Laser-induced Fluorescence (LIF) Based Optical Fiber Probe for Biomedical Application

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1 Laser-induced Fluorescence (LIF) Based Optical Fiber Probe for Biomedical Application Jagdish P. Singh, Sunil K. Khijwania, Chan Kyu Kim, Fang-Yu Yueh Shane C. Burgess, Diagnostic Instrumentation and Analysis Laboratory (DIAL) Department of Basics Sciences, College of Veterinary Sciences Mississippi State University, 205 Research Boulevard, Starkville MS 39759, USA Phone: , Fax: Department of Physics, Indian Institute of Technology-Guwahati North Guwahati, , India ABSTRACT Laser induced fluorescence (LIF) spectroscopy has emerged as a potential tool for the cancer diagnosis. A comprehensive analytical study of a compact optical fiber LIF based sensor for in-vitro point monitoring of tissue auto-fluorescence as a non-invasive tool for cancer diagnosis is presented. The effect of two critically important parameters from the sensor designing aspects, namely, the excitation-collection geometry and the excitation wavelength over the tissue auto-fluorescence response and malignancy resolution is investigated. An attempt has been made to determine an optimum sensing configuration to develop a diagnostics procedure to enhance small but consistent spectral difference between the normal and malignant tissue from various parts of animal body to greatly improve the accuracy of the auto-fluorescence cancer diagnosis. Keywords: Optical fiber, Laser-induced fluorescent spectroscopy, Auto-fluorescence, cancer diagnosis. 1. INTRODUCTION Optical spectroscopy has been widely used to acquire fundamental knowledge about physical, chemical, and biological processes that occur in biomaterials 1-3. In particular, laser-induced auto-fluorescence, which was first observed by Stokes 4 and later was recognized as a potential diagnostic tool by Stubel 5, has been extensively studied over the past 20 years and significantly emerged as a promising technology for biomedical diagnostics. This is a process whereby molecules/atoms are excited to higher electronic energy state via laser absorption and subsequently fluoresce at emission wavelengths, which are independent and longer (red-shifted) than that of the excitation wavelength. It has been applied for the in vitro and in vivo analysis 6,7 of many different types of samples, ranging from individual biochemical species (e.g. NADH, tryptophan) to human and animal tissues as the associated signal is intense with an excellent signal to noise ratio. This leads to a greater achievable sensitivity 8, 9. This technique has the capability to quickly, non-invasively, and quantitatively probe the biochemical and morphological changes that occur as the tissue transforms from normal to malignant. The altered tissue architecture and bio-characteristics of native fluorophores associated with malignant transformations is reflected in the spectral characteristics of the measured fluorescence 10. Thus in recent years, laser induced fluorescence has emerged as a promising tool 6-9 and significant progress has been made in tissue fluorescence spectroscopy for cancer detection However, an accurate, sensitive and rapid method for the diagnosis of a normal and malignant tissue is quit challenging. Major initial studies were focused on the measurement of continuous wave (CW) fluorescence emission spectra of tissue when illuminated at a single excitation wavelength Differences in the emission spectra of normal and diseased tissue were then examined to attempt optical diagnosis of the disease process. These spectral differences were attributed to the variation in tissue structure and fluorescent species content. However the spectral contrast for normal and malignant tissue, which is extremely critical and a major issue for the successful diagnosis, remained extremely weak in these studies. For example, Demos et al 15 in their approach could obtain a maximum fluorescence intensity contrast of to 5. Owing to the fact that the fluorescence signal from a photo-sensitizer is generally higher in intensity than that from auto-fluorescence, Nadeau et al 16 had administered aminolaevulinic acid (ALA) as a photo-sensitizer drug in order to achieve high signal contrast neglecting its own disadvantages and dangerous side effects. They could obtain a fluorescence contrast in the optical spectrum of malignant and normal tissue of not more than 5. Further, all these studies have generally incorporated bulky, expensive, complex equipments, for example pulsed nitrogen or dye lasers and time gated intensified CCD or diode array detectors. Another critically important issue related to the tissue fluorescence diagnosis is the fact that it does not depend on the concentration and

