Segmentation of positron emission tomography images: some recommendations for target delineation in radiation oncology

Multimodality imaging with CT, MR and FDG-PET for radiotherapy target volume delineation in oropharyngeal squamous cell carcinoma

Background

This study aimed to quantify the variation in oropharyngeal squamous cell carcinoma gross tumour volume (GTV) delineation between CT, MR and FDG PET-CT imaging.

Methods

A prospective, single centre, pilot study was undertaken where 11 patients with locally advanced oropharyngeal cancers (2 tonsil, 9 base of tongue primaries) underwent pre-treatment, contrast enhanced, FDG PET-CT and MR imaging, all performed in a radiotherapy treatment mask. CT, MR and CT-MR GTVs were contoured by 5 clinicians (2 radiologists and 3 radiation oncologists). A semi-automated segmentation algorithm was used to contour PET GTVs. Volume and positional analyses were undertaken, accounting for inter-observer variation, using linear mixed effects models and contour comparison metrics respectively.

Results

Significant differences in mean GTV volume were found between CT (11.9 cm³) and CT-MR (14.1 cm³), p < 0.006, CT-MR and PET (9.5 cm³), p < 0.0009, and MR (12.7 cm³) and PET, p < 0.016. Substantial differences in GTV position were found between all modalities with the exception of CT-MR and MR GTVs. A mean of 64 %, 74 % and 77 % of the PET GTVs were included within the CT, MR and CT-MR GTVs respectively. A mean of 57 % of the MR GTVs were included within the CT GTV; conversely a mean of 63 % of the CT GTVs were included within the MR GTV. CT inter-observer variability was found to be significantly higher in terms of position and/or volume than both MR and CT-MR (p < 0.05). Significant differences in GTV volume were found between GTV volumes delineated by radiologists (9.7 cm³) and oncologists (14.6 cm³) for all modalities (p = 0.001).

Conclusions

The use of different imaging modalities produced significantly different GTVs, with no single imaging technique encompassing all potential GTV regions. The use of MR reduced inter-observer variability. These data suggest delineation based on multimodality imaging has the potential to improve accuracy of GTV definition.

Trial registration

ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015.

Correlation between PET/CT parameters and KRAS expression in colorectal cancer

PURPOSE

The objective of this study was to correlate the association between mutated KRAS and wild-type colorectal cancer (CRC) by using various F-FDG PET-related parameters.

METHODS

One hundred twenty-one CRC patients who had undergone preoperative PET/CT were included in this study. Several PET/CT-related parameters, including SUVmax and various thresholds of metabolic tumor volume, total lesion glycolysis, and PET/CT-based tumor width, were measured. Tumor- and PET/CT-related parameters were correlated with genomic expression between KRAS mutant and wild-type groups, using a Mann-Whitney U test and logistic regression analysis.

RESULTS

Colorectal cancer tumors with a mutated KRAS exhibited higher SUVmax and an increased accumulation of FDG among several threshold methods. Multivariate analysis showed that SUVmax and using a 40% threshold level for maximal uptake of TW (TW40%) were the 2 predictors of KRAS mutations. The odds ratio was 1.23 for SUVmax (P = 0.02; 95% confidence interval, 1.01-1.52) and 1.15 for TW40% (P = 0.02; 95% confidence interval, 1.02-1.30). The accuracy of SUVmax for predicting mutated KRAS was higher in patients with colon or sigmoid colon cancers, whereas it was TW40% in those with rectal cancers.

CONCLUSIONS

SUVmax and TW40% were associated in CRC with KRAS mutations. PET/CT parameters can supplement genomic analysis to determine KRAS expression in CRC.

Advances in Radiotherapy for Head and Neck Cancer

Over the last few decades, significant improvements have been made in the radiotherapy (RT) treatment of head and neck malignancies. The progressive introduction of intensity-modulated RT and the use of multimodality imaging for target volume and organs at risk delineation, together with the use of altered fractionation regimens and concomitant administration of chemotherapy or targeted agents, have accompanied efficacy improvements in RT. Altogether, such improvements have translated into improvement in locoregional control and overall survival probability, with a decrease in the long-term adverse effects of RT and an improvement in quality of life. Further progress in the treatment of head and neck malignancies may come from a better integration of molecular imaging to identify tumor subvolumes that may require additional radiation doses (ie, dose painting) and from treatment adaptation tracing changes in patient anatomy during treatment. Proton therapy generates even more exquisite dose distribution in some patients, thus potentially further improving patient outcomes. However, the clinical benefit of these approaches, although promising, for patients with head and neck cancer need to be demonstrated in prospective randomized studies. In this context, our article will review some of these advances, with special emphasis on target volume and organ-at-risk delineation, use of molecular imaging for tumor delineation, dose painting for dose escalation, dose adaptation throughout treatment, and potential benefit of proton therapy.

PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods

Purpose

This work describes PETSTEP (PET Simulator of Tracers via Emission Projection): a faster and more accessible alternative to Monte Carlo (MC) simulation generating realistic PET images, for studies assessing image features and segmentation techniques.

