful information to form an image, as it is energy dependent. In addition to that, comparing studies done at different energy spectrums or different scanners will be very complex. As a solution to the above difficulties, when using µ, a relative value was developed, known as CT value or CT number. CT number is the coefficient value relative to the attenuation of water (11,12,27). It is measured in Hounsfield (HU) units, and is defined as: CT# = µ T µ Water µ Water Equation 3-3 Based on the equation above, CT number of water is zero HU, where µ T = µ Water. Using the same CT number scale renders air CT number to be HU, as µ air = 0. As demonstrated by the previous examples, the values and comparison between air and water CT numbers are independent of the scanner and the energy spectrums were used. Any material in the body with a density less than that of water will have a negative CT number, and any material denser than water will have a positive CT number (27,31). 30

52 Tissue CT Number (HU) Soft Tissue 10 to 300 Blood 30 to 45 Bone 700 to 3000 Water 0 Grey matter 37 to 45 White matter 20 to 30 Lung -500 Fat -100 to -50 Air Table 3-1 List of the most common types of tissue and their CT numbers. 3.7 CT Artifacts In cases where the CT image does not truly represent the anatomic structure that was scanned, this indicates a false representation produced by the scanner. The artificial structures that scanners may introduce to the actual image are known as image artifacts. Some artifacts are clearly distinguishable from normal structure and will not be misinterpreted as true structures in the image; however, these types of artifacts may obscure important, true information. Other types of artifacts can mimic true structures in the images, which may lead to misinterpretation of the images. 31

53 3.7.1 Beam Hardening Beam Hardening related to the fact that the x-ray beam is made out of a spectrum of energies (polychromatic) and also due to linear attenuation energy dependent. Usually, material will absorb low-energy photons better than absorbing high-energy ones due to photoelectric effect. As the beam passes through an object, the x-ray beam becomes harder. Harder beam has a high average energy due to the low-energy photons absorption (11,27). Figure 3-6: Linear attenuation coefficient muscle, bone and water. Adapted from Hsieh (27). As shown in figure 3-6, the attenuation coefficient is strongly dependent on the beam energy. Cupping artifact (Figure3-7) is a direct result of the beam hardening. As the beam travels and becomes harder, it becomes easier to penetrate, which is interpreted by the system as low attenuation coefficient and shows as a darker spot where the 32

54 hardened beam penetrated. Cupping artifact can mimic some pathology, and that may lead to wrong diagnosis. Dark bands and streaks between dense objects (bones) are another artifact that occurs due to beam hardening, where the beam is hardened as it passes through two dense objects compared to other projections where the beam passes though only one of the two objects (13,27) (Figure3-8 ). Several techniques are used to reduce beam hardening and the resulting cupping artifact, one of which is beam filtration. Aluminum and copper filters are usually used to remove low-energy photons and harden the beam prior to reaching the patient to allow for better beam attenuation uniformity. Calibration correction and other types of software correction are utilized as well to reduce beam hardening (11,27,32,33). Figure 3-7: Cupping artifact manifested as low attenuation region in the middle of a uniform water phantom (left); same image after applying software correction (right) (20). 33

55 Figure 3-8: Streaks between dense bones (arrow left); same image after applying beam hardening artifact reduction (right) (14) Partial Volume The cause of partial volume is the extending of a high-contrast object partially into the slice in the Z direction. One way for partial volume to occur is shown in Figure (12-33,34). The high-contrast object partially enters the scanned slice in such a way that part of the object is seen by the detector when the tube is on the left; however, the object is not seen by the same detector when the tube is on the right. This inconsistency between the two projections causes the artifact shown in figure The best technique 34

56 to correct partial volume artifact is to use thin slices during acquisition, especially when scanning body parts that encounter a rapid change in density (12,27,34). Using thin slices during acquisition can result in reduced signal-to-noise ratio to undiagnostic levels; in such a case, a few thin slices can be summed to generate a thicker slice with better signal-to-noise ratio. Figure 3-9: Partial volume; object is off-center and partially protrudes into the slice when the tube is at one side and not the other (14). 35

57 Figure 3-10: Posterior Cranial Fossa; streaks of dark and light produced due to partial volume (20) Metal Artifact As the name suggests, metal artifacts rise from having metallic material within the scan s field of view. The appearance of metal artifacts can vary significantly with the size, shape and density of the metal it originated from (Figure 3-11). Metals in the human body can range from dental implants or filling to large joint prosthesis. Metal objects can cause beam hardening, partial volume and photon starvation (11,12,27,29-35). When the presence of metal results in beam hardening, several techniques can be utilized to address the problem, one of the solutions is increasing the KVp setting. Increasing KVp from 120 KVp to 140 KVp is usually used in cases where large metallic artifacts are present, such as hip, knee or shoulder implants; however, that comes with the 36

58 price of increasing patient dose. Another method to reduce beam hardening caused by metal objects is to utilize metal artifact correction algorithm as discussed in chapter 8. Partial volume that is caused by metal implants can be addressed with the method mentioned above or by using correction algorithm as well. Photon starvation causes severe deficiency in the intensity of photons reaching the detector. Increasing KVp might help with the photon starvation; however, not it is not very successful when encountering large dense metallic implants. Likewise, increasing tube mas is not the best approach, as it results in a significant increase in patient dose (35,36). A software algorithm for photon starvation artifact correction has been developed, where it uses data from neighboring regions to the implant and injects it in the missing data to reconstruct the image. Such technique is quite successful; however, all the information pertaining to the implant itself is destroyed in addition to the information from the tissue immediately next to the implant, which is a significant drawback, as many of the clinical applications depend on the information pertaining to those tissues. 37

59 Figure 3-11: Metal artifact result of dental filing (left) and shoulder prosthesis (right) Motion Artifact Patient motion causes shades and streaks as a result of misregistration of the acquired data (Figure 3-12). Motion artifact does not only appear as local artifact pertaining to its location, but it also causes disturbance in the entire image, as the back projection process results in all the details in the images contributing to each pixel (11.27,14,37,). Avoiding motion artifact can be achieved by means of patient positioning and immobilization. Decreasing scan time helps minimize motion artifact, especially in cardiac imaging. Controlling tube start and stop positions can also help with minimizing that by choosing the start-stop direction to be in the same as the motion. For example, when scanning abdomen or chest, the tube will start and stop in the anterior-posterior direction. CT vendors also developed software algorithms to correct for motion artifact. 38

60 Figure 3-12: Shows motion artifact due to respiratory motion (left); corrected image with motion artifact correction algorithm (right) (14) Noise There are two types of noise encountered in modern CT images, quantum noise and electronic noise. Quantum noise (statistical noise) is a result of scattered photons which are randomly scattered from the scanned material. Noise is defined as the standard deviation from the intensity mean within a region of interest. In CT, it decreases with the increase in tube current. Also, the reconstruction kernels determine the amount of noise allowed in the image based on the application. Utilizing sharp kernels results in an increase in image noise contrary to body kernel. During signal processing, electronic circuits add noise to the signal. However, digital processing and modern engineering resulted in significant reduction in the amount of electronic noise, making it a very small fraction in comparison to quantum noise (12,13,27,38,39) 39

61 CHAPTER IV BACKGROUND AND LITERATURE 4.1 Computed Tomography Dose Index, CTDI When computed tomography dose index was introduced over thirty years ago, it was to serve as an index and not as an actual measurement for patient dose. Over the past thirty years, CTDI was enhanced and developed to give a closer look at what the actual dose might be (1). CTDI is measured using a 100-mm long ion chamber that is designed solely for CTDI measurement. It is measured using either a 16-cm PMMA phantom for head-protocol dose as well as pediatric abdominal dose, or 32-cm for adult abdomen dose (Figure 1). CTDI has been the only standard for measuring dose in Computed Tomography. It has gone through several modifications since it was first introduced. It is defined as the average absorbed dose along the Z axis (11-40,41). CTDI = 1 NT D(z) dz, (Eq. 1) 40

62 Where, N is the number of tomographic sections in each axial scan. D(z) is the radiation dose profile along z axis T is the nominal thickness of each tomographic section CTDI FDA was introduced by the FDA to account for over-beaming or the tails of the radiation dose profile (Figure 3). CTDI FDA used integration limits of +7T and -7T (12,41). and it underestimated the average dose, which led to progress towards new development [4]. CTDIFDA CTDI= 1 FDA Where T is the nominal slice width. 7T NT 7T D(z) dz,. (Eq. 2) CTDI 100 is the accumulated dose at the center of the 100-mm ion chamber. CTDI 100 underestimates the dose for longer scans when the 100-mm long ion chamber does not detect the entire beam profile (4). It is measured using the 100-mm ion chamber, hence, the integration limits are ±50 mm (12,41). CTDIFD CTDI = mm NT 50 mm D(z) dz,. (Eq. 3) CTDI 100 is measured in axial mode using single rotation and stationary table mode. The 100-mm pencil chamber measures the integral of the dose profile D(z) from a single rotation axial scan (41). When measurement is made with the pencil chamber as shown 41

63 in figure 1-C, the value given by the meter is the average exposure over the chamber length. Figure 4-1: Monte Carlo Simulation of radiation dose distribution in 32-cm CTDI phantom shows the increased dose in the edges compared to the middle portion of the phantom. The distinguished design of computed tomography gives rise to a very unique dose distribution (figure 4-1). CTDI 100 measured in the peripheral position of the phantom is twice that measured in the center of the 32-cm CTDI phantom as shown in figure 4-2-A. The dose to the area represented by the outer region of the phantom is about twice that represented by the center portion. Using Monte Carlo simulation confirmed such dose distribution, so averaging CTDI across the scanned volume is calculated as follows: 42