2 distribution of fluorophore (s) present in the tissue only. The illumination and collection geometry of the excitation and the emitted light also play a crucial role in the tissue fluorescence measurement. Further, most tissues contain multiple fluorophore as a constituting bio-species 17. The presence of all these integral fluorophores influences the composite tissue spectrum individually and more or less apparently, depending on how intensely the excitation radiation excites these fluorescent species. Hence a single wavelength excitation for the optical tissue diagnosis has its own limitation in terms of fluorescence analysis and optical identification for disease forecast. Multiple excitation wavelengths may induce different types of tissue fluorophore to fluoresce, resulting in different spectral profiles/intensities of tissue spectra with better discrimination abilities between cancerous and non-cancerous tissue. This leads the need for a multiple wavelength excitation to realize a finer spectral resolution and differentiation between tissue types for early cancer diagnosis. This paper presents a rigorously comprehensive study of a laser-induced fluorescence (LIF) based optical fiber sensor to discriminate normal and malignant tissue at premature stage. The sensor is optimized in order to enhance small but consistent spectral difference between the normal and malignant tissue to greatly improve the accuracy of cancer diagnosis. Further, the effect of the excitation and collection configuration on the diagnosis response was investigated. In a most useful and rigorous bio-diagnostic tool, the excitation and emission geometry that yields fluorescence measurements should not depend on geometric dependencie 18. Sensors comprising two different excitation-collection configurations were designed fulfilling this geometric criterion where the emitted light from the tissue is collected only from that surface, which is directly illuminated by the excitation light. Two separate fibers, one for excitation and one for collection were used in first configuration, whereas a bifurcated optical fiber probe with one excitation fiber and six surrounding collection fibers were used for the second configuration. Fluorescence was induced by a nano-second pulsed laser (frequency triple Nd:YAG, operating at 355 nm) in both the cases. Tissues were taken from various parts of the animal (dog) body. The emitted tissue fluorescence was investigated in a 360 to 700 nm range. Next, the effect of different laser excitation on the tissue response was investigated. A wide spectrum of excitation wavelength, as low as 355 nm and as high as 532 nm, was used to study the spectroscopic properties of tissues and to determine optimal excitation wavelength for distinguishing malignant from normal tissue. The emitted tissue fluorescence in this case was investigated in a 350 to 850 nm range. A comparative analysis is presented and an optimum sensing configuration in terms of the sensing geometry and other influential experimental parameters was determined. In addition, a remarkably high fluorescence contrast of malignant versus normal tissue was achieved. Finally, the results of our approach were compared with histopathology results and indicated excellent agreement in the classification of normal and malignant tissue. 2. EXPERIMENTS 2.1 Sample preparation A number of tissue samples (biopsy material, 75 mm 3 ) including normal and malignant (Haemangiosarcoma) used in the present work were collected from different parts of the animal body. These include kidney, spleen, and liver. The samples were placed in a drop of OCT embedding medium (BDH) on a square of Whitman filter paper (5 cm 2 ) and cooled in nitrogen vapor before immersion in liquid nitrogen. Sections (16µm) were cut using a Cryocut cryostat (Reichert-Jung), placed onto plain glass slides and then air-dried to fix it. The thickness of all the tissue samples was 16 µm. No chemical was added to the samples and they were not frozen prior to taking the measurements. They were just kept in the refrigerator at temperature C. 2.2 Sensor Configuration To develop a prototype LIF system for measuring the optical characteristics of the tissue sample, two excitationcollection geometries for diagnostic capability comparison were employed in the first part of the study. This was inspired from the fact that the recorded tissue fluorescence spectrum depends on the geometry used for the illumination and detection of the fluorescence volume. This geometrical dependency of measurement is critical for diagnostic purposes especially in understanding single point monitoring. In both the sensor configurations, fluorescence was induced by a monochromatic excitation light source, which was a frequency tripled 355 nm pulsed Nd:YAG laser (Continuum, model # NY 82S-10) with pulsed width 4-5 nsec, 10 Hz repetition rate and 570 µj/pulse maximum output power. To attenuate the output laser power, laser was operated at increased Q-switched time-delay and appropriate quartz neutral density filter were introduced. The laser light was blocked using a shutter, except during the short intervals required for acquiring spectra. This is important since prolonged exposure of tissue to light results in photo bleaching of the fluorescence signal and accidental PDT. The output laser beam, with spot size of ~ 3 mm was reflected by the dichroic mirror (DM 1, CVI) onto a lens (UV grade fused silica, CVI) that focuses it onto the proximal aperture of the optical fiber probe. Another dichroic mirror (DM 2, CVI, high transmittance at 355 nm and high reflectivity at 532 nm) was further inserted to attenuate 532 nm laser radiation. 2