Methods

PETSTEP was implemented within Matlab as open source software. It allows generating three-dimensional PET images from PET/CT data or synthetic CT and PET maps, with user-drawn lesions and user-set acquisition and reconstruction parameters. PETSTEP was used to reproduce images of the NEMA body phantom acquired on a GE Discovery 690 PET/CT scanner, and simulated with MC for the GE Discovery LS scanner, and to generate realistic Head and Neck scans. Finally the sensitivity (S) and Positive Predictive Value (PPV) of three automatic segmentation methods were compared when applied to the scanner-acquired and PETSTEP-simulated NEMA images.

Results

PETSTEP produced 3D phantom and clinical images within 4 and 6 min respectively on a single core 2.7 GHz computer. PETSTEP images of the NEMA phantom had mean intensities within 2% of the scanner-acquired image for both background and largest insert, and 16% larger background Full Width at Half Maximum. Similar results were obtained when comparing PETSTEP images to MC simulated data. The S and PPV obtained with simulated phantom images were statistically significantly lower than for the original images, but led to the same conclusions with respect to the evaluated segmentation methods.

Conclusions

PETSTEP allows fast simulation of synthetic images reproducing scanner-acquired PET data and shows great promise for the evaluation of PET segmentation methods.

Early volume variation of positive lymph nodes assessed by in-room mega voltage CT images predicts risk of loco-regional relapses in head and neck cancer patients treated with intensity-modulated radiotherapy

BACKGROUND

We investigated the possibility to early identify non-responding patients based on FDG-PET positive lymph nodes (PNs) volume variation assessed with in-room images.

MATERIAL AND METHODS

Twenty-seven head and neck cancer patients with at least one pre-treatment PNs were retrospectively analyzed; they received 54 Gy, 66 Gy, 69 Gy in 30 fractions on precautionary lymph nodal (N), primary (T) and PET positive (BTV) planning target volumes (PTVs), respectively with Helical TomoTherapy (SIB approach). PNs volume changes during treatment were assessed based on megavoltage computed tomography (MVCT) used for image guidance as ratio between volumes at fractions 10/20/30 and at first fraction. Data on T, N and M relapses (rT, rN, rM) were collected for all patients. The difference of PNs volume changes, during treatment, between patients with versus without relapses was tested (Mann-Whitney test). The impact of shrinkage on the corresponding survival curves (Cox proportional-hazard regression), dividing between no/moderate versus large shrinkage (based on ROC curve best cut-off value) was also investigated.

RESULTS

Median follow-up was 27.4 m (3.7-108.9). The numbers for rT, rN, rM were 5, 4, 6, respectively. Differences in PNs shrinkage were found between patients with and without rT/rN at all considered timing [fr 20, rT: 0.56 vs. 1.07 (median), p = 0.06; rN: 0.57 vs. 1.25, p = 0.07]. Differences were lower for rM. Survival curves provide high hazard ratios (HR) between PNs changes and rT/rN at all considered timing [fr 20, rT: best cut-off = 0.58, HR 5.1 (95% CI 0.5-49.4), p = 0.12; rN: best cut-off = 0.98, HR 14.9 (1.6-142.9), p = 0.01].

CONCLUSION

A limited shrinkage of PNs during treatment is associated with poorer outcome in terms of T/N relapses. The early variation of PNs observed on in-room images may provide useful information about the individual response with potential application in guiding an early adaptation of the treatment.

Comparison of (18)F-FDG PET/CT methods of analysis for predicting response to neoadjuvant chemoradiation therapy in patients with locally advanced low rectal cancer

PURPOSE

The aim of this study was to prospectively investigate the predictive value of (18)F-FDG PET/CT semiquantitative parameters for locally advanced low rectal cancer (LARC) treated by neoadjuvant chemoradiation therapy (nCRT).

METHODS

68 patients with LARC had (18)F-FDG PET/CT scans twice (baseline and 5-6 weeks post-nCRT). All patients underwent surgery with preservation of the sphincter 8 weeks later. (18)F-FDG PET/CT analysis was performed by visual response assessment (VRA) and semiquantitative parameters: SUVmax(baseline), SUVmean(baseline), MTV(baseline), TLG(baseline), SUVmax(post-nCRT), SUVmean(post-nCRT), MTV(post-nCRT), TLG(post-nCRT); ΔSUVmax and mean and Response indexes (RImax% and RImean%). Assessment of nCRT tumor response was performed according to the Mandard's Tumor Regression Grade (TRG) and (y)pTNM staging on the surgical specimens. Concordances of VRA with TRG, and with (y)pTNM criteria were evaluated by Cohen's K. Results were compared by t student test for unpaired groups. ROC curve analysis was performed.

RESULTS

VRA analysis of post-nCRT (18)F-FDG PET/CT scan for the (y)pTNM outcome showed sensitivity, specificity, accuracy, PPV, and NPV of 87.5%, 66.7%, 83.8%, 92.5%, and 53.3%, respectively. Concordances of VRA with TRG and with (y)pTNM were moderate. For the outcome variable TRG, the statistical difference between responders and non-responders was significant for SUVmax(post-nCRT) and RImean%; for the outcome variable (y)pTNM, there was a significant difference for MTV(baseline), SUVmax(post-nCRT), SUVmean(post-nCRT), MTV(post-nCRT), RImax%, and RImean%. ROC analysis showed better AUCs: for the outcome variable TRG for SUVmax(post-nCRT), SUVmean(post-nCRT), and RImean%; for the outcome variable (y)pTNM for MTVbaseline, SUVmax(post-nCRT), SUVmean(post-nCRT), MTV(post-nCRT), RImax%, and RImean%. No significant differences among parameters were found.

