FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0.

The purpose of these guidelines is to assist physicians in recommending, performing, interpreting and reporting the results of FDG PET/CT for oncological imaging of adult patients. PET is a quantitative imaging technique and therefore requires a common quality control (QC)/quality assurance (QA) procedure to maintain the accuracy and precision of quantitation. Repeatability and reproducibility are two essential requirements for any quantitative measurement and/or imaging biomarker. Repeatability relates to the uncertainty in obtaining the same result in the same patient when he or she is examined more than once on the same system. However, imaging biomarkers should also have adequate reproducibility, i.e. the ability to yield the same result in the same patient when that patient is examined on different systems and at different imaging sites. Adequate repeatability and reproducibility are essential for the clinical management of patients and the use of FDG PET/CT within multicentre trials. A common standardised imaging procedure will help promote the appropriate use of FDG PET/CT imaging and increase the value of publications and, therefore, their contribution to evidence-based medicine. Moreover, consistency in numerical values between platforms and institutes that acquire the data will potentially enhance the role of semiquantitative and quantitative image interpretation. Precision and accuracy are additionally important as FDG PET/CT is used to evaluate tumour response as well as for diagnosis, prognosis and staging. Therefore both the previous and these new guidelines specifically aim to achieve standardised uptake value harmonisation in multicentre settings.

Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability.

PURPOSE: Besides basic measurements as maximum standardized uptake value (SUV)max or SUVmean derived from 18F-FDG positron emission tomography (PET) scans, more advanced quantitative imaging features (i.e. "Radiomics" features) are increasingly investigated for treatment monitoring, outcome prediction, or as potential biomarkers. With these prospected applications of Radiomics features, it is a requisite that they provide robust and reliable measurements. The aim of our study was therefore to perform an integrated stability analysis of a large number of PET-derived features in non-small cell lung carcinoma (NSCLC), based on both a test-retest and an inter-observer setup. METHODS: Eleven NSCLC patients were included in the test-retest cohort. Patients underwent repeated PET imaging within a one day interval, before any treatment was delivered. Lesions were delineated by applying a threshold of 50% of the maximum uptake value within the tumor. Twenty-three NSCLC patients were included in the inter-observer cohort. Patients underwent a diagnostic whole body PET-computed tomography (CT). Lesions were manually delineated based on fused PET-CT, using a standardized clinical delineation protocol. Delineation was performed independently by five observers, blinded to each other. Fifteen first order statistics, 39 descriptors of intensity volume histograms, eight geometric features and 44 textural features were extracted. For every feature, test-retest and inter-observer stability was assessed with the intra-class correlation coefficient (ICC) and the coefficient of variability, normalized to mean and range. Similarity between test-retest and inter-observer stability rankings of features was assessed with Spearman's rank correlation coefficient. RESULTS: Results showed that the majority of assessed features had both a high test-retest (71%) and inter-observer (91%) stability in terms of their ICC. Overall, features more stable in repeated PET imaging were also found to be more robust against inter-observer variability. CONCLUSION: Results suggest that further research of quantitative imaging features is warranted with respect to more advanced applications of PET imaging as being used for treatment monitoring, outcome prediction or imaging biomarkers.

Measuring response to therapy using FDG PET: semi-quantitative and full kinetic analysis.