3 A schematic diagram of the system components for first sensor configuration is shown in the Figure 1 (a). In this case, laser reflected from two dichroic mirrors was coupled to a single 1 mm core diameter UV grade fused silica optical fiber, which is used to excite a small volume of the tissue. Power at the distal end of the optical fiber was 165 µj/pulse. The guided light through this fiber was focused onto the sample using suitable launching/collimating optics. This optics is a combination of two UV-grade fused silica Plano-convex lenses with focal length f 1 equal to ~ DM1 Laser A Spectrometer DM 2 Optical fiber ND Filter L Cut-off filter Collection Optics (a) xyz-translation stage Excitation Optical fiber Receiving Optical fiber f 1 f 2 θ f 2 f 1 Sample on xyztranslator stepper Excitation Optics Laser A DM 1 Spectrometer xyz-translation stage L DM µm Optical 200 µm Optical Fiber Cut-off filter Loss insertion mechanism In-line filter holder (b) Y-Probe z d x y Sample on xyz-translator stepper Figure 1: The schematic representation of the optical fiber sensor comprising separate optical fiber for excitation and collection (a), and sensor comprising Y-reflection probe (b). 5 cm (having numerical aperture equal to 2, matching with that of the fiber) and f 2 equal to 7.62 cm, with ~ 5 cm spatial separation between them. The spot size area of the beam at its focal plan (i. e. on sample) was measured to be ~ 6.95 mm 2. The optical intensity on the sample was adjusted to approximately 8 mj/pulse using appropriate neutral density filters. The tissue sample was mounted on a XYZ-micro-translator sample-mount for an easy adjustment and optimization of the distance between tissue sample and optical fiber probe. The emitted fluorescence signal was then received from two locations within the fluorescence volume through another identical optical fiber using a collection optics, which was similar to the launching/collimating optics. This signal was collected at proper angular and translational position with respect to the exciting fiber and the sample orientation. This is critically important in terms of enhancing the coupling of the fluorescence signal back into the fiber, and to optimize the signal-to-noise ratio. To minimize the detection of the scattered excitation light, which is much stronger than the weaker emitted LIF signal, appropriate optical component needed to be employed in front of the detection system. Hence, the collected LIF signal was transmitted through an online filter module to an auxiliary fiber (1 mm core dia, UV grade fused silica) prior to feeding it to the spectrometer. As shown in figure, this online-filter-module was having the capability to couple the signal from one fiber to another with an in-built collimating and focusing lens and SMA fiber connector provisions. A 370 nm long pass optical cut-off filter was mounted on this filter module for this purpose. The signal was then fed to an Ocean Optic spectrometer (USB-200) and the fluorescence spectral response data were acquired using personal computer and standard software. In the second configuration, an Ocean Optics Reflection/Backscattering Y-shaped probe (R200-REF) was incorporated. This probe consists total seven optical fibers, each having 200 µm core diameters and 2 numerical aperture, with one launching fiber and six surrounding collecting fibers. In order to reduce the optical irradiation onto the sample and prevent it from photo bleaching, the filtered light from the excitation source was first coupled to a single 200 µm UV grade fused silica fiber and then couple to the excitation arm of the Y-reflection probe through loss insertion device as shown in Fig. 1 (b). This was also needed in order to avoid any damage (burning) to the excitation fiber from the high-energy laser radiation. The distal aperture of the later delivers the excitation radiation to illuminate tissue at normal incidence, thereby inducing the auto-fluorescence. The laser energy at this end was adjusted to ~ 09 µj/pulse. The diverging output beam from the fiber is used to provide nearly uniform illumination of the sample. Unlike the previous case, here the tissue