CONCLUSIONS

Qualitative and semiquantitative evaluations for (18)F-FDG PET/CT are the optimal approach; a valid parameter for response prediction has still to be established.

18F-FDG PET/CT role in staging of gastric carcinomas: comparison with conventional contrast enhancement computed tomography

The purpose of the report was to evaluate the role of fluorine-18 fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT) in staging gastric cancer comparing it with contrast enhancement computed tomography (CECT).This retrospective study included 45 patients who underwent performed whole body CECT and F-FDG PET/CT before any treatment. We calculated CECT and F-FDG PET/CT sensitivity, specificity, accuracy, positive and negative predictive values (PPV and NPV) for gastric, lymphnode, and distant localizations; furthermore, we compared the 2 techniques by McNemar test. The role of F-FDG PET/CT semiquantitative parameters in relation to histotype, grading, and site of gastric lesions were evaluated by ANOVA test.Sensitivity, specificity, accuracy, PPV and NPV of CECT, and F-FDG PET/CT for gastric lesion were, respectively, 92.11%, 57.14%, 86.66%, 92.11%, 57.14% and 81.58%, 85.71%, 82.22%, 96.88%, 46.15%. No differences were identified between the 2 techniques about sensitivity and specificity. No statistical differences were observed between PET parameters and histotype, grading, and site of gastric lesion. The results of CECT and F-FDG PET/CT about lymphnode involvement were 70.83%, 61.90%, 66.66%, 68%, 65% and 58.33%, 95.24%, 75.55%, 93.33%, 66.67%. The results of CECT and F-FDG PET/CT about distant metastases were 80%, 62.86%, 66.66%, 38.10%, 91.67% and 60%, 88.57%, 82.22%, 60%, 88.57%. FDG PET/CT specificity was significantly higher both for lymphnode and distant metastases.The F-FDG PET/CT is a useful tool for the evaluation of gastric carcinoma to detect primary lesion, lymphnode, and distant metastases using 1 single image whole-body technique. Integration of CECT with F-FDG PET/CT permits a more valid staging in these patients.

Comparison of [(11)C]choline Positron Emission Tomography With T2- and Diffusion-Weighted Magnetic Resonance Imaging for Delineating Malignant Intraprostatic Lesions

PURPOSE

The purpose of this study was to compare the accuracy of [(11)C]choline positron emission tomography (CHOL-PET) with that of the combination of T2-weighted and diffusion-weighted (T2W/DW) magnetic resonance imaging (MRI) for delineating malignant intraprostatic lesions (IPLs) for guiding focal therapies and to investigate factors predicting the accuracy of CHOL-PET.

METHODS AND MATERIALS

This study included 21 patients who underwent CHOL-PET and T2W/DW MRI prior to radical prostatectomy. Two observers manually delineated IPL contours for each scan, and automatic IPL contours were generated on CHOL-PET based on varying proportions of the maximum standardized uptake value (SUV). IPLs identified on prostatectomy specimens defined reference standard contours. The imaging-based contours were compared with the reference standard contours using Dice similarity coefficient (DSC), and sensitivity and specificity values. Factors that could potentially predict the DSC of the best contouring method were analyzed using linear models.

RESULTS

The best automatic contouring method, 60% of the maximum SUV (SUV60) , had similar correlations (DSC: 0.59) with the manual PET contours (DSC: 0.52, P=.127) and significantly better correlations than the manual MRI contours (DSC: 0.37, P<.001). The sensitivity and specificity values were 72% and 71% for SUV60; 53% and 86% for PET manual contouring; and 28% and 92% for MRI manual contouring. The tumor volume and transition zone pattern could independently predict the accuracy of CHOL-PET.

CONCLUSIONS

CHOL-PET is superior to the combination of T2W/DW MRI for delineating IPLs. The accuracy of CHOL-PET is insufficient for gland-sparing focal therapies but may be accurate enough for focal boost therapies. The transition zone pattern is a new classification that may predict how well CHOL-PET delineates IPLs.

Preoperative risk stratification using metabolic parameters of (18)F-FDG PET/CT in patients with endometrial cancer

PURPOSE

To evaluate the usefulness of metabolic parameters obtained by (18)F-FDG PET/CT for preoperative stratification of high-risk and low-risk endometrial carcinomas.

METHODS

Preoperative (18)F-FDG PET/CT was performed in 56 women with endometrial cancer. Maximum standardized uptake values (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) of primary tumours were compared with clinicopathological features of surgical specimens. Diagnostic performance in terms of differentiation of low-risk disease (endometrioid histology, histological grade 1 or 2, invasion of less than half of the myometrium, and FIGO stage I) from high-risk disease was assessed.