64 CTDI W = 1/3 CTDI 100, center + 2/3 CTDI 100, peripheral (Eq. 4) The 1/3 and 2/3 ratios are approximate to the areas in the middle and edge of the phantom (figure 1, figure 2-A). As mentioned earlier, the MSCT tube rotation results in a higher dose at the entrance (surface) and a lower dose in the middle of the scanned object. If the same parameters are used to scan small and large CTDI phantoms, the dose to the small phantom will be greater. Also, the measurement made in the center will not be significantly smaller than the peripheral measurement. A C B D Figure 4-2: (A) 32-cm CTDI phantom for measuring abdominal dose. ( B) 16-cm CTDI phantom is used for measuring head dose and some CT vendors use it for measuring pediatric abdominal dose. (C) Integrating Electrometer. (D) 10-cm pencil chamber for measuring dose in CTDI phantom (42). 43

65 Figure 4-3: Dose profile graph shows the over-beaming (blue arrows); the tail of the dose profile is due to scatter radiation. NT is nominal beam width (43). 4.2 Helical or Spiral Mode As previously discussed in chapter 3, the x-ray tube in computed tomography rotates continuously in the spiral mode, which was the result of the development of slip ring technology (12). By translating the table into the gantry while the tube is rotating we were able to scan continuously. The ratio of the table speed to the tube rotation speed determines whether there will be beam overlap or gaps between consecutively-imaged sections (figure 4-4) (44,45). 44

66 Figure 4-4: Helical trajectory due to movement of scanner table while tube is rotating. In this example, table speed is faster than tube rotation time, resulting in gaps (red arrow) (43). Helical scan mode provided a solution to multiple image acquisition problems related to scan time. Step-and-shoot mode involves long non-acquisition time, where the x-ray tube is turned off and the patient is translated to the next position. Step-and-shoot resulted in movement and possible deformation of scanned organs due to the acceleration and deceleration when the table moves and stops, and in some instances, there used to be misregistration and sections of scanned organs were missed. Also, this technique required multiple breath-holds to scan the same organ, which resulted in additional misregistration (11,12,46). With helical mode, chest or abdomen scans can be done with one breath-hold, which minimizes motion artifact significantly. 45

67 Acquired Signal Power Supply Figure 4-5: Slip ring technology allowed continuous rotation of gantry; data and power are transferred using slip brushes. Helical Pitch Helical pitch is defined in equation 3-1 as Pitch = I/(NxT) Where I is the table travel per 360 degree rotation. N is the number of detector rows, and T is row width. NxT represents the total collimation. As figure 3 illustrates, pitch greater than 1 will result in, not only a faster scan, but also less data samples. The other significant advantage of using pitch greater than 1 is lower dose, as images are formed using less sampled data points with less x-ray per volume. Measuring dose in helical CT takes pitch value into account, as dose will significantly vary with changing pitch and keeping all other parameters fixed. CTDI VOL is the dose descriptor used to define dose in helical CT. It is defined by the following formula: 46

68 CTDI VOL = CTDI VOL / Pitch (Eq. 6) Equation 6 shows the inverse relation between pitch and radiation dose. It is recommended when scanning pediatric patients to keep pitch greater than 1 in order to lower radiation dose to the patient. CTDI takes into account pitch as a factor in measuring radiation dose in CT, however, it does not give enough information regarding the total energy absorbed. CTDI for abdomen study can be the same for abdomen/pelvis study, even though the radiated volume in the latter is significantly larger. To incorporate scan length as a parameter that determines scanned volume and in return total deposited energy, the Dose Length Product (DLP) was introduced. 4.3 Dose Length Product, DLP DLP is the product of CTDI vol in mgy and scan length in cm. DLP accounts for scan length, including over-ranging in helical protocols (11,22,41,). All modern CT scanners report CTDI vol and DLP in what is known as dose summary sheet. DLP is proportional to effective dose (ED), which is a measure of radiation risk; ED-to-DLP ratio can be used as the conversion factor to estimate ED from displayed DLP. Figure 6 shows the increased risk associated with scanning radiosensitive organs. Two different scans with the same DLP can have different ED/DLP ratios, as the organs radio sensitivity varies along the scan axis (47,49). 47

69 Figure 4-6: Graph showing the ED/DLP value as a function of position in the z axis of the scanner; graph shows higher ratio for radio sensitive organs (43). 4.4 CTDI and DLP Limitations CTDI is not a measurement of patient dose; rather, it is an index that can be used to compare protocols and systems. Using a cylindrical phantom of fixed size is one of CTDI s limitations, as it does not represent the true geometry of average-sized patients. Also, CTDI does not measure dose in tissue, rather it measures dose in air. With the increase in employing a wider beam in CT, CTDI is under-estimating the dose by a factor ranging from 0.6 to 0.8 (50), as the effective length of the pencil chamber is too short for covering the tails of the dose profile. To accurately measure dose, a phantom with length greater than 400 mm should be utilized. In some cases, the beam width exceeds the length of the pencil chamber used for measuring CTDI, in which case CTDI completely 48

70 fails to provide any information about the dose with such a wide beam. CTDI has to be measured without any ma modulation; meanwhile, using ma modulation has become standard practice and is employed by all vendors. ma modulation technique uses attenuation information from scout scan to adjust ma as the x-ray tube is rotating around the patient. The ma modulation helps reduce the dose by varying ma based on the attenuation profile; however, CTDI does not take that into account as it is measured using standard protocol without ma modulation, since the CTDI phantom is a perfect cylinder where ma modulation cannot be used (50,51). 4.5 New Approach to CT Dose The American Association of Physicists in Medicine (AAPM) Report 111 was introduced as an alternative to CTDI in order to keep up with the advances in CT technology(52), as CTDI has proven to be limited in it capability to keep up with these rapid advances in CT. AAPM task group 111 introduced new methodology utilizing a 45-cm long phantom (water or PMMA) with 32-cm diameter (figure 4-7 A). Measurement is made using 0.6 cm 3 farmer type chambers that is capable of reading out with rate greater than 1000 Hz (figure 4-7 B). Measurements are made in the described phantom at different scan lengths using helical mode (spiral), and data gathered from multiple scans at different scan lengths are plotted as shown in figure 4-8 The curve obtained is defined as rise-to-dose equilibrium. As the scan length increases, the dose in the center of the scan increases until it reaches equilibrium. The advantage of this method is that it allows for measuring dose with large phantom that allows for better scatter collection mimicking real patient scenario. 49

71 A B Figure 4-7: Graph showing, (A) 45-cm long phantom (water or PMMA) with 32-cm diameter. (B) 0.6 cm3 farmer type ion chamber (52). Figure 4-8: Graph showing data collected for different scan length, Data gathered until equilibrium is reached (52). 50

72 4.6 Metal Implants Metal implants are among the most common foreign objects to be found in human bodies. But it was not until the 1960s when Charnley successfully introduced metal-onpolyethylene prosthesis. However, the downside of metal-on-polyethylene was the long term use in younger patients (53). That group of patients suffered significant polyethylene wear and need for resurfacing (54). Metal-on-metal prosthesis were developed to meet the demands for more reliability and wear particles, since for the younger, more active patient population, it is expected that the replacement would be used more and for a longer duration Imaging Metal Implants Radiography is routinely used to image postoperative implants; however, it is common to obtain negative results in symptomatic patients, as the massive attenuation of the large implant obscures a significant amount of information (Figure 4-9 B). Crosssectional imaging is usually needed in symptomatic patients with normal radiography. The challenge with imaging large implants is not only restricted to diagnosis of an abnormality or evaluating the condition of the implant. Imaging implants is also very crucial in planning radiation therapy for cancer treatment in regards to localizing treatment region and calculating the needed dose. It is common practice to use computed tomography CT number in delineation of the treatment target and healthy tissue that should be spared, and error in CT number due to metal implant artifact in the CT images 51

73 obtained can lead to significant error in the dose delivery plan and healthy tissue sparing. In proton therapy, the range of protons depends on the composition of the tissue, and errors in tissue CT number can drastically alter the dose distribution (55). Magnetic Resonance Imaging (MRI) has been utilized in imaging joint implants. Significant improvement in image quality has been achieved in using MRI with metal implants. Specialized pulse sequences to reduce metal artifacts have been developed and in many cases MRI has become part of the normal workup for implant evaluation. However, susceptibility artifact in MRI due to inhomogeneity of the magnetic field as a result of the presence of metal in the field is a major concern, not to mention the fact that many patients cannot be scanned with MRI due to the presence of other implants that are incompatible with the magnetic field, preventing those patients from utilizing MRI altogether (53). A B 52

74 Figure 4-9 (A) MRI of hip implant shows susceptibility artifact due to magnetic field inhomogeneity. (B) Radiograph of hip joint implant shows lost information due to the massive attenuation of x-ray by the high Z implant (53) Metal Artifact Reduction Algorithm Evaluation There have been several attempts to evaluate metal artifacts reduction algorithms developed by the different vendors. Evaluation of such algorithms has been primarily based on clinical images that have been corrected using the algorithm under investigation. Even though evaluating clinical images gives a great deal of information with regards to the software capability, it is limited by the physiological and anatomical changes that occur post the implantation, and the possibility of the presence of diseased tissue, which alters the true composition and cannot be compared to normal tissue. In their study to evaluate a metal artifact reduction algorithm in CT, Andersson et al utilized water phantom with two hip implants to evaluate metal artifact reduction algorithm (O-MAR) (figure 4-9) (56). Such a phantom allowed for scanning with or without the implant. This provides a significant advantage over evaluating the O-MAR through actual patient studies, which does not allow for comparison with images without the implant. Besides, using water as the background material allows for easy measurement and evaluation of CT number before and after the algorithm correction. Nevertheless, a drawback to such a phantom design is the lack of a structure that mimics real patients, which is critical, since in true clinical images, there is a wide range of tissues with different densities that would be altered differently when the software (O- MAR) correction is applied. 53