fluorescence signal in the backward direction was simultaneously collected through a ring of six optical fibers around the single illumination channel. The collected LIF signal was transmitted through the same online filter module to an auxiliary fiber (600 µm core dia, UV grade fused silica) prior to feeding it to the spectrometer. Further, the use of multiple excitation wavelengths is predicted to result in different spectral profiles/intensities of tissue spectra. To investigate it, in addition to the frequency tripled 355 nm pulsed Nd:YAG laser, fluorescence was induced by two other laser wavelengths for diagnostic capability comparison. The excitation-collection geometrical configuration depicted in Fig 1(b) was used for this purpose (reason is explained in the next section). In one such 3

4 case, fluorescence was excited by a continuous wave laser diode operating at 410 nm, with maximum output power at 35 mw. The experimental set-up remained the same except for the set-up used to couple light from the laser diode to the first optical fiber. A proper collimating and focusing optics was used for the coupling of the laser light to this fiber, without the use of dichroic mirrors. The laser energy at the distal end of the Y-fiber probe in this case was adjusted to ~ 0.3 mw. Finally, fluorescence was excited by a frequency doubled 532 nm continuous wave Nd:YAG laser, with maximum output power at 330 mw. The experimental set-up remains the same except that the attenuated laser energy through proper neutral density filter was directly coupled to the launching arm of the Y- shaped optical fiber probe. The laser energy at the distal end of the fiber was adjusted to ~ 1.6 mw for this experiment. For each excitation wavelength, a different optical cut-off filter was mounted on the online-filtermodule in the collection arm to properly filtrate the scattered background signal. All measurements were performed at room temperature. Detection of the fluorescence signal from the tissue was performed almost instantaneously. The optical fiber probe was precisely kept at the same orientation with respect to the tissue sample to correct for the influence of variations in probe positioning in all the sets of experiments comprising each configuration. This enables comparison of the relative intensities between different tissue samples. Each sample emission was run five times for reproducibility. Prior to the examination of each tissue sample, background spectrum was acquired without the tissue, and this spectrum was subtracted from subsequent fluorescence spectra. This allowed correction for source-intensity variations and any ambient light that may enter the system, which could otherwise distort the fluorescence measurements. 3. RESULTS AND DISCUSSIONS The experiments presented here were carried out with three objectives: (1) to investigate the effect of sensor geometry on the tissue spectral characteristics, (2) to investigate the effect the spectral characteristics of the tissue fluorescence emission and to evaluate how a fluorescence spectrum differs depending on at what excitation wavelength the measurement is taken, (3) to utilize these aspects for the cancer diagnostic application & developing a clinical device, optimized in terms of system configuration and various experimental parameters of influence. 3.1 Effect of excitation geometry: Two excitation-collection geometries for the sensor were employed in this study. First geometry comprised two individual 1 mm core fibers for fluorescence excitation and collection (hence for worth mentioned as Geometry I) as shown in Fig. 1 (a). In the process of critically improving the sensor performance, this configuration was characterized for test measurement and optimization against a standard fluorescent agent as a sample. The angular and translational orientation of the excitation and collection fiber with respect to the sample was observed to be very critical and needed to be optimized. An optimum signal was obtained at 82 0 relative angular orientation (θ) of miniaturized optics, attached to the respective fibers; and the sample at their focal plan. However, the second geometry comprised Y-reflection optical fiber probe (hence for worth mentioned as Geometry II) as shown in Fig. 1 (b). The distance between the excitation spot at the fiber probe and the sample (d) was observed to be very critical and needed to be optimized. Hence, experiments were carried out against the same standard sample to evaluate how a fluorescence spectrum differs depending on what distance d the measurement is done in this case. The peak sample-probe separation (d ) (mm) Figure 2: Effect of the variation of fiber probe to sample separation (d) on the sensor response. Peak Intensity fluorescence intensity versus the separation is plotted in Fig. 2. As can be observed, optimum fluorescence intensity was observed at d equal to1.75 mm. The theoretically calculated value of d came out to be 1.51 mm for the given fiber parameters, which showed a good degree of agreement. Once optimizing these parameters, experiments using 355 nm excitation wavelengths were then extended to normal and cancerous tissue samples in order to realize 4