RESULTS

MTV and TLG were significantly higher in patients with higher histological grade (p = 0.0026 and p = 0.034), larger tumour size (p = 0.002 and p = 0.0017), lymphovascular space involvement (LVSI; p = 0.012 and p = 0.0051), myometrial invasion (p = 0.027 and p = 0.031), cervical stromal invasion (p = 0.023 and p = 0.014), ovarian metastasis (p = 0.00022 and p = 0.00034), lymph node metastasis (p < 0.0001 and p < 0.0001), and higher FIGO stage (p = 0.0011 and p = 0.00048). SUVmax was significantly higher in patients with larger tumour size (p = 0.0025), LVSI (p = 0.00023) and myometrial invasion (p < 0.0001). The areas under the ROC curves (AUCs) for distinguishing high-risk from low-risk carcinoma were 0.625, 0.829 and 0.797 for SUVmax, MTV and TLG, respectively. AUCs for both MTV and TLG were significantly larger than that for SUVmax (p = 0.0049 and p = 0.021). The optimal TLG cut-off value of 70.2, determined by ROC analysis, was found to have 72.0% sensitivity and 74.2% specificity for risk stratification.

CONCLUSION

MTV and TLG of primary endometrial cancer show better correlations with clinicopathological features and are more useful for differentiating high-risk from low-risk carcinoma than SUVmax.

Alterations in anatomic and functional imaging parameters with repeated FDG PET-CT and MRI during radiotherapy for head and neck cancer: a pilot study

Background

The use of imaging to implement on-treatment adaptation of radiotherapy is a promising paradigm but current data on imaging changes during radiotherapy is limited. This is a hypothesis-generating pilot study to examine the changes on multi-modality anatomic and functional imaging during (chemo)radiotherapy treatment for head and neck squamous cell carcinoma (HNSCC).

Methods

Eight patients with locally advanced HNSCC underwent imaging including computed tomography (CT), Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)-CT and magnetic resonance imaging (MRI) (including diffusion weighted (DW) and dynamic contrast enhanced (DCE)) at baseline and during (chemo)radiotherapy treatment (after fractions 11 and 21). Regions of interest (ROI) were drawn around the primary tumour at baseline and during treatment. Imaging parameters included gross tumour volume (GTV) assessment, SUV_max, mean ADC value and DCE-MRI parameters including Plasma Flow (PF). On treatment changes and correlations between these parameters were analysed using a Wilcoxon rank sum test and Pearson’s linear correlation coefficient respectively. A p-value <0.05 was considered statistically significant.

Results

Statistically significant reductions in GTV-CT, GTV-MRI and GTV-DW were observed between all imaging timepoints during radiotherapy. Changes in GTV-PET during radiotherapy were heterogeneous and non-significant. Significant changes in SUV_max, mean ADC value, Plasma Flow and Plasma Volume were observed between the baseline and the fraction 11 timepoint, whilst only changes in SUV_max between baseline and the fraction 21 timepoint were statistically significant. Significant correlations were observed between multiple imaging parameters, both anatomical and functional; 20 correlations between baseline to the fraction 11 timepoint; 12 correlations between baseline and the fraction 21 timepoints; and 4 correlations between the fraction 11 and fraction 21 timepoints.

Conclusions

Multi-modality imaging during radiotherapy treatment demonstrates early changes (by fraction 11) in both anatomic and functional imaging parameters. All functional imaging modalities are potentially complementary and should be considered in combination to provide multi-parametric tumour assessment, to guide potential treatment adaptation strategies.

Trial Registration

ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015.

PET image segmentation using a Gaussian mixture model and Markov random fields

Background

Classification algorithms for positron emission tomography (PET) images support computational treatment planning in radiotherapy. Common clinical practice is based on manual delineation and fixed or iterative threshold methods, the latter of which requires regression curves dependent on many parameters.

Methods

An improved statistical approach using a Gaussian mixture model (GMM) is proposed to obtain initial estimates of a target volume, followed by a correction step based on a Markov random field (MRF) and a Gibbs distribution to account for dependencies among neighboring voxels. In order to evaluate the proposed algorithm, phantom measurements of spherical and non-spherical objects with the smallest diameter being 8 mm were performed at signal-to-background ratios (SBRs) between 2.06 and 9.39. Additionally ⁶⁸Ga-PET data from patients with lesions in the liver and lymph nodes were evaluated.

Results

The proposed algorithm produces stable results for different reconstruction algorithms and different lesion shapes. Furthermore, it outperforms all threshold methods regarding detection rate, determines the spheres’ volumes more accurately than fixed threshold methods, and produces similar values as iterative thresholding. In a comparison with other statistical approaches, the algorithm performs equally well for larger volumes and even shows improvements for small volumes and SBRs. The comparison with experts’ manual delineations on the clinical data shows the same qualitative behavior as for the phantom measurements.

Conclusions

In conclusion, a generic probabilistic approach that does not require data measured beforehand is presented whose performance, robustness, and swiftness make it a feasible choice for PET segmentation.

PET imaging biomarkers in head and neck cancer

In locally advanced head and neck squamous cell carcinoma (HNSCC), the role of imaging becomes more and more critical in the management process. In this framework, molecular imaging techniques such as PET allow noninvasive assessment of a range of tumour biomarkers such as metabolism, hypoxia and proliferation, which can serve different purposes. First, in a pretreatment setting they can influence therapy selection strategies and target delineation for radiation therapy. Second, their predictive and/or prognostic value could help enhance the therapeutic ratio in the management of HNSCC. Third, treatment modification can be performed through the generation of a molecular-based heterogeneous dose distribution with dose escalation to the most resistant parts of the tumour, a concept known as dose painting. Fourth, they are increasingly becoming a tool for monitoring response to therapy. In this review, PET imaging biomarkers used in the routine management of HNSCC or under investigation are discussed.