75 Figure 4-10: Water filled phantom including hip prostheses placed on a slab of PMMA (56). Similar work phantom design was performed by Jeong et al. However, a more sophisticated phantom was designed, containing two spinal screws, two sticks of rice cake mimicking larger vessels, and two sausages to mimic retroperitoneal lymph nodes. The background was chosen as 1.0% diatrizoate meglumine and diatrizoate sodium to represent soft tissue in abdominal region (Figure 4-10). (57) 54

76 Figure 4-11: Phantom containing two spin screws, two sausages to mimic retroperitoneal lymph nodes, and sticks of rice cake mimicking larger vessels (57). Using the above phantom allowed for studying the effect of the metal artifact reduction algorithm on maintaining the correct CT number of the surrounding material, along with investigating the possibility of maintaining proper contrast between different objects (inserts) that resemble vessels and lymph nodes. Such a design is a step forward towards better evaluation of MAR algorithms, however, it lacks the accuracy of background material and the inserts CT number. Moreover, the limiting size of the inserts does not allow for evaluating the algorithm performance in regard to small lesions and vessels. Another drawback to such a design is the size of the implant compared to the size of the lesions or targets in the background. MAR algorithm will perform correction to artifacts associated with small metal implants different from that performed 55

77 with large joint implants, so the limited size of the spine screws does not give enough information in regard to the software performance and its success in reversing the artifact and preserving CT number accuracy. Also, it has been noted that the measurement was not done in close proximity to the implant, but rather far from the implant edge where the artifact extends. Significant amount of information lays within the region adjacent to the implant and the surrounding tissue, as this is the area where many of the post-operative complications will occur, hence, the importance of accurately correcting the artifact and CT number within the implant-tissue interface. 56

78 CHAPTER V PRELIMINARY DATA 5.1 Development of scan protocol (CTDI) Phantoms were scanned using several scan protocols. Protocols for both adult abdomen and pediatric abdomen were selected. The protocols are chosen such that a wide range of KVp, mas and beam widths is utilized in order to be able to study the effect of each parameter and the consistency of dose measurements with the expected values. The following parameters were evaluated: - Effect of tube current and study of linearity of the system - Effect of tube voltage on dose with different phantom sizes - Effect of beam width (collimation) - Effect of chamber position, 12 o clock versus 3 o clock position Effect of tube current and study of linearity of the system We will be studying the effect of mas on dose and confirming the linearity of the system under various scanning parameters. Dose was measured using a 32-cm CTDI 57

79 Dose in mgy phantom and a large developed elliptic phantom with abdominal protocol using 120 KVp. mas ranging from 50 to 350 with 50 increments. The maximum error in linearity was found to be 1.4 %. Figure 10 shows the linear relation between mas and dose. 25 Linearity Large CTDI Phantom Large Elliptic Phantom mas Figure 5-1: Dose in mgy vs mas graph using 32-cm CTDI phantom and large elliptic phantom with 120 KVp setting shows the linearity relation Effect of tube voltage on dose with different phantom sizes Tube voltage setting has a significant effect on dose (58); phantoms were scanned with different KVp settings. A wide range of tube currents was used with all available tube voltage settings to investigate the change in dose accompanying tube voltage change. The dose increase with increasing tube voltage (from 80 to 100, 100 to 120, 120 to 140 KVp) is not linear (figure 11). By normalizing dose increase to tube voltage percentage increase, information about the most dose-efficient tube voltage and tube 58

80 current setting can be obtained. Comparison of the effect of tube voltage on dose between different size and shape phantoms will be carried out to investigate possible error in CTDI due to using cylindrical phantom versus newly designed elliptic phantom. All the required scans will be carried out using both pediatric and adult routine abdominal protocol with the appropriate size phantom (59-61) Effect of nominal beam width Z-axis geometric efficiency is defined as the area under the dose profile that falls on the active detector to the total area under the dose profile. Thus, factors that reduce the useful part of the beam along the z-axis direction will cause less z-axis dose efficiency (62-66). The finite size of the focal spot in the x-ray tube gives rise to what is known as penumbra (11,63). In multi-slice CT, x-ray within the penumbra region cannot be used to form an image, therefore, the detector rows have to be within the useful part of the beam in order to form good-quality images (65). Thus, the penumbra region only increases patient radiation dose without any contribution to the imaging process. Wide-beam collimation has an advantage over narrow-beam collimation in that the penumbra region represents a small percentage compared to the useful beam, unlike narrow-beam collimation (figure 13). It is standard procedure to use the maximum possible beam width when developing CT protocols to maximize z-axis geometric efficiency; however, some applications require narrow beam (67,68). Different beam width settings will be utilized 59

81 Dose in mgy in order to investigate the change of this relation with using different phantom sizes and shapes Dose vs KVp for Eliptic Phantom mas 200 mas 300 mas KVp Figure 5-2: Dose vs tube voltage graph shows the non-linear relation Effect of chamber position, 12 o clock versus 3 o clock position Using the 12-o clock position for peripheral measurement is standard practice when measuring CTDI for routine quality control practice. For the purpose of comparing different phantoms and the dose behavior in each of them, the choice of pencil chamber s peripheral position is important. Factors like table attenuation adds to the complexity of this issue, and so measurement will be made using all 4 positions, 12-o clock, 3-o clock, 6-o clock and 9-o clock. This is a an extremely critical step, especially for elliptic phantom measurements, as the radius changes from one point to another and the attenuation profile changes based on that. Table 1 shows CTDI 100 values measured at all 60

82 4 edge positions using CTDI body phantom. Measurements at 3 o clock and 9 o clock positions are the same for each tube current setting. On the other hand, CTDI 100 measurements at the 6 o clock position are 8 to 10% lower than the measurements made at the 12 o clock position. This result shows how CTDI values can be significantly different for the same protocol setting based on where the measurement is taken. This data also suggests that the difference between 12 o clock and 6 o clock measurements is expected to be greater when an elliptic phantom is used mas 12 O'clock O'clock O'clock O'clock Table 5-1 CTDI100 measurement in mgy for 4-edge positions using 32-cm CTDI body phantom. 61

83 Dose in mgy C LP 0deg 19.2 C LP 0Deg mas Figure 5-3: Graph shows the inverse relation between dose and nominal beam width, same protocol settings for 19.2 and 38.4 mm. Dose using 19.2 mm collimation is greater. Figure 5-4: Due to the finite size of the focal spot, geometric penumbra is formed (62). 62

84 5.2 Development of scan protocol (Metal Artifact) Routine shoulder protocols and shoulder implant protocols will be used for patient studies. For Siemens scanners the protocols will be set as follows: Range Patient is positioned with the unaffected arm above the head and the affected arm down by the side with the palm up. Patient is off-centered on the table so that the affected shoulder is entered. Spiral scan to include entire shoulder joint and scapula and all metal. Dose 300 mas 120 Kvp (140 Kvp for metal) CareDose ON Reconstructions Spiral thinnest collimation, 3-mm slice thickness, 3-mm recon interval B30 2nd recon 1-mm slice thickness, 0.8-mm recon interval B20 soft tissue 2-mm X 2-mm axial, coronal and sagittal MPRs B70 bone kernel 63

85 5.3 imar Initial Evaluation Nine patients with metal shoulder implants were selected for the initial evaluation of the imar. Evaluation was made based on visual observation of the metal artifact and also by measuring CT number in regions where information was lost due to the metal artifact and comparing it to CT number from the same region in the image prior to shoulder replacement. Visual evaluation of images corrected with imar show significant reduction in metal artifact (figure 16), however, there still is some loss of information adjacent to the metal implant where important diagnosis is usually made. The visual observation was consistent in all images from the same study, but the degree of residual metal artifact varied between different patients. Table 5:2 shows that applying imar correction provided CT number recovery in regions where the artifact was dominant, and all clinical information was lost. Before imar After imar Mean STD Mean STD Table 5-2 Region of Interest (ROI) measurement before and after imar correction using same position and same size ROI. 64

86 A B Figure 5-5: CT image of patient with metal shoulder implant without any correction algorithm (A) and with imar correction (B). 65

87 CHAPTER VI POTENTIAL FOR REPLACING CTDI PHANTOM WITH MORE REALISTICLY SHAPED PHANTOM TO ADJUST FOR SHAPE INACURACY OF THE CTDI PHANTOM Specific aim 1: Better-designed (human-like shape) phantom yields more realistic dose distribution. In this chapter, the potential for replacing CTDI phantom with a more realistic, ellipticshaped phantom will be investigated, in addition to evaluating the shape dependency when measuring dose. Dose distribution, within the new phantom will also be investigated as it will influence the organ dose within the scanned region. The study will be performed by investigating the dose distribution using Monte Carlo simulation which will help obtaining regional contribution to calculate CTDI. Measurements will be performed using a small and large CTDI phantom and their equivalent elliptic phantom. Siemens and GE CT scanners will be utilized. 66

88 6.1 Abstract Objective: To study the feasibility of using elliptic phantom for CTDI measurements and the difference between the dose to a cylindrical phantom and the dose to an elliptic phantom of the same volume. Materials and Methods: Two elliptic phantoms were manufactured with a cross sectional area and volume equal to that of the large and small CTDI phantoms (32 and 16cm phantoms). Three scanners were utilized in this study. CTDI measurements were made using all 4 phantoms with all available tube potential. Data from each set of phantoms were analyzed and compared. Elliptic phantoms were used to measure CTDI with tube current modulation activated. Conclusion: This study was inconclusive in regard to the possibility and feasibility of replacing the cylindrical CTDI with an elliptic phantom of the same cross sectional area and volume. Also, measuring CTDI when the tube current modulation is utilized was not possible due to poor system reproducibility. 6.2 Purpose Designing a new CTDI phantom that mimics the overall geometry of the human body should presumably offer better understanding of patient and organ dose. Existing CTDI phantoms are cylindrical and mimics human body and head; they are 32- and 16-67