5 successful cancer diagnosis with improved signal resolution. All the data with Geometry I were recorded with a relative angular orientation of 82 0, and with the front surface of the illumination fiber positioned at ~1.75 mm above the sample with Geometry II. A total of 24 tissue samples were used for the fluorescence study. Clinical and histological examination of the samples showed that there were 12 normal specimens, and rest 12 with a stage tumor. The tissue samples were exposed to the signal for an optimum time interval in order to record the spectral ized Intens ized Intens Wevelength (nm) (a) (b) ized Intens ized Intensity (a) (b) 0.1 Wevelength (nm) 0.9 (c) Wevelength (nm) Figure 3: Typical fluorescence emission spectrum from (a) spleen, (b) kidney, and (c) liver obtained with the Sensor Geometry I, comprising two identical fibers for excitation and collection each. ized Intensit ized Intensity (c) Figure 4: Typical fluorescence emission spectrum from (a) spleen, (b) kidney, and (c) liver obtained with the Sensor Geometry II, comprising Y-reflection optical fiber probe. signature. The fluorescence of samples was measured at 355 nm excitation wavelength and the emission wavelengths with the greatest discrepancy between normal and tumor tissue was determined. Care was taken to eliminate the second harmonic occurring at 710 nm and the leakage of the excitation wavelength at 355 nm. Typical auto-fluorescent spectra obtained from normal and malignant tissues, suspended on a glass micro-slide are shown in Fig. 3 and 4 for Geometry I, and Geometry II respectively in the nm region. Spleen spectra are shown in (a), kidney spectra in (b) & liver spectra in (c). All the emission profiles were obtained from normal and cancer tissue under identical illuminating conditions for a given sensor geometry. The absolute intensity in the case of sensor Geometry II was observed to be significantly greater than that for Geometry I, even though the power at the distal end of the probe in the former case was ~ 10 times lower as compared to the power in the later case. Thus the sensor comprising Geometry II was found to be highly sensitive and more advantageous in terms of the diagnostic resolution of disease. The measured spectra were corrected for source-intensity variations and spectral 5

6 response of the system. These spectral data were also normalized to the tissue fluorescence peak intensity at ~ 485 nm. For all the tissue samples including normal as well as cancer, three emission maxima were observed at ~ 420, ~ 440 and ~ 485 nm respectively with the Geometry I. This reflected the similar spectral contents for normal and diseased samples. Peak at 485 nm constitutes the prominent emission maxima, whereas peak at 440 nm constitutes major secondary emission maxima, and at 420 nm constitutes minor secondary emission maxima. However, in the case of the sensor Geometry II, only constituting prominent emission maxima at ~ 485 nm and major secondary emission maxima at ~ 440 nm could be observed for normal and cancerous tissues. The fluorescence peak positions were not significantly altered for tumors in any case. Nevertheless, the spectral shape as reflected from experimental results was not identical for the tissues taken from three parts of the body due to the difference in the intensities at the characteristic emission wavelengths. This reflects the variation in the constituting bio-chemical concentration in the samples from different parts of the body. Further, as indicated by these normalized spectra, the line shape for the normal and malignant samples for a given organ remains almost the same irrespective to the employed sensor Geometry. A close evaluation of these emission spectra indicates a distinctive increase in the fluorescence intensity for normal compared to the malignant tissue in the 360 to 700 nm spectral region. The prominent features that are common among the spectral characteristics from the normal and tumor tissues recorded from both the sensor geometries can be concluded as follow: 1. The prominent emission maxima of the normal spectra are observed at about 485 nm having a broad width, which is virtually the same in all cases. 2. Major Secondary emission peak, also having a broad width, is observed at ~ 440 nm to all normal tissues. 3. The same spectral contents (emission peaks) are observed in the cancerous tissue spectra with greatly reduced intensity. 