Adaptive threshold segmentation of pituitary adenomas from FDG PET images for radiosurgery

In this study we have attempted to optimize a PET based adaptive threshold seg- mentation method for delineating small tumors, particularly in a background of high tracer activity. The metabolic nature of pituitary adenomas and the constraints of MRI imaging in the postoperative setting to delineate these tumors during radio- surgical procedures motivated us to develop this method. Phantom experiments were done to establish a relationship between the threshold required for segmenting the PET images and the target size and the activity concentration within the target in relation to its background. The threshold was developed from multiple linear regression of the experimental data optimized for tumor sizes less than 4 cm3. We validated our method against the phantom target volumes with measured target to background ratios ranging from 1.6 to 14.58. The method was tested on ten retro- spective patients with residual growth hormone-secreting pituitary adenomas that underwent radiosurgery and compared against the volumes delineated by manual method. The predicted volumes against the true volume of the phantom inserts gave a correlation coefficient of 99% (p &lt; 0.01). In the ten retrospective patients, the automatically segmented tumor volumes against volumes manually delineated by the clinicians had a correlation of 94% (p &lt; 0.01). This adaptive threshold segmentation showed promising results in delineating tumor volumes in pituitary adenomas planned for stereotactic radiosurgery, particularly in the postoperative setting where MR and CT images may be associated with artifacts, provided opti- mization experiment is carried out. 

Impact of PET reconstruction algorithm and threshold on dose painting of non-small cell lung cancer

PURPOSE

In the current work, we investigate the impact of PET reconstruction methods (RMs) and threshold on two types of dose painting (DP) prescription strategies for non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Sixteen patients with NSCLC underwent an 18F-FDG-PET/CT examination prior to radiotherapy. Six different RMs were used. For both a dose painting by contours (DPBC) and a dose painting by numbers (DPBN) strategy, the prescribed radiation dose within the gross tumor volume (GTV) was mapped according to the spatial distribution of standardized uptake values (SUVs). SUVmax and SUVpeak were used for volume thresholding in DPBC and a linear SUV-dose scaling approach was used for DPBN. Deviations from the dose prescription as determined by the standard RM was scored by a quality factor (QF).

RESULTS

For DPBC, the mean difference in thresholded boost volume between RMs was typically within 10%. The difference in dose prescription was systematically lower for thresholding based on SUVpeak (largest mean QF 2.8±2.0%) compared to SUVmax (largest mean QF 3.6±3.0%). For DPBN, the resulting dose prescriptions were less dependent on RM and threshold; the largest mean QFs were 1.3±0.3% both for SUVmax and SUVpeak.

CONCLUSIONS

PET reconstruction algorithms will both influence DPBC and DPBN, although the impact is smaller for DPBN. For some patients, the resulting variations in dose prescriptions may result in clinically different dose distributions. SUVpeak is a more robust thresholding parameter than SUVmax.

Tumor SUVmax Normalized to Liver Uptake on (18)F-FDG PET/CT Predicts the Pathologic Complete Response After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

PURPOSE

This study investigates the feasibility of using (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) to predict the pCR (pathologic complete response) rate after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer.

METHODS

A total of 88 patients with locally advanced rectal cancer were retrospectively analyzed. All patients were treated with NCRT, followed by radical surgery, and (18)F-FDG PET/CT was performed before and after NCRT. For a semiquantitative assessment, a volume of interest was drawn, including the whole tumor region, and the maximum SUV (SUVmax), SUVmax normalized to liver uptake (SLR), SUVmax normalized to blood pool uptake (SBR), the metabolic tumor volume at SUV 2.0 (MTV[2.0]), SUV 2.5 (MTV[2.5]), and SUV 3.0 (MTV[3.0]) were measured. In addition, their percentage changes after NCRT were assessed. The pCR was verified through a histologic examination of postsurgical specimens. A receiver operating characteristic curve analysis was conducted to predict the pCR by using these PET parameters.

RESULTS

The pCR was predicted in 17 patients (19 %). The values of the area under the curve (AUC) for predicting the pCR were 0.774 for SUVmax after NCRT, 0.826 for SLR after NCRT, 0.815 for SBR after NCRT, 0.724 for MTV(2.5) after NCRT, 0.729 for the percentage change in SUVmax, 0.700 for the percentage change in SLR, and 0.749 for the percentage change in MTV (2.5). Among these PET parameters, SLR after NCRT showed the highest AUC value. The optimal criterion, sensitivity, specificity, and accuracy of SLR after NCRT for predicting the pCR were ≤1.41, 88 %, 65 %, and 68 %, respectively.

CONCLUSIONS

F-FDG PET was found to be useful for predicting the pCR after NCRT in patients with locally advanced rectal cancer. Among various PET parameters, SUVmax normalized to liver uptake after NCRT was the best predictor of the pCR.

Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities

Imaging techniques for the characterization and delineation of primary lung tumours and lymph nodes are a prerequisite for adequate radiotherapy. Numerous imaging modalities have been proposed for this purpose, but only computed tomography (CT) and FDG-PET have been implemented in clinical routine. Hypoxia PET, dynamic contrast-enhanced CT (DCE-CT), dual energy CT (DECT) and (functional) magnetic resonance imaging (MRI) hold promise for the future. Besides information on the primary tumour, these techniques can be used for quantification of tissue heterogeneity and response. In the future, treatment strategies may be designed which are based on imaging techniques to optimize individual treatment.