PURPOSE: Imaging with positron emission tomography (PET) using (18)F-2-fluoro-2-deoxy-D: -glucose (FDG) plays an increasingly important role for response assessment in oncology. Several methods for quantifying FDG PET results exist. The goal of this study was to analyse and compare various semi-quantitative measures for response assessment with full kinetic analysis, specifically in assessment of novel therapies. METHODS: Baseline and response dynamic FDG studies from two different longitudinal studies (study A: seven subjects with lung cancer and study B: six subjects with gastrointestinal cancer) with targeted therapies were reviewed. Quantification of tumour uptake included full kinetic methods, i.e. nonlinear regression (NLR) and Patlak analyses, and simplified measures such as the simplified kinetic method (SKM) and standardized uptake value (SUV). An image-derived input function was used for NLR and Patlak analysis. RESULTS: There were 18 and 9 lesions defined for two response monitoring studies (A and B). In all cases there was excellent correlation between Patlak- and NLR-derived response (R (2) > 0.96). Percentage changes seen with SUV were significantly different from those seen with Patlak for both studies (p < 0.05). After correcting SUV for plasma glucose, SUV and Patlak responses became similar for study A, but large differences remained for study B. Further analysis revealed that differences in responses amongst methods in study B were primarily due to changes in the arterial input functions. CONCLUSION: Use of simplified methods for assessment of drug efficacy or treatment response may provide different results than those seen with full kinetic analysis.

Partial volume correction strategies for quantitative FDG PET in oncology.

PURPOSE: Quantitative accuracy of positron emission tomography (PET) is affected by partial volume effects resulting in increased underestimation of the standardized uptake value (SUV) with decreasing tumour volume. The purpose of the present study was to assess accuracy and precision of different partial volume correction (PVC) methods. METHODS: Three methods for PVC were evaluated: (1) inclusion of the point spread function (PSF) within the reconstruction, (2) iterative deconvolution of PET images and (3) calculation of spill-in and spill-out factors based on tumour masks. Simulations were based on a mathematical phantom with tumours of different sizes and shapes. Phantom experiments were performed in 2-D mode using the National Electrical Manufacturers Association (NEMA) NU2 image quality phantom containing six differently sized spheres. Clinical studies (2-D mode) included a test-retest study consisting of 10 patients with stage IIIB and IV non-small cell lung cancer and a response monitoring study consisting of 15 female breast cancer patients. In all studies tumour or sphere volumes of interest (VOI) were generated using VOI based on adaptive relative thresholds. RESULTS: Simulations and experiments provided similar results. All methods were able to accurately recover true SUV within 10% for spheres equal to and larger than 1 ml. Reconstruction-based recovery, however, provided up to twofold better precision than image-based methods. Clinical studies showed that PVC increased SUV by 5-80% depending on tumour size. Test-retest variability slightly worsened from 9.8 +/- 6.5 without to 10.8 +/- 7.9% with PVC. Finally, PVC resulted in slightly smaller SUV responses, i.e. from -30.5% without to -26.3% with PVC after the first cycle of treatment (p < 0.01). CONCLUSION: PVC improves accuracy of SUV without decreasing (clinical) test-retest variability significantly and it has a small, but significant effect on observed tumour responses. Reconstruction-based PVC outperforms image-based methods, but requires dedicated reconstruction software. Image-based methods are good alternatives because of their ease of implementation and their similar performance in clinical studies.

FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0.

The aim of this guideline is to provide a minimum standard for the acquisition and interpretation of PET and PET/CT scans with [18F]-fluorodeoxyglucose (FDG). This guideline will therefore address general information about[18F]-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) and is provided to help the physician and physicist to assist to carrying out,interpret, and document quantitative FDG PET/CT examinations,but will concentrate on the optimisation of diagnostic quality and quantitative information.

The Netherlands protocol for standardisation and quantification of FDG whole body PET studies in multi-centre trials.