4. The most salient feature, as can be observed, is that a sufficient fluorescence contrast of malignant versus normal tissue was obtained. The main fluorescence components centered at ~ 485 and ~ 440 nm and dominating the emission fluorescent spectra of the normal tissues, cease to contribute and disappeared in the fluorescence signature of the cancerous tissue. This led to a dramatic reduction in the fluorescence intensity for all the cancerous tissues. 5. The prominent emission intensity peaks for the normal and cancer tissues are located at the same wavelengths. No blue shift from the normal to the cancer spectra was observed, as reported in the literature. Further, the ratios of the integrated intensities of the emission from normal over the intensity from cancerous tissue for both the sensor geometries and for all the samples are given in the Table 1. These values are plotted in Fig. 5 for 440 nm (a) and 485 nm (b) emission peaks for comparison. The following observations can be made from these results. First, for a given sensor geometry the fluorescence intensity ratio of normal over the cancerous sample is Table 1: Ratio of the peak intensity for normal to cancer tissue samples at the observed characteristic emission maxima for the two sensor geometries. I normal / I cancer Sensor Geometry I II Geometry II Geometry I Intensity Ratio (I normal /I cancer ) for Tissue emission maxima at sample ~ 420 nm ~ 440 nm ~ 485 nm Spleen Kidney Liver Spleen Kidney Liver (a (b) I normal /I cancer Geometry II Geometry I 0 spleen kidney liver Figure 5: A comparison of the intensity ratio for the normal to the cancerous tissue for both the sensor configurations at (a) 440 nm emission peak, and (b) 485 nm emission peak. 0 spleen kidney liver 6

7 found to be maximum at ~ 485 nm emission for all the tissue samples except for few exceptions. Second, as can be observed from Fig. 5, in comparison, a better cancer identification and resolution was realized through sensor Geometry II with a far better normal to cancer spectral contrast in all the cases. Thus Geometry II will be useful in designing medical application oriented miniaturized optical fiber sensing bio-probe. 3.2 Effect of excitation wavelength: To study this, two additional excitation wavelengths, 410 nm and 532 nm were used for the auto-fluorescence measurement experiments. Owing to the finding of previous study, Geometry II was employed for all these sets of experiments. All the data in each case were recorded with ~1.75 mm distal separation between the front surface of ized Intensity ous (a) ized Intensity ous (b) ized Intensity ous (c) Figure 6: A comparison of typical fluorescence emission spectrum obtained at 355 nm, 410 nm and 532 nm laser excitation (a) kidney, (b) liver, and (c) spleen. The dark line shows results obtained at 355 nm excitation, thin gray line shows results obtained at 410 nm excitation, and thick gray line shows results obtained at 532 nm excitation. the illumination fiber and the tissue sample, as this was observed the optimum distance for these excitation wavelengths also. Typical auto-fluorescent spectra obtained from the normal and malignant tissues using the three excitation wavelengths are shown in Fig. 6 for nm region. The dark line shows results obtained at 355 nm excitation, thin gray line shows results obtained at 410 nm excitation, and thick gray line shows results obtained at 532 nm excitation. Kidney spectra is shown in (a), liver spectra in (b) & spleen spectra in (c). All the emission profiles were obtained from normal and cancer tissues under identical geometric and physical conditions. All the measured spectra were again corrected for source-intensity variations and normalized to the prominent fluorescence emission peak intensity. As can be observed, in the case of 532 nm excitation, two emission maxima were observed for normal and diseased tissue samples. Unlike the 355 nm case, this time they were positioned at ~ 570 nm and ~ 632 nm. 570 nm constituted the prominent primary emission maxima and ~ 632 nm constituted the minor secondary emission maxima. However, in the case of 410 nm excitation, only one constituting prominent emission maxima could be observed for normal and cancerous tissue. This maxima was centered at ~ 492 nm. These results can be concluded and interpreted as follow: 1. The spectral profiles and prominent emission peak locations for the normal and cancerous tissues of a given body organ are located at the same wavelength for a given excitation wavelength. This reflected in similar spectral composition for normal and diseased samples. 7