A review on segmentation of positron emission tomography images

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results.

[Target volume segmentation of PET images by an iterative method based on threshold value]

OBJECTIVES

An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition.

MATERIAL AND METHODS

Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients.

RESULTS

The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml.

CONCLUSIONS

The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images.

Molecular PET imaging for biology-guided adaptive radiotherapy of head and neck cancer

Integration of molecular imaging PET techniques into therapy selection strategies and radiation treatment planning for head and neck squamous cell carcinoma (HNSCC) can serve several purposes. First, pre-treatment assessments can steer decisions about radiotherapy modifications or combinations with other modalities. Second, biology-based objective functions can be introduced to the radiation treatment planning process by co-registration of molecular imaging with planning computed tomography (CT) scans. Thus, customized heterogeneous dose distributions can be generated with escalated doses to tumor areas where radiotherapy resistance mechanisms are most prevalent. Third, monitoring of temporal and spatial variations in these radiotherapy resistance mechanisms early during the course of treatment can discriminate responders from non-responders. With such information available shortly after the start of treatment, modifications can be implemented or the radiation treatment plan can be adapted tailing the biological response pattern. Currently, these strategies are in various phases of clinical testing, mostly in single-center studies. Further validation in multicenter set-up is needed. Ultimately, this should result in availability for routine clinical practice requiring stable production and accessibility of tracers, reproducibility and standardization of imaging and analysis methods, as well as general availability of knowledge and expertise. Small studies employing adaptive radiotherapy based on functional dynamics and early response mechanisms demonstrate promising results. In this context, we focus this review on the widely used PET tracer (18)F-FDG and PET tracers depicting hypoxia and proliferation; two well-known radiation resistance mechanisms.

Predictive value of pre-therapy (18)F-FDG PET/CT for the outcome of (18)F-FDG PET-guided radiotherapy in patients with head and neck cancer

PURPOSE

The aim of this study was to evaluate the predictive role of pre-therapy fluorodeoxyglucose (FDG) uptake parameters of primary tumour in head and neck cancer (HNC) patients undergoing intensity-modulated radiotherapy (IMRT) with simultaneous integrated boost (SIB) on FDG-positive volume-positron emission tomography (PET) gross tumour volume (PET-GTV).

METHODS

This retrospective study included 19 patients (15 men and 4 women, mean age 59.2 years, range 23-81 years) diagnosed with HNC between 2005 and 2011. Of 19 patients, 15 (79 %) had stage III-IV. All patients underwent FDG PET/CT before treatment. Metabolic indexes of primary tumour, including metabolic tumour volume (MTV), maximum and mean standardized uptake value (SUVmax, SUVmean) and total lesion glycolysis (TLG) were considered. Partial volume effect correction (PVC) was performed for SUVmean and TLG estimation. Correlations between PET/CT parameters and 2-year disease-free survival (DFS), local recurrence-free survival (LRFS) and distant metastasis-free survival (DMFS) were assessed. Median patient follow-up was 19.2 months (range 4-24 months).

RESULTS

MTV, TLG and PVC-TLG predicting patients' outcome with respect to all the considered local and distant disease control endpoints (LRFS, DMFS and DFS) were 32.4 cc, 469.8 g and 547.3 g, respectively. SUVmean and PVC-SUVmean cut-off values predictive of LRFS and DFS were 10.8 and 13.3, respectively. PVC was able to compensate errors up to 25 % in the primary HNC tumour uptake. Moreover, PVC enhanced the statistical significance of the results.

CONCLUSION

FDG PET/CT uptake parameters are predictors of patients' outcome and can potentially identify patients with higher risk of treatment failure that could benefit from more aggressive approaches. Application of PVC is recommended for accurate measurement of PET parameters.

[Validation of segmentation techniques for positron emission tomography using ex-vivo images of oncological surgical specimens]

OBJECTIVE

To design a novel ex-vivo acquisition technique to establish a common framework to validate different segmentation techniques for oncological PET images. To evaluate several automatic segmentation algorithms on this set of images.

MATERIAL AND METHODS

In 15 patients with cancer, ex-vivo PET studies of surgical specimens removed during surgery were performed after injection of (18)F-FDG. Images were acquired in two scanners: a clinical PET/CT and a high-resolution PET scanner. Real tumor volume was determined in each patient, and a reference image was generated for segmentation of each tumor. Images were segmented with 12 automatic algorithms and with a standard method for PET (relative threshold at 42%) and results were evaluated by quantitative parameters.

RESULTS

It has been possible to demonstrate by segmentation of PET images of surgical specimens that on high resolution PET images, 8 out of 12 evaluated segmentation techniques outperformed the standard method, whose value is 42%. However, none of the algorithms outperformed the standard method when applied on images from the clinical PET/CT. Due to the great interest of this set of PET images, all studies have been published on the Internet in order to provide a common framework for validation and comparison of different segmentation techniques.

CONCLUSIONS

We have proposed a novel technique to validate segmentation techniques for oncological PET images, acquiring ex-vivo PET studies of surgical specimens. We have demonstrated the usefulness of this set of PET images by evaluating several automatic segmentation algorithms.

