The EARL FDG-PET/CT Accreditation Programme & Guideline Developments: Results of more than 65 Successfully Accredited Sites and Future Perspectives

The EARL FDG-PET/CT Accreditation Programme & Guideline Developments: Results of more than 65 Successfully Accredited Sites and Future Perspectives

Disclosure statement Research support: Philips Healthcare & Roche

Biomarkers Biomarkers are physical entities or images of these entities that can be measured and used to indicate a biological process, disease process, or drug response A surrogate endpoint, or marker, is a laboratory measurement or physical sign used in therapeutic trials as a substitute for a clinically meaningful endpoint that is a direct measure of how a patient feels, functions, or survives, and is expected to predict the effect of the therapy Courtesy of Arturo Chiti

Molecular Imaging with (Q)PET (with CT and/or MR) Different radiopharmaceuticals to image different metabolic pathways Diagnosis and staging Restaging Biological Characterization Response Evaluation Therapy Courtesy of Arturo Chiti

Standardised Uptake Value SUV TBW = ct[ kbq/ ml] Dose[ MBq]/ weight[ kg] SUV is activity concentration ratio Weight is sometimes replaced by BSA, LBM, BMI

Use of SUV in response assessment studies Absolute SUV: -Patient eligibility -Patient stratification -Lesion selection (PERCIST) -Residual SUV Relative of % SUV changes -% change of the same lesions (EORTC) -% change of the (5) hottest lesions per scan + SUV=0.9 (PERCIST) For all applications absolute SUV and SUV changes are used

Entire chain of process determines quantitative result of an imaging biomaker Picture taken from QIBA FDG PET/CT profile (draft)

Basic principle is same for most (PET based) imaging biomarkers (1) (2) (3) (4) Standardisation/harmonization implies: 1. Guidelines or imaging procedures to address user/observer related factors (uptake time, patient preparation, data analysis/intepretation) 2. Requirements for image data acquisition (activity, scan acquisition parameters, reconstruction settings) 3. Rules for image/data analysis 4. Criteria for data (e.g. response) intepretation

PET imaging / SUV uncertainties Technical factors Relative calibration between PET scanner and dose calibrator (10%) Residual activity in syringe (5%) Incorrect synchronisation of clocks (10%) Injection vs calibration time (10%) Quality of administration (50%) Physics related factors Scan acquisition parameters (15%) Image reconstruction parameters (30%) Use of contrast agents (15%) ROI (50%) Biological factors Uptake period (15%) Patient motion and breathing (30%) Blood glucose levels (15%) R. Boellaard 2009, J Nucl Med Supplement Issue 50: 11S

Glu 200 mg% Glu 79 mg% Karoline Spaepen-Sigrid Stroobants Department of Nuclear Medicine University Hospital Gasthuisberg Leuven, Belgium

Lowe VJ et al. Optimum scanning protocol?for FDG-PET evaluation of pulmonary malignancy. J Nucl Med. 1995, image taken from Shankar et al. JNM 2006

Effects of different number of OSEM iterations, as seen in the Netherlands, on SUV SUVmax = 4.0 5.9 6.4 8.6 SUV 50%= 3.0 4.1 4.6 5.9

Entire chain of process determines quantitative result of an imaging biomaker Needs consistency of the execution of imaging procedure in longitudinal setting

Standardisation and quantification Personalized management of cancer allows the use of specific drugs Molecular imaging techniques can be used to study several tumors FDG PET-CT has been proposed as a surrogate biomarker for monitoring cancer therapies There are several radiopharmaceuticals other than FDG, with the potential to characterize tumors and monitor response to therapy Imaging biomarkers must be standard and quantitative Courtesy of Arturo Chiti

Quantitative imaging biomarker Requirements for (quantitative) imaging biomarkers: Repeatability (in one patient using the same PET/CT system) Reproducibility (between patients, systems and institutions) of performance, analysis and interpretation This implies that standardisation & harmonisation of imaging procedures are essential

FDG PET and PET/CT: EANM Procedure Guidelines for Tumour PET Imaging: version 1.0 Eur.J.Nucl.Med.Mol.Imag. 2010

The EANM guideline for FDG PET and PET/CT provides recommendations for: Minimising physiological or biological effects by patient preparation guidelines Procedures to ensure accurate FDG administration Matching of PET study statistics ( image quality )by prescribing FDG dosage as function of patient weight, type of scanner, acquisition mode and scan duration Matching of image resolutionby specifying image reconstruction settings and providing activity concentration recovery coefficients specifications (QC experiment) Standardisation of data analysisby prescribing region of interest strategies and SUV measures Multi-center QC/QA procedures for PET and PET/CT scanners

Multi-center QC and calibration Daily QC conform standard procedure of system / manufacturer Calibration QC using (cylindrical) phantom (15-30cm diameter) Adjusted NEMA NU 2-2001 Image Quality procedure/measurement to measure recovery coefficients as function of sphere size (= effective image resolution ) CT-QC cf recommendations of ESR/national law Misc. QC (e.g. for scales, alignment etc)

Multi-center QC and calibration Calibration QC specification: maximum allowable calibration deviation = + or 10% (global) SUV recovery specifications: for SUVmax (focus as SUVmax is used clinically!) for SUVmean [BQML] 20000.0 15000.0 10000.0 5000.0 0.0 SUV recovery coefficient 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 VOI A50%, new limits 0 0.1 1 10 100 Sphere volume (ml)

Multi-center harmonization of quantification Calibration QC PET/CT and DC Results at first testm Maccredited sites 1.30 1.20 1.10 GE Philips Siemens 1.3 1.2 1.1 GE Philips Siemens GE Philips Siemens 1.00 1 0.90 0.9 0.80 0.8 0.70 0.5 1.5 2.5 3.5 0.7 0.5 1 1.5 2 2.5 3 3.5 ~5% outside specs Comparable calibration accuracy and SUV recovery among sites and vendors is feasible (n=>65)