INTRODUCTION: Several studies have shown the usefulness of positron emission tomography (PET) quantification using standardised uptake values (SUV) for diagnosis and staging, prognosis and response monitoring. Many factors affect SUV, such as patient preparation procedures, scan acquisition, image reconstruction and data analysis settings, and the variability in methodology across centres prohibits exchange of SUV data. Therefore, standardisation of 2-[(18)F] fluoro-2-deoxy-D-glucose (FDG) PET whole body procedures is required in multi-centre trials. METHODS: A protocol for standardisation of quantitative FDG whole body PET studies in the Netherlands (NL) was defined. This protocol is based on standardisation of: (1) patient preparation; (2) matching of scan statistics by prescribing dosage as function of patient weight, scan time per bed position, percentage of bed overlap and image acquisition mode (2D or 3D); (3) matching of image resolution by prescribing reconstruction settings for each type of scanner; (4) matching of data analysis procedure by defining volume of interest methods and SUV calculations and; (5) finally, a multi-centre QC procedure is defined using a 20-cm diameter phantom for verification of scanner calibration and the NEMA NU 2 2001 Image Quality phantom for verification of activity concentration recoveries (i.e., verification of image resolution and reconstruction convergence). DISCUSSION: This paper describes a protocol for standardization of quantitative FDG whole body multi-centre PET studies. CONCLUSION: The protocol was successfully implemented in the Netherlands and has been approved by the Netherlands Society of Nuclear Medicine.

Prognostic relevance of response evaluation using [18F]-2-fluoro-2-deoxy-D-glucose positron emission tomography in patients with locally advanced non-small-cell lung cancer.

PURPOSE: The objective of this study was to determine the accuracy of (early) response measurements using [18F]-2-fluoro-2-deoxy-D-glucose positron emission tomography (18FDG PET) with respect to survival of patients with stage IIIA-N2 non-small-cell lung cancer (NSCLC) undergoing induction chemotherapy (IC), with a comparative analysis of PET methods. PATIENTS AND METHODS: In a prospective multicenter study, PET was performed in patients before IC and after one and three cycles. Computed tomography (CT) was performed before and after IC. Glucose consumption (metabolic rate of glucose [MRglu]) was measured using Patlak graphical analysis and correlated with simplified methods. Mediastinal lymph node (MLN) status was assessed visually. Cox proportional hazards analysis was used to determine the prognostic relevance of CT and PET measures of response with respect to survival. RESULTS: Complete PET data sets were available in 47 patients. Median survival was 21 months. MLN status after IC by PET predicted survival (hazard ratio [HR], 2.33; 95% CI, 1.04 to 5.22; P = .04) in contrast with CT (HR, 1.87; 95% CI, 0.81 to 4.30; P = .14). Residual MRglu after IC proved to be the best prognostic factor (HR, 1.95; 95% CI, 1.28 to 2.97; P = .002). Multivariate stepwise analysis showed that PET identified prognostically different strata in patients considered responsive according to CT. Residual MRglu after one cycle selected patients with different outcomes (HR, 2.04; 95% CI, 1.18 to 3.52; P = .01). Simplified quantitative 18FDG PET methods were correlated with Patlak graphical analysis during and after therapy (r > or = 0.90). CONCLUSION: 18FDG PET has additional value over CT in monitoring response to IC in patients with stage IIIA-N2 NSCLC, and it seems feasible to predict survival early during IC. Simple semiquantitative and complex PET methods perform equally well.

Measurement of perfusion in stage IIIA-N2 non-small cell lung cancer using H(2)(15)O and positron emission tomography.

PURPOSE: As the interest in antiangiogenesis therapy in oncology is rising, the need for in vivo techniques to monitor such therapy is obvious. Measurement of tumor perfusion using positron emission tomography and H(2)(15)O potentially is such a technique. The objective of the present study was to assess whether it is feasible to measure perfusion in vivo in non-small cell lung cancer (NSCLC) using H(2)(15)O and positron emission tomography. EXPERIMENTAL DESIGN: Fifteen dynamic H(2)(15)O and [(18)F]2-fluoro-2-deoxy-D-glucose ((18)FDG) studies were performed in 10 patients with stage IIIA-N2 NSCLC. Blood flow (BF) data were correlated with simplified methods of analysis (tumor:normal tissue ratio and standardized uptake value) and with glucose metabolism (MR(glu)). RESULTS: (18)FDG data were required for accurate definition of tumor and mediastinal lymph node metastases. There was large intertumor variation in BF. Correlation of simplified methods of analysis with quantitative BF was poor. In addition, BF and MR(glu) were not correlated. CONCLUSION: Measurement of BF in NSCLC using H(2)(15)O and (18)FDG is feasible. Simple uptake analysis, however, cannot be used as an indicator of perfusion. Whether BF can be used for response monitoring needs to be evaluated in a large patient study, where results can be compared with outcome.