The reliability of quantitative thresholding methods for PET aided delineation of GTVs in Head and Neck tumours

Introduction: PET–CT scans are commonly used for the purpose of gross tumour volume (GTV) delineation in head and neck cancers. Qualitative visual methods (QVM) are currently employed in most radiotherapy departments but these are subject to inter- and intra-observer variability. Quantitative thresholding methods which appear in the published literature are evaluated with respect to their reliability for delineation of GTVs in head and neck cancers.

Discussion: Image segmentation involves the application of a distinct value to all pixels or voxels in an image dataset. This is a complex process affected by numerous variables. Some of the following segmentation thresholds may be applied to automatically delineate specified regions. Standardised uptake value (SUV) is commonly used to apply a threshold for GTV delineation, however this leads to inappropriately large GTVs. A further common quantitative threshold is based on the maximum signal on the PET image relative to the background uptake, known as signal to background ratio (SBR). This method generates GTVs that correlate well with surgically removed tumour volumes. Applying a fixed threshold of a percentage of the maximal intensity uptake is also documented in the literature but was found to be unsuitable for the purpose of head and neck GTV contouring. Systems based on the physical features of the PET-CT images are also discussed and are found to produce very promising results.

Conclusion: A number of quantitative techniques are evaluated and currently the most suitable is found to be SBR, however even this method was not found to be entirely reliable. More promising techniques need further evaluation before they could be implemented clinically and a Radiation Oncologist or Nuclear Medicine Radiologist must still validate all GTVs produced by quantitative methods.

PET-based delineation of tumour volumes in lung cancer: comparison with pathological findings

PURPOSE

The objective of the study was to validate an adaptive, contrast-oriented thresholding algorithm (COA) for tumour delineation in (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for non-small cell lung cancer (NSCLC) in comparison with pathological findings. The impact of tumour localization, tumour size and uptake heterogeneity on PET delineation results was also investigated.

METHODS

PET tumour delineation by COA was compared with both CT delineation and pathological findings in 15 patients to investigate its validity. Correlations between anatomical volume, metabolic volume and the pathology reference as well as between the corresponding maximal diameters were determined. Differences between PET delineations and pathological results were investigated with respect to tumour localization and uptake heterogeneity.

RESULTS

The delineated volumes and maximal diameters measured on PET and CT images significantly correlated with the pathology reference (both r > 0.95, p < 0.0001). Both PET and CT contours resulted in overestimation of the pathological volume (PET 32.5 ± 26.5%, CT 46.6 ± 27.4%). CT volumes were larger than those delineated on PET images (CT 60.6 ± 86.3 ml, PET 48.3 ± 61.7 ml). Maximal tumour diameters were similar for PET and CT (51.4 ± 19.8 mm for CT versus 53.4 ± 19.1 mm for PET), slightly overestimating the pathological reference (mean difference CT 4.3 ± 3.2 mm, PET 6.2 ± 5.1 mm). PET volumes of lung tumours located in the lower lobe were significantly different from those determined from pathology (p = 0.037), whereas no significant differences were observed for tumours located in the upper lobe (p = 0.066). Only minor correlation was found between pathological tumour size and PET heterogeneity (r = -0.24).

CONCLUSION

PET tumour delineation by COA showed a good correlation with pathological findings. Tumour localization had an influence on PET delineation results. The impact of tracer uptake heterogeneity on PET delineation should be considered carefully and individually in each patient. Altogether, PET tumour delineation by COA for NSCLC patients is feasible and reliable with the potential for routine clinical application.

Dynamic Target Definition: a novel approach for PTV definition in ion beam therapy

PURPOSE

To present a beam arrangement specific approach for PTV definition in ion beam therapy.

MATERIALS AND METHODS

By means of a Monte Carlo error propagation analysis a criteria is formulated to assess whether a voxel is safely treated. Based on this a non-isotropical expansion rule is proposed aiming to minimize the impact of uncertainties on the dose delivered.

RESULTS

The method is exemplified in two cases: a Head and Neck case and a Prostate case. In both cases the modality used is proton beam irradiation and the sources of uncertainties taken into account are positioning (set up) errors and range uncertainties. It is shown how different beam arrangements have an impact on plan robustness which leads to different target expansions necessary to assure a predefined level of plan robustness. The relevance of appropriate beam angle arrangements as a way to minimize uncertainties is demonstrated.

CONCLUSIONS

A novel method for PTV definition in on beam therapy is presented. The method show promising results by improving the probability of correct dose CTV coverage while reducing the size of the PTV volume. In a clinical scenario this translates into an enhanced tumor control probability while reducing the volume of healthy tissue being irradiated.

Application of FDG-PET/CT in Radiation Oncology

Positron emission tomography (PET)/computed tomography (CT), which combines the advantages of high sensitivity and specificity of PET and high resolution of CT, is a unique tool for cancer management. PET/CT has been widely used in cancer diagnosis and treatment. The article reviews the recent applications of PET/CT in radiation oncology, with a focus on ¹⁸F-fluorodeoxyglucose (FDG)-PET/CT, addressing the applications in treatment planning and treatment response assessment of radiation therapy.

Fifteen different 18F-FDG PET/CT qualitative and quantitative parameters investigated as pathological response predictors of locally advanced rectal cancer treated by neoadjuvant chemoradiation therapy

PURPOSE

The aim of this study was to correlate qualitative visual response and various PET quantification factors with the tumour regression grade (TRG) classification of pathological response to neoadjuvant chemoradiotherapy (CRT) proposed by Mandard.

