Repeatability of metabolically active tumor volume measurements with FDG PET/CT in advanced gastrointestinal malignancies: a multicenter study.

PURPOSE: To evaluate the feasibility and repeatability of various metabolically active tumor volume ( MATV metabolically active tumor volume ) quantification methods in fluorine 18 fluorodeoxyglucose ( FDG fluorine 18 fluorodeoxyglucose ) positron emission tomography (PET)/computed tomography (CT) in a multicenter setting and propose the optimal MATV metabolically active tumor volume method together with the minimal threshold for future response evaluation studies. MATERIALS AND METHODS: The study was approved by the institutional review board of all four participating centers, and patients provided written informed consent. Thirty-four patients with advanced gastrointestinal malignancies underwent two FDG fluorine 18 fluorodeoxyglucose PET/CT examinations within 1 week. MATV metabolically active tumor volume s were defined semiautomatically with 27 variations of tumor delineation methods with different reference values. Feasibility was determined as the percentage of successful tumor segmentations per MATV metabolically active tumor volume method. Repeatability was determined with intraclass correlation coefficients, Bland-Altman plots, and limits of agreement ( LOA limit of agreement s) of the percentage difference between the test and repeat test measurements. In addition, LOA limit of agreement variability per center was investigated. RESULTS: In total, 136 lesions were identified. Feasibility of tumor segmentation ranged from 54% to 100% (74-136 of 136 lesions); repeatability was evaluated for 19 MATV metabolically active tumor volume methods with feasibility of greater than 95%. The median MATV metabolically active tumor volume derived with 50% threshold of mean standardized uptake value ( SUV standardized uptake value ) of a sphere of 12-mm diameter with highest local intensity ( SUVhp mean SUV of a sphere of 12-mm diameter with highest local intensity ), which may not include the voxel with highest SUV standardized uptake value corrected for local background, was 5.7 and 6.1 mL for test and retest scans, respectively, with a relative LOA limit of agreement of 36.1%. Comparable repeatability was found between centers. A difference in uptake time between scan 1 and 2 of 15 minutes or longer had a minor negative influence on repeatability. CONCLUSION: MATV metabolically active tumor volume measured with 50% of SUVhp mean SUV of a sphere of 12-mm diameter with highest local intensity corrected for local background is recommended in multicenter FDG fluorine 18 fluorodeoxyglucose PET/CT studies on the basis of a high feasibility (96%) and repeatability ( LOA limit of agreement of 36.1%).

Effects of reusing baseline volumes of interest by applying (non-)rigid image registration on positron emission tomography response assessments.

OBJECTIVES: Reusing baseline volumes of interest (VOI) by applying non-rigid and to some extent (local) rigid image registration showed good test-retest variability similar to delineating VOI on both scans individually. The aim of the present study was to compare response assessments and classifications based on various types of image registration with those based on (semi)-automatic tumour delineation. METHODS: Baseline (n = 13), early (n = 12) and late (n = 9) response (after one and three cycles of treatment, respectively) whole body [(18)F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (PET/CT) scans were acquired in subjects with advanced gastrointestinal malignancies. Lesions were identified for early and late response scans. VOI were drawn independently on all scans using an adaptive 50% threshold method (A50). In addition, various types of (non-)rigid image registration were applied to PET and/or CT images, after which baseline VOI were projected onto response scans. Response was classified using PET Response Criteria in Solid Tumors for maximum standardized uptake value (SUV(max)), average SUV (SUV(mean)), peak SUV (SUV(peak)), metabolically active tumour volume (MATV), total lesion glycolysis (TLG) and the area under a cumulative SUV-volume histogram curve (AUC). RESULTS: Non-rigid PET-based registration and non-rigid CT-based registration followed by non-rigid PET-based registration (CTPET) did not show differences in response classifications compared to A50 for SUV(max) and SUV(peak), however, differences were observed for MATV, SUV(mean), TLG and AUC. For the latter, these registrations demonstrated a poorer performance for small lung lesions (<2.8 ml), whereas A50 showed a poorer performance when another area with high uptake was close to the target lesion. All methods were affected by lesions with very heterogeneous tracer uptake. CONCLUSIONS: Non-rigid PET- and CTPET-based image registrations may be used to classify response based on SUV(max) and SUV(peak). For other quantitative measures future studies should assess which method is valid for response evaluations by correlating with survival data.

Test-retest variability of various quantitative measures to characterize tracer uptake and/or tracer uptake heterogeneity in metastasized liver for patients with colorectal carcinoma.

PURPOSE: The aim of this study was to assess test-retest variability of various quantitative measures to characterize tracer uptake and/or tracer uptake heterogeneity. PROCEDURES: Two baseline whole-body 2-deoxy-2-[(18)F]fluoro-D-glucose positron emission tomography/computed tomography (CT) scans were acquired in 29 subjects with colorectal carcinoma. Whole liver volumes of interest (VOI) were defined manually on CT. For each VOI, various quantitative measures were determined, e.g., skewness, kurtosis, and the area under a cumulative standardized uptake value-volume histogram (AUC). RESULTS: AUC showed a good reliability (intraclass correlation coefficients (ICC): 0.97) and low test-retest variability (10%). Most other quantitative parameters showed excellent agreement between test and retest values (ICC: 0.78-0.97) and low test-retest variability (<12%), except for kurtosis. Skewness also showed a higher test-retest variability (19%), but good ICC (0.96) and it correlated well with AUC (R (2): 0.90, all others: <0.76). CONCLUSION: This high reproducibility and reliability of AUC warrant further investigation of its use for quantification of tracer uptake heterogeneity.

Repeatability of 18F-FDG uptake measurements in tumors: a metaanalysis.