Methods to monitor response to chemotherapy in non-small cell lung cancer with 18F-FDG PET.

UNLABELLED: PET using 18F-FDG is a promising technique to monitor response in oncology. Unfortunately, a multitude of analytic methods is in use. To date, it is not clear whether simplified methods could replace complex quantitative methods in routine clinical practice. The aim of this study was to select those methods that would qualify for further assessment in a future prospective response-monitoring study by comparing results with patient outcome. METHODS: Dynamic 18F-FDG PET scans were obtained on 2 groups of patients. First, 10 patients with advanced non-small cell lung cancer (NSCLC) were scanned on consecutive days before treatment to assess test-retest variability. Second, 30 scans were obtained on 19 patients with locally advanced NSCLC as part of an ongoing response-monitoring study. These scans were analyzed by 2 observers to assess observer variability. In addition, these studies were used to compare various methods with the gold standard, full kinetic analysis (nonlinear regression [NLR]). RESULTS: Using an image-derived input function, NLR showed excellent test-retest and observer agreement confirming that it could be used as a gold standard method. From a total of 34 analytic methods, 10 showed good correlation with NLR. Taking into account the degree of complexity of the methods, 4 remain for further evaluation. CONCLUSION: The optimal method for analysis of 18F-FDG PET data was determined for several levels of complexity. Four methods need to be evaluated further to determine the optimal trade-off between simplicity and accuracy for routine clinical practice.

Positron emission tomography using 2-deoxy-2-[18F]-fluoro-D-glucose for response monitoring in locally advanced gastroesophageal cancer; a comparison of different analytical methods.

PURPOSE: To determine the ability of 2-deoxy-2-[18F]-fluoro-D-glucose (FDG) positron emission tomography (PET) to monitor response in locally advanced gastroesophageal cancer (LAGEC). Additionally, optimal FDG-PET methods for response monitoring were selected. PROCEDURES: Sequential dynamic FDG-PET scans were performed in 13 patients with LAGEC (T2-3N0-1M0-1a) treated with neoadjuvant cisplatin and gemcitabine plus granulocyte macrophage colony stimulating growth factor at a three weekly schedule. The standard FDG-PET method, nonlinear regression (NLR), was compared with computed tomography (CT), endoscopic-ultrasound (EUS), and histopathology as well as with 21 simplified analytical FDG-PET methods. RESULTS: Five out of 12 operated tumors responded histopathologically with less than 10% residual tumorcells (42%). These had a higher decrease in FDG uptake compared with nonresponders (P=0.008). Early (after two cycles) and late (after completed induction therapy) response evaluation showed a specificity of 86% and 100%, respectively, and a sensitivity of 100%. Both FDG-PET and EUS were superior to CT. From 21 methods analyzing FDG uptake, the quantitative Patlak analysis, the simplified kinetic method (SKM), and the semiquantitative standardized uptake value corrected for bodyweight (SUV-BW) seemed to correlate best with NLR. CONCLUSIONS: FDG-PET reliably predicted response in LAGEC. FDG-PET measurements using Patlak analysis or the more clinical applicable SKM and SUV-BW were acceptable alternatives to NLR.

Measurement of metabolic tumor volume: static versus dynamic FDG scans.