89 cm in diameter respectively. An elliptic phantom should offer a better representation of a large sector of human geometry, hence, will allow the use of dose reduction algorithm (ma modulation in plane) that is usually used when scanning patients. Tube current modulation technique won t be activated when scanning a cylindrical uniform phantom, as the diameter of the phantom does not change in either the xy plane, or along the length of the phantom in the z direction. Tube current modulation is a technique that uses attenuation information from scout images generated by the scanner to adjust the tube current at different tube angles as well as along the z direction (68,69). The adjustment of tube current is done in such a controlled manner as to maintain the similar level of image noise, so that diagnostic quality image is maintained across the length of the scan. Measuring CT dose with the ma modulation turned on, which is the practice used for most of today s body imaging (12,70), allows for better estimation of dose and also better estimation of the actual dose reduction. In addition to the advantages mentioned above, designing an elliptic phantom with a cross-sectional area equal to that of the traditional CTDI phantom will allow for better understanding of the dose distribution within the scanned body. In their research, Huda et al showed the effect of using CTDI phantom to estimate patient and embryo dose in abdominal CT (12). When comparing the use of an adult Rando phantom (Radiology Support Devices (RSD), Long Beach, Ca, USA) and Thermoluminescent dosimeter (TLD) to measure patient/fetal dose to the use of CTDI published values, it was discovered that the CTDI estimate was 2.9 to 4 times lower than the dose obtained using a more realistic Rando phantom. Their research clearly shows that CTDI is not the optimum dose metrics to estimate the patient dose. Such inaccuracy 68

90 in patient and organ dose estimates warrants a need for a better way to measure CTDI. Several researchers suggested adjusting CT output based on the patient size to minimize dose to patient, more importantly in pediatric imaging (75-77). It is becoming common practice for hospitals to estimate patient dose for radiation risk assessment in cases when wrong patients or wrong body parts are imaged. The CTDI related dose metric, more specifically, the dose length product (DLP), is used to estimate the patient effective dose in those events. Using a Rando phantom is not a practical or economical option for periodic quality control practice beyond research work (78-80). CTDI is the gold standard in measuring CT scanner s radiation output (12), and has been adopted by all vendors to serve as a reference for scan protocols dose measurement. It is now a required parameter by the FDA and has to be displayed by the scanner prior to and after each scan. (81). 6.3 Methods and Materials Phantoms Geometry Four Polymethyl methacrylate (PMMA) phantoms were used in this study. Two cylindrical CTDI phantoms (16 and 32 cm) were used for measuring CTDI 100 and CTDI W as described in chapter 4. Two elliptic phantoms, one small and the other large, were designed and manufactured so that they have a volume equal to that of the 16- and 32-cm traditional CTDI phantoms respectively (Figure 6-1). The two sizes phantoms represent adult abdomen (large phantoms) and pediatric abdomen (small phantoms). Each of the phantoms has a center hole and 4 peripheral holes 1 cm from the phantom edge. The 69

91 diameter of the hole is 13 mm to allow for inserting a pencil chamber to measure CTDI 100 in the center and in the 12, 3, 6, and 9 o clock positions. In order to evaluate the effect of object shape on radiation dose, the volume and the cross sectional area of the elliptic phantom and the cylindrical phantom have to be the same. Also, the effect of kvp will be studied to investigate how the change in shape, hence, the change in beam hardening and attenuation, will change the delivered dose. A B Figure 6-1: Elliptic phantoms. (A) 16 cm equivalent small phantom. (B) 32 cm equivalent large phantom Imaging Protocols Three different scanners were utilized in this study, Siemens Definition Flash 128, Siemens Emotion 16 (Siemens Healthcare, Forchheim, Germany), and General Electric Light Speed 32 (General Electric Healthcare, Waukesha, Wisconsin, USA). All measurements were made using a Raysafe X2 radiation meter (Fluke Biomedical, Cleveland, Ohio, USA). The meter was calibrated as required by the Ohio department of 70

92 Health regulations. The most clinically-used collimation settings were utilized, including at least one small and one large collimation setting. All available tube voltages were used at each collimation setting. Some of the settings used were not optimal for clinical practice, for example, using 80KVp with mas setting less than 300 when scanning a large phantom. Such a setting would not be used in clinical application, as the image quality would be significantly degraded; however, it is very useful in studying the effect of KVp change on dose. The first step of the study was to investigate the output linearity of each make and model at different tube potentials and beam collimations. The linearity test was performed using the CTDI head phantom (16 cm) with the clinical adult head protocol, with the probe in the central hole of the phantom. The number of data points acquired at each scan setting was determined based on the results of the linearity check of all scanners (more details on linearity test in chapter 7). For Siemens Emotion scanner, percent error in reproducibility was tested using the following equation: % Error =( Max R-Min R)/(Average(Max R, Min R)) (6-1) Where Max R is the maximum meter reading and Min R is the minimum meter reading in a set of measurements made at the same protocol setting with the same phantom. Adult head protocol was used for testing the percent error in reproducibility with 120 kvp tube potential, 300 mas tube current and 10-mm beam collimation. 71

93 Percent error in reproducibility was performed using the 16-cm CTDI phantom with the probe in the center hole; ten measurements were made with this setting CTDI Measurement CTDI measurements were performed on each of the 4 phantoms. CTDI 100 and CTDI w were calculated, using the procedure described in chapter 4, for all phantoms including small and large elliptic phantoms. All measurements for small phantoms were made with the phantom positioned on the table rather than in the head holder. For calculating CTDI w, measurements were made at the center and the peripheral positions of the phantom and CTDI w was calculated using the following equation: (12,82,83) CTDI W = 1/3 CTDI 100, center + 2/3 CTDI 100, peripheral (6-2) CTDI 100 was not uniform across the plane of the image, but varies from center to surface (84-86), and the dose to the peripheral (surface) region was higher than the center of the phantom. The dose distribution and the coefficients 1/3 and 2/3 in equation 6-1 were reassessed using Monte-Carlo simulation. Siemens definition flash was used for the simulation, with the following parameters: single axial scan, 80, 100, 120, 140 kvp, mm beam collimation and standard filter (wedge 1 + wedge 3). Monte-Carlo simulation showed that the coefficients 1/3 and 2/3 were found to be accurate and a true representation for dose distribution. The same Monte-carlo simulation technique was used to calculate CTDI 100 coefficients for the elliptic phantom. Calculating CTDI w was performed using two different methods. The first method was to calculate CTDI w using equation 6-2. The 72

94 second method utilized Monte-Carlo simulation to estimate the dose distribution and acquire CTDI w coefficient based on the phantom size and shape (figure 6-2). Equation 6-2 shows how CTDI w was calculated using new coefficients acquired through Monte- Carlo simulation. CTDI W = 5/12 CTDI 100, center + 1/4 CTDI 100, major + 1/3 CTDI 100, minor (6-3) CTDI 100, major and CTDI 100, minor are the measurements made at 3 o clock and 6 o clock positions respectively. Minor and major refer to the shortest and longest diameter (or radii) of the elliptic phantom (figure 6-3). In addition to measuring CTDI w at fixed tube current in axial mode, another set of measurements was performed on the elliptic phantom using tube current modulation in axial mode. A B 73

95 C D Figure 6-2: Monte-Carlo Simulation showing the relative dose distribution in Elliptic and cylindrical phantoms. Areas with the same color represent areas with same average dose. (A) 16cm equivalent elliptic pediatric abdomen phantom. (B) Conventional 16cm CTDI pediatric body phantom (C) 32 cm equivalent elliptic adult abdomen phantom. (D) Conventional 32cm CTDI adult body phantom. W minor w major Figure 6-3: Image of large elliptic phantom used in the study with the minor and major radii used in CTDI calculation. The measurement of dose to an elliptic phantom using protocol setting with the tube modulation was performed to study the effect of the tube modulation on measured CTDI values. Siemens Emotion 16 scanner was used for this part of the study. Body 74

96 protocol utilizing the tube modulation with quality reference mas of 300 was used. Another set of measurements was made without the tube modulation, but with the same tube voltage and fixed mas at Statistical Analysis For the elliptic phantom, CTDI w, calculated using equation 6-1, was compared to CTDI w calculated using equation 6-2 with newly simulated coefficients. CTDI w data from the cylindrical and elliptic phantom was acquired using Siemens Definition Flash scanner. The difference between doses in the cylindrical and elliptic phantoms was reported for each tube voltage. A two-tailed paired t-test with significance level of 0.05 was performed for each tube voltage and also for each collimation setting to study their effects on measured dose in cylindrical and elliptic phantom. The same analysis was performed on both large and small phantoms. The dose data from elliptic and cylindrical phantoms were plotted against the tube voltage at the same tube current. The correlation between increasing tube voltage and increasing radiation dose for cylindrical and elliptic phantoms was calculated and compared, and the same analysis was performed for small and large phantoms. Measurements made on the elliptic phantom utilizing the tube modulation was analyzed and compared to measurements made on the same phantom without the tube modulation but with the fixed tube current equal to the quality reference mas. 75

97 6.5 Results Linearity and Reproducibility All Three scanners were found to have percent error in linearity less than 2%. Siemens Flash scanner s percent error in reproducibility was 0.1% CTDI in Elliptic Phantom Table 6-1 and table 6-2 are a summary of measured CTDI w in large and small elliptic phantoms respectively, using the conventional coefficients and new coefficients. Data shows that utilizing the proper coefficients for the change in shape, but no change in total volume, resulted in a significant reduction in the calculated dose (Large phantom with p = 0.9; small phantom with p = 0.9). For the same protocol setting, the imparted radiation energy per unit volume to the small phantom is larger than that imparted to the large phantom. 76