8 2. The prominent emission maxima, observed at a given excitation wavelength, has a broad width whether it is for the normal tissue emission spectra or for the malignant tissue emission spectra. 3. These spectral profiles & emission peaks do not remain identical, and differ under different wavelength excitation. Thus, a variation in the excitation wavelength resulted in a different spectral signature from the same tissue sample. This is due to the difference in the characteristic emission wavelengths, corresponding to the different constituting bio-species (fluorophores) that got excited with each excitation wavelength. 4. In the emission spectra, the fluorescence component present at wavelength < 550 nm when λ ex was 532 nm ceased to contribute to the emission and disappeared when the excitation wavelength was 410 nm. 5. The spectral shape was not exactly identical for the tissues taken from three parts of the body at a given excitation wavelength. This is attributed to the difference in the intensities at the characteristic emission wavelengths and reflects the presence of numerous constituting bio-chemicals in a given tissue sample and their concentration variation in the samples from different parts of the body. 6. Finally, a sufficient fluorescence intensity contrast of malignant versus normal tissue was obtained. The main fluorescence components, centered at ~ 485, ~ 492 and ~ 570 nm respectively for the three excitation wavelengths dominated the emission fluorescent spectra of the normal tissues. However, they ceased to contribute and virtually disappeared in the fluorescence signature of the cancerous tissue. This led to a dramatic reduction in the fluorescence intensity for all the cancerous tissues as compared to the normal tissues for a given organ at all excitations. Next, the ratios of the integrated intensities of the peak fluorescence emission from normal to that from cancerous tissue are again calculated for all the excitation wavelengths and tissue samples used in the experiment and are given in the Table 2. These ratios corresponds to the 485 nm peak in the case of 355 nm excitation, 492 nm peak in the case of 410 nm excitation and finally 570 nm in the case of 532 nm laser excitation. Further, these values are plotted in Fig. 7 for a better comparison. The following observations can be made from these results. First, the fluorescence intensity ratio of normal over the cancerous sample is observed to be maximum for liver tissue samples at all the excitation wavelengths. Second, the 410 nm excitation wave- length resulted in the minimum achieved spectral Table 2: Ratio of the peak intensity for the normal to cancer tissue samples at the observed characteristic emission maxima corresponding to the different excitation wavelengths. λ ex (nm) Tissue sample Intensity Ratio (I normal /I cancer ) for primary emission peak at 485 nm 492 nm 570 nm Spleen Kidney Liver Spleen Kidney Liver Spleen Kidney Liver Inormal / I cancer nm 410 nm 532nm spleen kidney liver Figure 7: A comparison of the intensity ratio for the normal to the cancerous tissue for the emission peak at ~ 485, ~492 and ~570 nm, corresponding to the excitation wavelength of 355, 410 and 532 nm respectively, for the tissue samples from different body organs. contrast and disease resolution except for the spleen tissues. Third and most important, though excitation at 532 nm resulted in a far better malignancy resolution as compared to 410 nm, it was the 355 nm excitation wavelength that yielded the greatest spectral discrepancy between normal and malignant tissue sample at 485 nm emission peak. A maximum intensity ratio over 22 was achieved in this case at 485 nm maxima, which is far better than what have been reported in the literature so far. This shows that 485 nm emission wavelength carries greatest spectral discrepancy and should be ideal for medical diagnosis. Thus, the advantage of the present research, in comparison, is the realization of a sensor system capable of better cancer identification and resolution with much ease and without any tissue alteration. Hence, the proposed senor with sensor Geometry II, 355 nm excitation wavelength and 485 nm observation (emission) wavelength should be the ideal to maximize the medical ability of cancer discrimination and diagnosis. The high spectral contrast achieved with this operating and observation wavelength combination and sensor configuration would result in optical resolution of cancer in its conceiving stage and will be tremendously useful in medical applications. Fluorescence spectroscopy of tissue depends on the concentration and distribution of fluorophore (s) present in the tissue. The results, shown in Fig. 3, 4 & 6 were further analyzed on the basis of those important bio-molecules, 8