BACKGROUND: Metabolic tumor volume assessment using positron-emission tomography [PET] may be of interest for both target volume definition in radiotherapy and monitoring response to therapy. It has been reported, however, that metabolic volumes derived from images of metabolic rate of glucose (generated using Patlak analysis) are smaller than those derived from standardized uptake value [SUV] images. The purpose of this study was to systematically compare metabolic tumor volume assessments derived from SUV and Patlak images using a variety of (semi-)automatic tumor delineation methods in order to identify methods that can be used reliably on (whole body) SUV images. METHODS: Dynamic [18F]-fluoro-2-deoxy-D-glucose [FDG] PET data from 10 lung and 8 gastrointestinal cancer patients were analyzed retrospectively. Metabolic tumor volumes were derived from both Patlak and SUV images using five different types of tumor delineation methods, based on various thresholds or on a gradient. RESULTS: In general, most tumor delineation methods provided more outliers when metabolic volumes were derived from SUV images rather than Patlak images. Only gradient-based methods showed more outliers for Patlak-based tumor delineation. Median measured metabolic volumes derived from SUV images were larger than those derived from Patlak images (up to 59% difference) when using a fixed percentage threshold method. Tumor volumes agreed reasonably well (< 26% difference) when applying methods that take local signal-to-background ratio [SBR] into account. CONCLUSION: Large differences may exist in metabolic volumes derived from static and dynamic FDG image data. These differences depend strongly on the delineation method used. Delineation methods that correct for local SBR provide the most consistent results between SUV and Patlak images.

How should we analyse FDG PET studies for monitoring tumour response?

FDG PET is a promising technique for monitoring tumour response early during anticancer therapy. Progress, however, has been limited owing to the multitude of methods currently in use. Here, the most promising techniques for multi-centre trials are discussed briefly, with emphasis on the need for standardisation. In addition, an approach is presented for response monitoring studies using newly developed drugs. This approach makes use of a large database of response monitoring studies, which defines the relationship between simplified clinical methods and full quantitative analysis for classic cytotoxic drugs. For a new drug, first a pilot study is performed to assess whether it affects this relationship. Based on this pilot, it is decided whether or not a simplified clinical method can be used in further studies.

Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial.

PURPOSE: Quantitative measurement of tracer uptake in a tumour can be influenced by a number of factors, including the method of defining regions of interest (ROIs) and the reconstruction parameters used. The main purpose of this study was to determine the effects of different ROI methods on quantitative outcome, using two reconstruction methods and the standard uptake value (SUV) as a simple quantitative measure of FDG uptake. METHODS: Four commonly used methods of ROI definition (manual placement, fixed dimensions, threshold based and maximum pixel value) were used to calculate SUV (SUV([MAN]), SUV15 mm, SUV50, SUV75 and SUVmax, respectively) and to generate "metabolic" tumour volumes. Test-retest reproducibility of SUVs and of "metabolic" tumour volumes and the applicability of ROI methods during chemotherapy were assessed. In addition, SUVs calculated on ordered subsets expectation maximisation (OSEM) and filtered back-projection (FBP) images were compared. RESULTS: ROI definition had a direct effect on quantitative outcome. On average, SUV[MAN), SUV15 mm, SUV50 and SUV75, were respectively 48%, 27%, 34% and 15% lower than SUVmax when calculated on OSEM images. No statistically significant differences were found between SUVs calculated on OSEM and FBP reconstructed images. Highest reproducibility was found for SUV15 mm and SUV[MAN] (ICC 0.95 and 0.94, respectively) and for "metabolic" volumes measured with the manual and 50% threshold ROIs (ICC 0.99 for both). Manual, 75% threshold and maximum pixel ROIs could be used throughout therapy, regardless of changes in tumour uptake or geometry. SUVs showed the same trend in relative change in FDG uptake after chemotherapy, irrespective of the ROI method used. CONCLUSION: The method of ROI definition has a direct influence on quantitative outcome. In terms of simplicity, user-independence, reproducibility and general applicability the threshold-based and fixed dimension methods are the best ROI methods. Threshold methods are in addition relatively independent of changes in size and geometry, however, and may therefore be more suitable for response monitoring purposes.