98 70 KVp 80KVp 100KVp 120 KVp 140 KVp mas CTDI/New coefficients CTDI/Conventional coefficients % decrease 22.2% 21.1% 20.6% CTDI/New coefficients CTDI/Conventional coefficients % decrease 16.1% 16.1% 15.9% CTDI/New coefficients CTDI/Conventional coefficients % decrease 15.8% 17.4% 15.4% CTDI/New coefficients CTDI/Conventional coefficients % decrease 13.8% 15.5% 14.3% CTDI/New coefficients CTDI/Conventional coefficients % decrease 13.9% 13.6% 14.0% Table 6-1 Calculated CTDIw (in mgy) values for a large elliptic phantom using various tube potentials and utilizing two different sets of coefficients, newly simulated coefficients and conventional CTDI coefficients. Data shows a significant difference between both cases. Measurements were made using Siemens Definition Flash scanner. 77

99 70 KVp 80 KVp 100 KVp 120 KVp 140 KVp mas CTDI/New coefficients CTDI/Conventional coefficients % decrease 13% 13% 13% CTDI/New coefficients CTDI/Conventional coefficients % decrease 11% 11% 11% CTDI/New coefficients CTDI/Conventional coefficients % decrease 10% 10% 10% CTDI/New coefficients CTDI/Conventional coefficients % decrease 9% 9% 9% CTDI/New coefficients CTDI/Conventional coefficients % decrease 9% 9% 9% Table 6.2: Calculated CTDI w (in mgy) values for a small elliptic phantom using various tube potentials and utilizing two different sets of coefficients, newly simulated coefficients and conventional CTDI coefficients. Data shows less significant difference in comparison to the large phantom. Measurements were made using Siemens Definition Flash Comparison of Radiation Dose in Elliptic and Cylindrical Phantom With fixed tube current, collimation, and tube voltage, measurements showed that calculated radiation dose values to the elliptic phantom were less than that to the cylindrical one. The percent difference in dose varied between all three scanners and also between small and large phantoms, however, the data was consistent in regards to 78

100 the decrease in dose when elliptic phantom is used. For the small phantom, the difference between the dose to the cylindrical and the dose to the elliptic phantom was insignificant (p>0.05) for all the scanners and can be attributed to slight inaccuracy in phantom positioning and/or fluctuation in meter reading. For the large phantom, the difference between the dose to cylindrical and the dose to elliptic phantom was more significant for all the scanners. The average decrease in dose was 10%, 5% and 6% for the Flash, Emotion and Light speed scanners respectively (p<0.05). The results of Monte-Carlo simulation showed that there was no difference between doses to cylindrical and elliptic phantoms of the same volume CTDI versus Tube voltage in Cylindrical and Elliptic Phantoms With a fixed tube current and increase in tube voltage, there was an increase in dose in all phantoms with all scanners (Large phantoms r =0.99, small phantoms r =0.99). 300 mas tube current was used. The utilized scanners did not employ the same collimation setting. Under ideal condition, CTDI w measurements should be comparable for the same tube current and tube voltage, however collimation efficiency varies between scanners which give rise to the difference between measurements mad at the same tube voltage and tube current. 79

101 Dose, mgy Dose, mgy 60 Dose vs Voltage, Large Cylindrical Phantom Flash Emotion Light speed Tube Voltage A 60 Dose vs Voltage, Large Elliptic Phantom Flash Emotion Light speed Tube Voltage B Figure 6-4 : (A) Graph shows dose as a function of tube voltage using cylindrical phantom for three different scanners. (B) Graph shows dose as function of voltage for the same scanners using elliptic phantom. 80

102 6.5.5 Comparison of Measurements Made With and Without Utilizing Tube Modulation. Measurements made utilizing tube modulation suffered severe fluctuation in the measured value at the same scan settings. Accurate CTDI calculation was not possible due to such fluctuation. Table 6-3 shows the percent error in reproducibility measured at 3 positions within the large elliptic phantom with the tube modulation on and with the tube modulation off. Percent Error in Reproducibility Position Center 12 O'clock 3 O'clock Tube Modulation on 23.00% 12.40% 25% Tube Modulation of 0.02% 0.02% 0.10% Table 6-3 Reproducibility error for with lareg phantom and different positions measurments, center, 12 O clock, and 3 O clock. Data shows calculated error with and without utilizing the tube modulation. 6.6 Discussion and Conclusion The main advantage of this study is that it utilizes two elliptic phantoms that have the same cross-section areas and volumes as the small and large CTDI phantoms. When cylindrical CTDI w coefficients were applied to the measurements made with the elliptic phantom, the calculated dose was found to be larger by 13% to 22 % for the large phantom and by 9% to 13% for the small phantom than that calculated with new coefficients obtained through Monte-Carlo simulation. Such difference in calculation 81

103 demonstrates the effect of the scanned object s shape on dose distribution across the field of view. Monte-Carlo simulation showed that new CTDI coefficients will be needed for any change in phantom shape. Different elliptic phantoms with different radii ratios were simulated, and the results confirmed that each one of them would have a different set of coefficients. This indicates that more work in the area of organ dose is warranted. The pediatric population is a main beneficiary of dosimetry studies, as children under the age of 10 are significantly more sensitive to radiation than adults (86-89), and investigating the actual change in dose distribution for different-size children will allow for developing scan techniques that spare sensitive organs based on their position within the field of view. Our study confirmed that increasing the tube voltage will result in increasing the radiation dose. The rate of change (percentage of increase) in CTDI w with increased tube voltage was the same for cylindrical and elliptic, so the change in shape for fixed volume has no influence on the effectiveness of tube voltage increase in regards to dose. More investigation is necessary to study whether the change in the tube voltage s effect on image contrast in elliptic phantoms will differ from that in a cylindrical phantom, since changing the tube voltage has a significant influence on image contrast (90-94). Future work can utilize the same elliptic phantoms after modifying the rod holes to accept low-contrast objects. When the comparison was made between the dose to cylindrical phantom and the dose to the elliptic phantom, experimental data showed that the dose to the elliptic phantoms (both small and large) was less than the dose to the equivalent cylindrical phantoms (both small and large). The percent difference between the dose 82

104 delivered to the small cylindrical phantom and that delivered to the small elliptic phantom was less than the difference between the large phantoms. However, when Monte-Carlo simulation was utilized to calculate the dose to cylindrical and elliptic phantoms under the same experimental conditions, the estimated dose to elliptic and cylindrical phantoms showed no significant difference, indicating that the dose to the object is a function of its size, not shape. We were unable to explain the discrepancy between the experimental and simulated dose, as the difference between the cylindrical and elliptic dose was investigated using three different scanners exhibiting the same results. Thus, more investigation is required to better understand the relationship between CTDI and phantom shape. The attempt to measure CTDI with tube modulation using the elliptic phantom was unsuccessful. The utilized scanner was tested and its output was found to be extremely linear and reproducible, however, this was not the case when tube current modulation was utilized. The tube current modulation employs a quality reference technique that uses attenuation information from the scout exam and compares it to the average-size patient (70 to 80 kg) information stored in the system as the quality reference. It is unclear how the system is comparing the information about the phantom attenuation to the stored quality-reference patient information. The discrepancy between what the system is expecting for the attenuation profile and what was input to the system from the phantom scout image can be the reason behind such a large error in reproducibility. Future work should include obtaining more information regarding how the tube current modulation conducts that comparison. 83

105 CHAPTER VII USING CT FREE-IN-AIR DOSE TO ESTIMATE COMPUTED TOMOGRAPHY DOSE INDEX (CTDI) Specific Aim 2: Hypothesis: Computed tomography dose index can be estimated from CT dose measured free-in-air. The possibility of estimating computed tomography dose index through measuring CT dose in air will be investigated. The new setup will utilize pencil ion chamber used for traditional CTDI measurement. Dose measured in air will be compared to traditional CTDI values for development of conversion factors. The American Association of Physicists in Medicine (AAPM) Task group 111 report outlines the latest development in measuring radiation dose in MDCT (95-97). TG 111 suggests using a 50-cm long with 30-cm diameter water-filled phantom or polyethylene phantom with the same dimensions. Using a large phantom with the above dimensions is feasible for routine quality control measurements, so developing conversion factors that allow in-air measurements is clearly a more realistic and practical way. 84

106 7.1 Abstract Objective: To develop free-in-air to CTDI conversion factor for routine quality control and major post repair system check. Methods: Analysis of CTDI fluctuation and it s effect on CT scaner performance was performed by studying the annual variation of CTDI for 12 CT scanners over 4 years period. Effect of CTDI fluctuation on image quality was studied by analyzing the same scanner s daily quality control failures. Stability of modern CT scanners was studied by analyzing the failures in daily quality control for 70 CT scanners over the same 4 years period. Next step was to measure free-in-air and CTDI for three sets of scanners, each set consisting of two of the same make and model scanners to allow for apple to apple comparison of conversion factors.. Results: Fluctuation in CTDI was found to have no effect on system performance. Freein-air to CTDI conversion factors were obtained for the three sets of scanners, same make and model scanners had very consistent conversion factors (p-value < 0.05). Conclusion: Using free-in-air to CTDI conversion factor is possible for routine annual and post repair testing, conversion factors are to be established upon acceptance of scanner and then used for all subsequent testing. 7.2 Purpose Computed tomography dose index (CTDI) has been in use since its development over 30 years ago. Measuring CTDI has been very useful in fulfilling quality control and 85

107 routine maintenance requirements. Also, system and protocol comparisons are done through comparing CTDI values. However, it is clear that there are many cases where CTDI falls short due to the rapid development in the CT technology in the past two decades (98). Measuring X-ray dose in-air has been utilized in other modalities as the gold standard for decades (99-103). Preliminary data has shown that it is possible to estimate CTDI by performing simple free-in-air measurement. Upon installation of a new system, measuring CTDI and free-in-air dose can be used to calculate free-in-air to CTDI conversion factor. For quality control purposes, the advantage of free-in-air to CTDI conversion utilization is that this measurement is much simpler and less timeconsuming, which allows for quicker system turnover for clinical use. This is critical, as the need for maximizing system utilization for better financial outcome has drastically increased, especially when hospital s profit margin has been significantly reduced (104, 105). Also, the frequency of CTDI measurement for clinical scanners has increased as a result of recent changes in regulations that require measuring CTDI after every major repair performed on the system, which may increase the down time (105,106). Free-inair measurement can be utilized for quality control purposes with a high degree of confidence due to the level of stability and accuracy that a modern x-ray tube has reached with regards to energy spectrum stability. It is an extremely rare event for a CT scanner to suffer significant change in tube output causing patient harm, which is the main reason for periodic CTDI check, however, it is a requirement and good practice to confirm the stability of the tube output periodically and after major system repairs ( ). 86