Multi-center harmonization of quantification 20000.0 Image Quality % SUV recovery [BQML] 15000.0 10000.0 Results at first testm Maccredited sites 5000.0 0.0 1.60 SUV Max RC - all vendors 1.6 SUV MAX RC - all vendors 1.40 1.4 1.20 1.2 SUV MAX RC 1.00 0.80 0.60 SUV MAX RC 1 0.8 0.6 0.40 0.4 0.20 0.2 0.00 0 5 10 15 20 25 30 Sphere volume (ml) 0 0 5 10 15 20 25 30 Sphere volume (ml) Comparable SUV recovery among sites and vendors is feasible (n=>65)

Multi-center harmonization of quantification 20000.0 Image Quality % SUV recovery [BQML] 15000.0 10000.0 1.2 SUV MAX 5000.0 0.0 1 SUV MAX RC 0.8 0.6 0.4 0.2 GE Philips Siemens 0 0.1 1 10 100 Sphere volume (ml) Small differences in RC curve shape between vendors

Should we use PSF reconstructions? Lasnon et al. EJNMMI 2013 Most accurate PSF + SUVmean (VOI=3D-50%) Most accurate No PSF + SUVmax Note that simple SUVmean & 3D 50% VOIs only perform well: - Simple phantoms - No tracer uptake heterogeneity - Good scan statistics None of these characteristics are met in clinical practice. (Cheebsumon et al. JNM 2011, EJNMMI 2011)

Why do we use SUVmax? SUVmax suffers from upward bias due to noise (Boellaard et al, JNM 1996, 2011, Lodge et al, JNM 2011) poor reproducibility and accuracy for PSF (HD) reconstructions (Tong, IEEE TNS 2011, Rahmim et al. MedPhys 2013, Lasnon et al. EJNMMI 2013) Despite these limitions: May represent metabolically most active part of tumor VOIs are not standardized simple isocontour work only well for simple phantoms CT and PET based manual segmentation suffer from observer variability CT based segmentation may suffer from CT-PET alignment issues PET based automated delineation methods: variability of methods variability in implementation of same method performance depend strongly on underlying image characteristics (Cheebsumon et al. JNM2011, EJNMMI 2011) cannot deal well with tracer uptake heterogeneity Therefore, need to optimize image quality for use of SUVmax

Future directions SUVmax suffers from: upward bias due to noise (Boellaard et al, JNM 1996, 2011, Lodge et al, JNM 2011, Lasnon EJNMMI 2013) poor reproducibility and accuracy for PSF (HD) reconstruction (Boellaard et al., JNM 2011, Tong, IEEE TNS 2011, Lasnon et al. JNM 2013) 1. Explore use of SUVpeak: 1ml spherical VOI located at highest average value good surrogate for SUVmax almost no observer variability less sensitive to scanner performance differences BUT, no everywhere available inventory among accredited sites is ongoing (Q4/2013) 2. Explore implementation of EARL compliant acq/recon protocols by vendors Positive feedback from and ongoing discussions with GE, Philips and Siemens Explore strategy proposed by Lasnon et al. EJNMMI 2013 2nd recon or post-recon filter after PSF recon 3. Include measure and upper limit for noise within the IQ-QC experiments

Future directions 1.2 SUV MAX Makris et al. EJNMMI 2013 1.2 SUV PEAK 1 1 SUV MAX RC 0.8 0.6 0.4 SUV PEAK RC 0.8 0.6 0.4 0.2 0.2 0 0.1 1 10 100 Sphere volume 0 0.1 1 10 100 Sphere volume (ml) SUV RC for 2 different PET/CT systems: more difference in SUV MAX RC between systems than with PEAK SUV PEAK RC more smooth curve, less sensitive to image artefacts (next slide)

Some typical image artefacts Edge or ring (Gibbs) artefacts: Allways seen with PSF based reconstructions Frequently on specific TF systems (>50% of cases) Problems in case using SUVmax Mitigation: SUVpeak?

Future directions UPICT uniformity of protocols in clinical trials: FDG PET/CT consensus guideline out for public comment (Q4/2013) QIBA FDG PET/CT Profile: under review/revision addresses performance and compliance criteria (systems and users)

Multi-center harmonization of quantification Main principles of EANM GL and EARL accreditation Standardisation of PET examinination procedure Quantification is combination of: image resolution image noise data analysis methods (SUVmax de facto the standard in practice) EARL QC s s based on exploration to find highest common denominator in performance of scanner calibration SUV-RCs SUVmax, transition to SUV Peak Scanner performance harmonization is feasible on a large scale, but long term sustainability requires support and service from vendors goal of SNM-CTN & EANM/EARL

FDG PET and PET/CT: EANM Procedure Guidelines for Tumour PET Imaging: version 1.0 Ronald Boellaard, Mike O Doherty, Wolfgang A. Weber, Felix M. Mottaghy, Markus N. Lonsdale, Sigrid G. Stroobants, Wim J.G. Oyen, Joerg Kotzerke, Otto S. Hoekstra, Jan Pruim, Paul K. Marsden, Klaus Tatsch, Corneline J. Hoekstra, Eric.P. Visser, Bertjan Arends, Fred J. Verzijlbergen, Josee M. Zijlstra, Emile FI Comans, Adriaan A. Lammertsma, Anne M. Paans, Antoon T. Willemsen, Thomas Beyer, Andreas Bockisch, Cornelia Schaefer-Prokop, Dominique Delbeke, Richard P. Baum, Arturo Chiti, Bernd J. Krause. Eur.J.Nucl.Med.Mol.Imag. 2010

Thank you for your attention!