9 which exhibit endogenous fluorescence upon laser excitation The main active fluorophores in the UV to visible (from 250-nm to 600-nm) spectral region excitation are tryptophan, collagen, elastin, NADH, flavins and prophyrins 15, 23. These are the fluorophores that are speculated to play a role in transformations that occur in the cancer development process. In particular, collagen, elastin and NADH have broad absorption spectral range starting from 350 to 410 nm and almost no absorption for λ ex 450 nm 23. Flavins, another important bio-molecule and natural fluorophores present within intact tissue cells, have a wide spectral absorption band, ranging from 370 to 550 nm with main absorption peak centered at ~ 410 nm and ~510 nm. Thus, these were the main fluorophores that were optically induced to fluoresce when excited by 355 nm, 410 nm and 532 nm laser radiation. With excitation laser in this absorption region, flavins fluoresces near 560 nm region 23-25, collagen fluoresces in 420±25 nm region, elastin fluoresces in 430±30 nm region 23, 25, 26 and NADH molecules fluoresce in a band with a maximum at ~ 480 nm 26. Thus, the peak at ~ 420 nm, observed in the emission spectrum for 355 nm excitation with the Geometry I is due to the intrinsic fluorescence of collagen, which has emission maxima at this wavelength. This secondary peak could not be observed with Geometry II, probably due to the related experimental constraints in this case. Next, the main secondary peak at ~ 440 nm, observed in the emission spectrum for 355 nm excitation is due to the intrinsic fluorescence of elastin, which has emission spectra dominating at this wavelength. However, the primary maxima in the fluorescence emission spectra observed at 485/492 nm for 355 nm as well as 410 nm excitation is essentially due to the NADH, as this bio-molecule dominates optically in this fluorescing region. Further, as can be noticed from Fig. 6, instead of having one absorption maxima at ~ 410 nm, flavins fluorescence peak could not be observed with this excitation wavelength. However, the characteristic flavins fluorescence emission peak was observed as a prominent peak with 532 nm excitation. The secondary peaks at 632 nm in the tissue s spectral signature for this excitation wavelength could be attributed either to the porphyrins, which has emission maxima at 630 nm or to the self-absorption of hemoglobin from bands centered at ~ 540 nm 27. These peaks appear in the fluorescence spectra of normal as well as cancer tissues without any apparent shift. However, the relative amplitudes of the peaks are substantially different for normal/malignant tissue samples at a given excitation wavelength. This reduction in the fluorescence intensity for malignant tissues at the three excitation wavelengths is attributed to the physiological and biochemical transformation of the cells from the normal tissue. The experimental results firmly indicate that there is a significant reduction mainly in the elastin (440 nm), NADH (485 nm), and Flavins (570 nm) molecular density and the corresponding quantum yield with the malignancy transformation. The maximum achieved spectral contrast at 485 nm showed that it s the NADH concentration, which plays the key role in the cancer growth and gets substantially reduced with the disease transition. In addition, the realization of this maximum spectral contrast at 355 nm excitation further indicated the suitability of this wavelength for optimum NADH stimulation. Thus, these excitation/emission wavelengths with Geometry II are concluded to be the best for the cancer diagnosis. 4. CONCLUSIONS A comprehensive study of the influence of sensor geometry and different excitation wavelength on the tissue fluorescence characteristics as well as the diagnosis response is presented. Sensor comprising single illumination centered fiber and six ring fiber probe observed to enhance the sensitivity greatly with far better cancer identification and resolution capability. The spectral line shape/emission spectra did not depend to the sensor geometry. However, it did depend on the excitation wavelength. Sensor comprising 355 nm excitation wavelength was observed to enhance the sensitivity greatly with far better cancer identification and resolution capability. An intensity ratio for normal to malignant tissues of more than 22 was achieved in this case at 485 nm emission wavelength using sensor Geometry II as compared to the reported maximum around 5 to the best of author s knowledge. Thus, this operating sensor configuration was determined as the optimum combination to realize a greatest spectral discrepancy and disease resolution for biomedical application and observed to be the ideal for diagnostic analysis. This study also demonstrates that the auto-fluorescence spectroscopy can be improved to distinguish the malignant state. The results of this approach were compared with other results reported in the literature and indicated excellent agreement with better resolution capability. ACKNOWLEDGEMENT Authors would like to thanks Dr. Allen Wood, Director, Life science and Biotechnology Institute (LSBI), Mississippi State University for providing funding for this work. REFERENCES 1. R. R. Alfano, D. B. Tata, J. Cordero, P. Tomashefsky, F. W. 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