108 7.3 Methods Experimental Setup and Parameter Several measurements were made to investigate the linearity of each make and model of scanners at different tube potentials and beam collimations. Based on linearity evaluation, it was determined how many data points were needed for subsequent measurements. Data was acquired using Siemens Emotion 16 MDCT (Siemens Healthcare, Forchheim, Germany), Philips Brilliance 16 (Philips Medical Systems, Cleveland, Ohio, USA) and GE BrightSpeed 16 (General Electric Healthcare, Waukesha, Wisconsin, USA). All measurements were made using Fluke biomedical TNT meter (Fluke Biomedical, Cleveland, Ohio, USA) and Raysafe X2 (Fluke Biomedical, Cleveland, Ohio, USA). Linearity was obtained using the CTDI head phantom (16 cm). Clinical adult head protocol was used for linearity measurement with the probe in the central position (Figure 7-1). Figure 7-1: Head CTDI phantom placed in the head holder with the pencil chamber in the center position for measuring system linearity. 87

109 Free-in-air measurements were made as shown in Figure 7-2, a 100mm pencil chamber was suspended in air and above the table to account for table attenuation as it is accounted for in CTDI measurement setup, and the chamber was positioned in the isocenter of the scanner. CTDI was measured as described in chapter 6 and according to AAPM report 96 (41). Free-in-air and CTDI measurements were made at all available tube potentials and the most frequently used beam collimations to allow for investigation of the effect of both kvp and beam collimation on dose in air and compare it to the same effect on CTDI measurement. CTDI measurements were made with both 16- and 32-cm phantoms to allow for establishing conversion factors for both adult and pediatric protocols. Analysis of collected CTDI data from multiple scanners with different make and model over a period of 4 years was performed as part of a systems stability study and to investigate what level of quality control is needed. The analysis will provide a better understanding of computed tomography s ongoing failure and its clinical significance. Based on the study results, it will be decided whether simple free-in-air measurement can be utilized and whether it is sufficient enough for routine quality control purposes. 88

110 Figure 7-2: 100mm pencil ion chamber suspended in air at isocenter for free-in-air dose measurement Measurements and Data Analysis System Linearity Tables 7-1, 7.2 and 7-3 display the summary for measured exposure at various mas values and corresponding measured exposures for Philips Brilliance, Siemens Emotion, and GE BrightSpeed respectively. Maximum error in the exposure per mas ratio at each data point is calculated using equation 7-1 Maximum Error = (max mr/mas) (min mr/mas) (max mr/mas) + (min mr/mas) (7-1) 89

111 Exposure (mr) 12 mm 24 mm mas Exposure (mr) mr/mas Exposure (mr) mr/mas Table 7-1 Measured exposure and exposure per mas for 12mm and 24mm collimation at 120 KVp tube potential (Philips Brilliance) Exposure (mr) VS mas mm 24mm mas Figure 7-3: Exposure as a function of mas (Philips Brilliance). 90

112 Exposure (mr) 10 mm Collimation 16 mm Collimation mas Exposure (mr) mr/mas Exposure (mr) mr/mas Table 7-2 Measured exposure and exposure per mas for 10- and 16-mm collimation at 120 kvp tube potential (Siemens Emotion). 900 Exposure (mr) VS mas mas 10mm 16mm Figure 7-4: Exposure as a function of mas (Siemens Emotion). 91

113 Exposure (mr) 5 mm Collimation 10 mm Collimation mas Exposure (mr) mr/mas Exposure (mr) mr/mas Table 7-3 Measured exposure and exposure per mas for 20-mm and collimations at 120 KVp tube potential (GE LightSpeed VCT 32 ) Exposure (mr) VS mas mas 5mm 10mm 92

114 Figure 7-5: Exposure as a function of mas (GE Light Speed). System linearity tests for Siemens, Philips and GE scanners showed extremely linear output responses with any change in tube current, as shown in figures 7.3, 7.4, and 7.5, for Philips, Siemen and GE scanners respectively. Tube output per unit mas is constant with the tube current changes from 50 to 350 with 25 mas increment. Maximum error was calculated for all 6 sets of measurements using equation 7.1 and is shown in table 7.4. Scanner Maximum Error: Philips Brilliance 12mm Philips Brilliance 24mm Siemens Emotion 10mm Siemens Emotion 16mm GE Light Speed 5mm GE Light Speed 10 mm 1,5 % 1.8 % 1.8 % 1 % 1.1% 1.2% Table 7-4 Maximum error in linearity for Philips, Siemens and GE scanners at different collimations. Maximum error in linearity was found to be at values < 2%. Such insignificant change is usually due to meter variation and calibration as ion chambers are sensitive to pressure and temperature fluctuation in the scan room. Great level of accuracy was achieved in regard to phantom positioning in the scanner isocenter utilizing the scanner alignment laser light, however, it is not uncommon for scanner alignment laser to be slightly out of alignment which can result in the ion chamber being positioned slightly off isocenter, and in turn disrupt the phantom symmetry based on the tube firing angle. These 93

115 factors play a role in the small error in system linearity, but it is considered within normal system variation. The above data shows that systems linearity does not have a significant effect on the data accuracy. Due to good system linearity, three measurements were made at each station, 100, 200, and 300 mas, with three repeated measurement at each mas CTDI Fluctuation CT technology requires high power tubes due to the relatively long scan time that can last up to 90 seconds. Typically, maximum power of 20 to 120 KW is the rating of CT tube; most CT tubes operate with kvp from 80 to 140 kvp. Great effort and investment have been devoted to the development of more reliable and stable tubes that can sustain such high work load with consistent image quality (8, ). Such an effort has been rewarding, as x-ray tubes performance have matured over the past two decades and have shown significant improvement in stability. However, measured CTDI can fluctuate over time. According to the American College of Radiology CT accreditation program, measured CTDI is expected to deviate by up to 20% from scanner-reported CTDI, and so it recommends that change in measured CTDI from year to year be within 5%. However, this is not a requirement (105,106). Table 7.4 shows a list of 12 scanners (Siemens, Philips, and GE) and the CTDI performance over a 4-year period. Investigated scanners included wide range of technologies as new and older models were chosen for the study. Also, PET/CT and SPECT/CT scanners were included in the investigated systems. 94

116 The mean of the annual change in CTDI is 5% and standard deviation is 6. These data show that CTDI changes for the same protocol can vary significantly from year to year, however, the scanner listed below has shown diagnostic image quality with no significant maintenance issues or any clinical image quality related problems. Annual Change in CTDI (percentage) Scanner Philips Brilliance Ge Bright speed Siemens Definition AD Siemens Sensation Philips ICT Siemens Emotion Biograph PET/CT Definition AS Siemens Sympia True Point SPECT/CT * NA Philips Brilliance GE Bright speed Philips Brilliance Table 7-5 Annual change in CTDI measurement for adult head protocol, includes Siemen, GE, and Philips scanners including PET/CT and SPECT CT. 95

117 Scanner Number of Daily QC Failures per Year Philips Brilliance Ge Bright speed Siemens Definition AD Siemens Sensation Philips ICT Siemens Emotion Biograph PET/CT Definition AS Siemens Sympia True Point SPECT/CT Philips Brilliance GE Bright speed Philips Brilliance Table 7-6 Number of failures in daily QC per year; data shows extremely stable performance with regard to CT number, noise and image artifacts. Table 7.6 shows the number of failures of daily quality control tests per year for the same period that annual change in CTDI was investigated. Only failure related to system image quality and dose were investigated. Irrelevant failures such as mechanical failures and failure due to external sources (for instance, chillers failure and power outage) were not part of the analyzed data. All scanners under investigation showed extremely stable performance in regards to CT number accuracy, noise and image artifacts. The data shows that there is no association between fluctuation in CTDI and the daily quality control testing failure rate (p-value < 0.05). Also it is important to note that CTDI fluctuation has been constantly within the allowable absolute limits in comparison 96

118 to the displayed CTDI as it was constantly within 20% of the displayed CTDI (required by ACR accreditation program) (105). A general study of the daily quality control failure rate was performed. A total of 70 CT scanners were used for the study, including Siemens, Philips and General Electric scanners. Daily quality control for all scanners over a period of 4 years ( ) was investigated. Table 7-7 is a summary of findings for failure in daily quality control over the 4-year period. A total of 125 daily failures with an annual failure mean of and 0.45 per scanner. This data provides great insight with respect to the level of stability in CT in terms of CT number and noise stability, as the data listed below pertains only to failures due to system components that can result in a significant decrease in image quality and not to failure due to mechanical and software malfunction or external causes like power outage. Year Daily QC Failure Table 7-7 Number of failures in daily QC for a total of 70 scanners over a 4-year period CTDI and Free-In-Air Measurement CTDI measurements were performed according to the method explained in chapter IV. Routine adult body and pediatric body protocols were measured. Using adult body and pediatric body protocols allows for calculating conversion factors for both CTDI phantoms (16- and 32-cm). Measurements were made on 3 sets of scanners, 2 97