UNLABELLED: PET with the glucose analog (18)F-FDG is increasingly used to monitor tumor response to therapy. To use quantitative measurements of tumor (18)F-FDG uptake for assessment of tumor response, the repeatability of this quantitative metabolic imaging method needs to be established. Therefore, we determined the repeatability of different standardized uptake value (SUV) measurements using the available data. METHODS: A systematic literature search was performed to identify studies addressing (18)F-FDG repeatability in malignant tumors. The level of agreement between test and retest values of 2 PET uptake measures, maximum SUV (SUV(max)) and mean SUV (SUV(mean)), was assessed with the coefficient of repeatability using generalized linear mixed-effects models. In addition, the influence of tumor volume on repeatability was assessed. Principal component transformation was used to compare the reproducibility of the 2 different uptake measures. RESULTS: Five cohorts were identified for this metaanalysis. For SUV(max) and SUV(mean), datasets of 86 and 102 patients, respectively, were available. Percentage repeatability is a function of the level of uptake. SUV(mean) had the best repeatability characteristics; for serial PET scans, a threshold of a combination of 20% as well as 1.2 SUV(mean) units was most appropriate. After adjusting for uptake rate, tumor volume had minimal influence on repeatability. CONCLUSION: SUV(mean) had better repeatability performance than SUV(max). Both measures showed poor repeatability for lesions with low (18)F-FDG uptake. We recommend the evaluation of biologic effects in PET by reporting a combination of minimal relative and absolute changes to account for test-retest variability.

Effects of rigid and non-rigid image registration on test-retest variability of quantitative [18F]FDG PET/CT studies.

BACKGROUND: [18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET) is a valuable tool for monitoring response to therapy in oncology. In longitudinal studies, however, patients are not scanned in exactly the same position. Rigid and non-rigid image registration can be applied in order to reuse baseline volumes of interest (VOI) on consecutive studies of the same patient. The purpose of this study was to investigate the impact of various image registration strategies on standardized uptake value (SUV) and metabolic volume test-retest variability (TRT). METHODS: Test-retest whole-body [18F]FDG PET/CT scans were collected retrospectively for 11 subjects with advanced gastrointestinal malignancies (colorectal carcinoma). Rigid and non-rigid image registration techniques with various degrees of locality were applied to PET, CT, and non-attenuation corrected PET (NAC) data. VOI were drawn independently on both test and retest scans. VOI drawn on test scans were projected onto retest scans and the overlap between projected VOI and manually drawn retest VOI was quantified using the Dice similarity coefficient (DSC). In addition, absolute (unsigned) differences in TRT of SUVmax, SUVmean, metabolic volume and total lesion glycolysis (TLG) were calculated in on one hand the test VOI and on the other hand the retest VOI and projected VOI. Reference values were obtained by delineating VOIs on both scans separately. RESULTS: Non-rigid PET registration showed the best performance (median DSC: 0.82, other methods: 0.71-0.81). Compared with the reference, none of the registration types showed significant absolute differences in TRT of SUVmax, SUVmean and TLG (p > 0.05). Only for absolute TRT of metabolic volume, significant lower values (p < 0.05) were observed for all registration strategies when compared to delineating VOIs separately, except for non-rigid PET registrations (p = 0.1). Non-rigid PET registration provided good volume TRT (7.7%) that was smaller than the reference (16%). CONCLUSION: In particular, non-rigid PET image registration showed good performance similar to delineating VOI on both scans separately, and with smaller TRT in metabolic volume estimates.

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.

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.

Repeatability of 18F-FDG PET in a multicenter phase I study of patients with advanced gastrointestinal malignancies.

UNLABELLED: (18)F-FDG PET is often used to monitor tumor response in multicenter oncology clinical trials. This study assessed the repeatability of several semiquantitative standardized uptake values (mean SUV [SUV(mean)], maximum SUV [SUV(max)], peak SUV [SUV(peak)], and the 3-dimensional isocontour at 70% of the maximum pixel value [SUV(70%)]) as measured by repeated baseline (18)F-FDG PET studies in a multicenter phase I oncology trial. METHODS: Double-baseline (18)F-FDG PET studies were acquired for 62 sequentially enrolled patients. Tumor metabolic activity was assessed by SUV(mean), SUV(max), SUV(peak), and SUV(70%). The effect on SUV repeatability of compliance with recommended image-acquisition guidelines and quality assurance (QA) standards was assessed. Summary statistics for absolute differences relative to the average of baseline values and repeatability analysis were performed for all patients and for a subgroup that passed QA, in both a multi- and a single-observer setting. Intrasubject precision of baseline measurements was assessed by repeatability coefficients, intrasubject coefficients of variation (CV), and confidence intervals on mean baseline differences for all SUV parameters. RESULTS: The mean differences between the 2 SUV baseline measurements were small, varying from -2.1% to 1.9%, and the 95% confidence intervals for these mean differences had a maximum half-width of about 5.6% across the SUV parameters assessed. For SUV(max), the intrasubject CV varied from 10.7% to 12.8% for the QA multi- and single-observer datasets and was 16% for the full dataset. The 95% repeatability coefficients ranged from -28.4% to 39.6% for the QA datasets and up to -34.3% to 52.3% for the full dataset. CONCLUSION: Repeatability results of double-baseline (18)F-FDG PET scans were similar for all SUV parameters assessed, for both the full and the QA datasets, in both the multi- and the single-observer settings. Centralized quality assurance and analysis of data improved intrasubject CV from 15.9% to 10.7% for averaged SUV(max). Thresholds for metabolic response in the multicenter multiobserver non-QA settings were -34% and 52% and in the range of -26% to 39% with centralized QA. These results support the use of (18)F-FDG PET for tumor assessment in multicenter oncology clinical trials.