119 Siemens Emotion 16, 2 Philips Brilliance 16 and 2 General Electric Light Speed. Free-inair measurements were made using equation 7-2, D air (rad) =C.f (rad/r). 100-mm.meter reading( R)/N.T (mm) (7-2) Where C is the chamber calibration factor f-factor (f ) is (R) to absorbed dose (rad) conversion factor N is the number of rows T is detector width Tables 7.7, 7.8, 7.9 list air to CTDI conversion factors for 3 sets of scanners and the percent difference in the conversion factors for each set; each set of scanners consists of two scanners of the same make and model. CTDI conversion factor (t.test, p-value =0.9). The data shows very consistent air to All scanners showed very consistent results across all tube voltage stations. Both free-in-air and CTDI behaved in the anticipated way. With the change to wider-beam collimation, the dose became more efficient as the over beaming to main beam width ratio decreased. 98

120 LARGE PHANTOM (ADULT) LARGE PHANTOM (ADULT) KVp Collimation (mm) Air to CTDI Conversion Factor % Difference Air to CTDI Conversion Factor % Difference CT1 CT2 CT1 CT % % % % % % % % % % % % % % % % % % % % % % % % Table 7-8 Conversion factors for 2 Philips brilliance 16 scanners, using all available KVp at four different collimations using abdomen protocol and 32-cm CTDI phantom. 99

121 LARGE PHANTOM (ADULT) SMALL PHANTOM (PEDIATRIC) KVp Collimation (mm) Air to CTDI Conversion Factor % Difference Air to CTDI Conversion Factor % Difference CT1 CT2 CT1 CT % % % % % % % % % % % % % % % % % % % % % % % % Table 7-9 Conversion factors for 2 Siemens Emotion 16 scanners, using all available KVp at four different collimations for 32- and 16-cm CTDI phantoms (adult and 100

122 KVp LARGE PHANTOM (ADULT) Collimation (mm) Air to CTDI Conversion Factor % Difference SMALL PHANTOM (PEDIATRIC) Air to CTDI Conversion Factor % Difference CT1 CT2 CT1 CT % % % % % % % % % % % % % % % % % % % % % % % % Table 7-10 Conversion factors for 2 GE BrightSpeed 16 scanners, using all available KVp at three different collimations for 32- and 16-cm CTDI phantoms (adult and pediatric). 7.4 Discussion and Conclusion The dose delivered to the patient or a scanned object partially depends on the amount of scatter photons created within the object ( ). CTDI phantom is clearly not a realistic object to be used as a measure for the dose delivered by each protocol. CTDI phantom is 15 cm long, and such short length is not sufficient to simulate actual scan. Nevertheless, building a sufficiently long phantom requires an extremely large and heavy phantom, which is obviously an unfeasible option for ongoing quality control. 101

123 Scatter in CTDI phantom is limited to the phantom length, free-in-air does not account for scatter as it utilizes a very small air-filled chamber, which is considered one of the limitations of using free-in-air technique. Also free-in-air technique does not account for spectrum differences. As a reference dose measurement, both CTDI and free-in-air measurements do not accurately account for scatter photons. Free-in-air dose measurement suffers the same limitation of CTDI technique; it is limited to the 10-cm length. Also, both CTDI and free-in-air are simple dose references that do not represent an actual patient dose. For the purpose of quality control, CTDI has served and still serves as a good technique for monitoring scanner output and for comparison between scanners and protocols Free-in-air can be utilized the same way CTDI has been used for the past 3 decades as a dose reference. Comparison between same make and model scanners showed that same tube model will have same conversion factors regardless of the system or the tube age. We concluded that free-in-air to CTDI conversion factors can be acquired during acceptance testing and used for all subsequent routine system evaluations to acquire CTDI. Future work should include a detailed study of the effect of the x-ray beam spectrum when built-in filtration is inadequate on free-in-air measurement. Inadequate or missing copper filters in the CT tubes were discovered during CTDI measurements done post system repair. The change in beam profile due to missing filtration results in a significant change in dose and measured CTDI beyond the allowed limit. The effect of 102

124 missing filtration and the drastic shift in the x-ray beam spectrum on free-in-air is not fully understood and more work is warranted to confirm the effectiveness of free-in-air as a dose reference technique. 103

125 CHAPTER VIII EVALUATION OF ITERATIVE METAL ARTIFACT REDUCTION (imar) Vs. FILTERED BACK PROJECTION (FBP) IN CLINICAL AND PHANTOM STUDIES Specific Aim 3: Hypothesis: imar allows better CT number recovery and reduces image noise in patients with shoulder implants. In this chapter, the effectiveness and accuracy of iterative Metal Artifact Reduction (imar) (Siemens Healthcare, Germany) in reducing metal artifact, recovering CT number, and reducing noise streaks artifact will be evaluated. imar evaluation will be carried out using two steps. The first step is to analyze and compare the quality of clinical images of patients with shoulder implants with and without applying imar to the images. Clinical images prior to the shoulder replacement will serve as a baseline for measurement. This step will allow for real clinical images analysis. The second step will utilize newly designed arthroplasty shoulder phantom that was custom made for 104

126 evaluating the imar algorithm. The phantom will be scanned with and without the metal implant inserts, the purpose of which is to accurately evaluate the image properties with imar correction and compare it to the image of the same phantom without the metal implant inserts. 8.1 Abstract Objective: To investigate the capability of imar algorithm to recover CT number and reduce metal artifact. Methods: Thirty patients with shoulder implants were selected. All patients had pre- and post-operative shoulder CT scan without intravenous contrast enhancement. Images were reconstructed using imar and FBP. Visual evaluation was made between the two sets of reconstructions, then, quantitative analysis was performed by measuring muscle, subcutaneous fat and bone CT numbers both at hardware level and distant from it. A two-tailed paired T-test with significance level of 0.05 was performed. Arthroplasty phantom was also used, and the same analysis was made. Results: For visual evaluation of patient images, imar showed consistent improvement in image uniformity and significant reduction in streaking artifact. Quantitative evaluation at the hardware level showed significant improvement in CT number for muscle, fat and bone tissue (muscle p < 0.01; fat p <0.03; bone p <0.05). Distant from the hardware, there was no significant difference (muscle p > 0.05; fat p > 0.05; bone p > 0.05). For unilateral phantom at the hardware level, there was significant improvement in CT numbers of muscle and bone tissue (muscle p < 0.001; bone p < 0.01). There was 105

127 also significant improvement in noise reduction (muscle p < 0.001; bone p < 0.01). Away from the hardware, there was no significant change in CT number (muscle p > 0.05; bone p > 0.05). Noise in muscle and bone tissue away from the hardware was significantly reduced (muscle p < ; bone p < 0.001). For bilateral phantom at the hardware level, there was a statistically significant improvement in CT numbers of muscle and bone tissues (muscle p < 0.01; bone p < 0.001). Also, there was a statistically significant improvement in noise reduction (muscle p < 0.001; bone p < 0.01). Away from the hardware level, there was no significant change in CT number of muscle or bone tissue (muscle p > 0.1; bone p > 0.1). There was a statistically significant reduction in noise (muscle p < 0.01; bone p < 0.001). Conclusion: imar algorithm improved image quality, reduced artifact, recovered CT number of muscle, fat and bone, and reduced the overall noise in the image. 8.2 Introduction The first total shoulder replacement was performed by Jules E. Pean in It was then removed, two years later, as the patient developed an infection. However, it was considered a successful surgery, as it improved the joint function (113, 114). Prosthetic shoulder implant went through over 70 different developments over the past century. Today, more than 53,000 total shoulder replacements are performed annually in the United States (115). In addition to shoulder replacement, knee and hip replacement have seen a significant increase in number of procedures; more than 900,000 knee and hip replacements are performed in the United States each year (115). 106

128 Shoulder joint replacement can be one of 4 types: anatomic total shoulder arthroplasty, reverse total shoulder arthroplasty, hemiarthroplasty and humeral head resurfacing. The type of surgery is selected based on several parameters including patient age, activity, type of joint or bone damage, and the condition of the rotator cuff. All types employ a metal implant that can vary in size and shape (116). Shoulder replacement surgery complications can range from a simple wound infection to deep infection that may require surgical intervention. Also, the prosthesis components may be loosen or dislocated, requiring additional surgeries. All post-operative complications will need an imaging modality to be used for evaluation; usually radiography is a standard modality for initial evaluation, however, computed tomography provides significantly more information that is crucially required for evaluating the condition of the implant (11-13,27). The decision for further treatment or evaluating the prognosis of the procedure is usually made based on this information. CT images of body parts that include any type of metal implants results in an artifact that degrades the image to non-diagnostic quality. The severity of the metal artifact depends on the size and type of metal used. It also depends on the scan protocol (11,12,27,121,123). Metal streak artifacts occur due to photon starvation, beam hardening and scattered photons, as high-attenuating metal implants significantly reduce the number of photons reaching the detectors (124, 125). Metal artifacts also disturb the dose distribution during radiation therapy for cancer treatment, as streaking artifact significantly disrupts the organ boundary definition ( ). Metal artifact results in inaccurate attenuation correction for PET/CT and SPECT/CT studies, as the photon starvation due to the high attenuating implant results in under-correction. The incorrect 107

129 data from CT is applied to the transmission data resulting in significant error in the transmission data (120). Iterative reconstruction technique was recently introduced to many clinical applications for MDCT as a method of reducing noise in images acquired with low radiation dose ( ). Metal artifacts result in significant reduction in SNR, which reduces low contrast detectability in images. Several metal artifact reduction techniques were evaluated previously with very promising results. Boas et al showed that metal detection technique (MDT) algorithm reduced streaks, providing improved image quality (123). 8.3 Methods Patient Information and Scanning Parameter Forty shoulder-implant patients were selected for the study at the initial stage (HIPAA compliant and IRB-approved-informed consent waived). Ten patients were rejected due to difficulty in making accurate measurement for the same tissue on preoperative and post-operative studies. Thirty patients were used in the study; all patients had preoperative and post-operative shoulder CT scans without intravenous contrast enhancement. The mean age was 63.7 years (range: years of age). There were 9 females and 21 males. As per the hospital s clinical protocol, the kvp was set at 140 and the quality reference mas was set at 300. The thinnest collimation available was used and the images were reconstructed with 3-mm slice thickness. B30S Kernel was used for FBP reconstruction; the same studies were reconstructed with imar algorithm. Both FBP and imar reconstructions were set to use the same field of view. imar 108

130 reconstruction was performed on an off-line workstation, the reconstruction time was, on average, 25 minutes per study. Visual evaluation of the clinical images with the FBP and imar was the initial step in the evaluation process. Two slices were chosen, one with the most severe streaking artifact at the hardware level and the other slice away from the hardware, were chosen for the evaluation. Window width and window level were set at the default bone setting for both reconstructions. The main focus of visual evaluation was to assess the uniformity of the soft tissue (muscle and fat) in regions where streaking artifact is the worst, adjacent to the humeral component of the hardware. A simple three-point scale was used to evaluate uniformity: 3, if the tissue has normal gray scale appearance at the optimized window width and window level without any sign of streaking artifact; 2, if the tissue has normal gray level appearance but limited streaking is visible; 1, if there is no significant difference in image quality between FBP and imar reconstructions, with streaking artifact degrading tissue signal uniformity. Quantitative method was performed by measuring CT number of subcutaneous fat, muscle and bone, by placing a region of interest (ROI) at the same slice and the same location. Measurements were made at hardware level slices and away from the hardware. Same measurements were made for the FBP and the imar reconstructed images then compared to the values measured at the preoperative images Phantom Information and Scanning Parameter Figure 8-1 is a custom-designed arthroplasty low contrast phantom manufactured by CIRS (Computerized Imaging Reference Systems, Inc, Norfolk, Va) and composed of 109

131 body phantom with two 10-cm diameter holes. The composition of the body material used muscle formula based on the ICRU 44 and ICRU 46 with 40 to 50 HU ( ). The second part of the phantom is the arthroplasty insert that contains the metal implant (Figure 8-2). Arthroplasty insert is composed of two sections with two different background materials, namely trabecular bone with 120 HU and soft tissue with 40 HU. Each of the two sections contains 4 contrast targets, two 10-cm, one 15-cm and one 20- cm with 20, 25, 30 and 50 HU within the trabecular background section respectively; for the soft tissue section, 20, 20, 25 and 30 HU respectively. The third part of the phantom is the bone insert (Figure 8-3). Bone insert is composed of trabecular bone, with the background section containing same size, HU and position contrast targets as the metal implant section does. The other section of the bone insert is composed of soft tissue background with bone stem, and contains low contrast target similar in size, HU and position as those in the soft tissue section of the metal implant insert. A dual-source CT scanner (Definition-Flash; Siemens Healthcare, Germany) with single tube source output was used to scan the phantom in single tube mode. Scanning parameters were: 140 kvp, 300 effective mas (100% dose level), 0.6 mm collimation, 2 mm slice reconstruction thickness. The raw data were reconstructed using the standard FBP with B30S kernel and imar with I30f kernel. All reconstructions were performed using the same size field of view and the same table position. The imar images reconstruction was done on an offline workstation. 110

132 A B C D Figure 8-1: Phantom (CIRS, Computerized Imaging Reference Systems). (A) Top view of the phantom with two 100-mm diameter holes for the shoulder inserts. (B) Side view of the phantom showing with standard patient size dimension of 300-mm width and 100- mm height to cover. (C) Body phantom with two bone and two metal implants inserts. (D) Phantom setup for unilateral metal implant test scan with one bone insert and one metal implant insert. 111

133 The phantom was scanned in three steps. First, the phantom was scanned with both bone inserts in place to establish a base line for comparison (preoperative scan). In step two, one of the two bone inserts (left insert) was replaced with a metal implant insert (unilateral). In step three, the phantom was scanned with both metal implant inserts (bilateral) to establish the most challenging artifact condition. At the time of the study, the reconstruction time for imar on the off-line station was around 25 minutes per study. imar was then installed on the scanner and the reconstruction time was reduced to less than 30 seconds per study. A B C D E Figure 8-2: Metal implant insert (A) Top view of insert with 45-mm diameter Cobalt Chrome Sphere. (B) Side view of the insert showing Cobalt Chrome Sphere with titanium rod attached to it and surrounded by cortical bone embedded in soft tissue material. (C) Side v view showing the position of contrast targets in both sections of the insert. (D) Top view of the soft tissue section. (E) Top view of the trabecular bone section. 112

134 Same-size ROIs at the same location and the same slice were placed to measure bone and muscle CT number and noise at hardware level slices, away from the hardware. Measurements were made on the preoperative scan, postoperative with FBP and postoperative with imar. Same measurements were made for both unilateral and bilateral phantom. A B Figure 8-3: Bone insert (A) Top view of insert showing low-contrast targets. (B) Side view of the insert upper section with trabecular background and low-contrast targets and lower section with trabecular bone stem C surrounded by cortical bone and low-contrast targets impeded in the background s soft tissue material. (C) Top view of the trabecular bone section. 113

135 8.3.3 Iterative Metal Artifact Reduction (imar) Traditional metal artifact reduction (MAR) uses interpolation ( sonogram inpainting ) to replace the missing data due to metal shadow ( ). This process improves image quality, especially by reducing the streaks artifacts; however, since it cannot recover all of the missing data, it may introduce new artifacts tangentially to high contrast objects, and also blur the edges by interpolation between neighboring data sets. imar algorithm uses normalized sonogram data for interpolation, therefore the tangential streak artifacts introduced by interpolation of high contrast object or metal edge is reduced. imar also uses frequency split technique to restore the high frequency components (object edges) of original images. Both processes (normalization and frequency split) go through several iterations until a certain preset condition is met. To reduce the number of iterations, imar starts with images that have been filtered backprojected. 8.4 Data Analysis Patients Scans Analysis and Statistic Visual Evaluation Visual evaluations of all clinical studies were performed. For slices at the hardware level (figure 8-4), score 2 was considered acceptable. Score of 1 was considered failure of the imar reconstruction algorithm in correcting the image properly, resulting in significant non-uniformity within soft tissue in regions near by the implant. For slices away from the hardware, a score of 3 was considered acceptable, meaning that no streaking or non-uniformity was introduced to slices away from the 114

136 hardware as a result of applying imar reconstruction algorithm. A score 2 was considered failure of the imar reconstruction algorithm by introducing streaking or nonuniformity to the images away from the hardware, where there was no artifact present before reconstructing the images using imar. A B 115

137 C Figure 8-4: Example of CT image of shoulder implant (A) Left, shoulder CT image for patient with shoulder implant using FBP; Right, same image after being imar processed. (B) Image of patient with bilateral shoulder implants (extreme case of artifact). Left, shoulder CT image using FBP, Right, same image after being imar reconstructed. (C) Image away from hardware with FBP (left), and with imar reconstruction (right). Quantitative Evaluation For patient data, measurments of muscle, subcutaneous fat and bone CT numbers were performed. Great attention was paid to the ROI positions to ensure that no adjacent type of tissue was included with the type under investigation. The size of ROI was determined to ensure ROI is fully contained within the tissue being measured. Also, the slices and positions of all ROIs were selected for preoperative FBP, postoperative FBP, and post-operative imar simulatenosly to ensure that it is in the same anatomic location on the preoperative and postoperative scans (figure 8-5). Measurments were made at the hardware level slice, where streaking is most prominent, to analyze the software capability of recovering CT number. Another set of measurments were made at a slice 116

138 away from the implant, where no metal artifact is present, to check for any change in the CT number due to software correction. Also Image histogram will be utilized to compare between images pre and post imar reconstruction. The diffrence between the mean CT numbers of tissue in the preoperative image and the mean CT number of the same tissue in both postoperative reconstructions (FBP and imar) were calculated. To test the imar cabability of recovering CT, a two tailed paired t-test with significance level of 0.05 was performed. T-test was performed on both data from slice at the level of hardware and data from slice away from the hardware. Also image histograms will be utilized to compare between images pre and post imar. A B C 117

139 Figure 8-5: Example muscle tissue CT number measurement (A) Preoperative Shoulder CT image FBP reconstructed, (B) Post-operative shoulder CT image FBP reconstructed, (C) Same image B reconstructed with imar Phantom Scans Analysis and Statistic For phantom data, muscle and bone tissue, CT number and noise were measured and tabulated in three categories. First are CT numbers and noise values for phantom scans with bone inserts only. This category represented the baseline measurement or preoperative condition. The second category is CT numbers and noise values for unilateral implant phantom (only one shoulder has the implant). This category represents post-operative scan with unilateral shoulder replacement. The third category is CT numbers and noise values for bilateral (both shoulders have metal implants) implant phantom. This category represents the most challenging scenario in terms of imaging patients with metallic implants, as the beam has to penetrate two different implants, creating severe metal artifacts and photon starvation. A paired, two-tailed T-test with 0.05 significance was performed to test whether the difference between the preoperative CT numbers and noise and the postoperative CT numbers and noise is significant. T-test was performed on both data collected at hardware level and away from the hardware level for both unilateral and bilateral phantoms. 118

140 A B C 119

141 D E Figure 8-6: Example arthroplasty phantom scan (A) Preoperative phantom scan without any metal implants. (B) Post-operative phantom scan with unilateral implant, FBP reconstructed. (C) Post-operative phantom scan with unilateral implant, imar reconstructed. (D) Post-operative phantom scan with bilateral implant, FBP reconstructed. (E) Post-operative phantom scan with bilateral implant, imar reconstructed. 8.5 Results Patients Data analysis results Visual Evaluation For patients scans at the hardware level, imar showed consistent improvement in image uniformity in comparison to FBP. Significant reduction in streaking artifact was noted in all 30 scans. All FBP reconstructed scans received a score of 1, and showed 120