METHODS

Included in this retrospective study were 69 consecutive patients with locally advanced rectal cancer (LARC). FDG PET/CT scans were performed at staging and after CRT (mean 6.7 weeks). Tumour SUVmax and its related arithmetic and percentage decrease (response index, RI) were calculated. Qualitative analysis was performed by visual response assessment (VRA), PERCIST 1.0 and response cut-off classification based on a new definition of residual disease. Metabolic tumour volume (MTV) was calculated using a 40 % SUVmax threshold, and the total lesion glycolysis (TLG) both before and after CRT and their arithmetic and percentage change were also calculated. We split the patients into responders (TRG 1 or 2) and nonresponders (TRG 3-5).

RESULTS

SUVmax MTV and TLG after CRT, RI, ΔMTV% and ΔTLG% parameters were significantly correlated with pathological treatment response (p < 0.01) with a ROC curve cut-off values of 5.1, 2.1 cm(3), 23.4 cm(3), 61.8 %, 81.4 % and 94.2 %, respectively. SUVmax after CRT had the highest ROC AUC (0.846), with a sensitivity of 86 % and a specificity of 80 %. VRA and response cut-off classification were also significantly predictive of TRG response (VRA with the best accuracy: sensitivity 86 % and specificity 55 %). In contrast, assessment using PERCIST was not significantly correlated with TRG.

CONCLUSION

FDG PET/CT can accurately stratify patients with LARC preoperatively, independently of the method chosen to interpret the images. Among many PET parameters, some of which are not immediately obtainable, the most commonly used in clinical practice (SUVmax after CRT and VRA) showed the best accuracy in predicting TRG.

FDG-PET and diffusion-weighted MRI in head-and-neck cancer patients: implications for dose painting

PURPOSE

The purpose of this study was to investigate if FDG-PET and DWI identify the same or different targets for dose escalation in the GTV of HN cancer patients. Additionally, the dose coverage of DWI-targets in an FDG-PET-based dose painting plan was analyzed.

MATERIALS AND METHODS

Eighteen HN cancer patients underwent FDG-PET and DWI exams, which were converted to standardized uptake value (SUV)- and apparent diffusion coefficient (ADC)-maps. The correspondence between the two imaging modalities was determined on a voxel-level using Spearman's correlation coefficient (ρ). Dose painting plans were optimized based on the 50% isocontour of the maximum SUV ( SUV(50%max)). Dose coverage was analyzed in three different SUV- and three different ADC-targets using the mean dose and the near-minimum and near-maximum doses.

RESULTS

The average maximum SUV was 13.9 and the mean ADC was 1.17 · 10(-3) mm(2)/s. The average ρ between SUV and ADC was -0.2 (range: -0.6 to 0.4). The ADC-targets were only partly overlapping the SUV(50%max)-target and the dose parameters were significantly smaller in the ADC-targets compared to the SUV(50%max)-target.

CONCLUSIONS

FDG-PET and DWI contain different information, resulting in different targets. Further information about failure patterns and dose relations can be obtained by adding DWI to currently ongoing dose painting trials.

Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on (18)F-FDG PET-CT for radiotherapy treatment planning

Positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process.

A semiautomatic CT-based ensemble segmentation of lung tumors: comparison with oncologists' delineations and with the surgical specimen

PURPOSE

To assess the clinical relevance of a semiautomatic CT-based ensemble segmentation method, by comparing it to pathology and to CT/PET manual delineations by five independent radiation oncologists in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

For 20 NSCLC patients (stages Ib-IIIb) the primary tumor was delineated manually on CT/PET scans by five independent radiation oncologists and segmented using a CT based semi-automatic tool. Tumor volume and overlap fractions between manual and semiautomatic-segmented volumes were compared. All measurements were correlated with the maximal diameter on macroscopic examination of the surgical specimen. Imaging data are available on www.cancerdata.org.

RESULTS

High overlap fractions were observed between the semi-automatically segmented volumes and the intersection (92.5±9.0, mean±SD) and union (94.2±6.8) of the manual delineations. No statistically significant differences in tumor volume were observed between the semiautomatic segmentation (71.4±83.2 cm(3), mean±SD) and manual delineations (81.9±94.1 cm(3); p=0.57). The maximal tumor diameter of the semiautomatic-segmented tumor correlated strongly with the macroscopic diameter of the primary tumor (r=0.96).

CONCLUSIONS

Semiautomatic segmentation of the primary tumor on CT demonstrated high agreement with CT/PET manual delineations and strongly correlated with the macroscopic diameter considered as the "gold standard". This method may be used routinely in clinical practice and could be employed as a starting point for treatment planning, target definition in multi-center clinical trials or for high throughput data mining research. This method is particularly suitable for peripherally located tumors.

Comparative study with new accuracy metrics for target volume contouring in PET image guided radiation therapy

The impact of PET on radiation therapy is held back by poor methods of defining functional volumes of interest. Many new software tools are being proposed for contouring target volumes but the different approaches are not adequately compared and their accuracy is poorly evaluated due to the illdefinition of ground truth. This paper compares the largest cohort to date of established, emerging and proposed PET contouring methods, in terms of accuracy and variability. We emphasise spatial accuracy and present a new metric that addresses the lack of unique ground truth. 30 methods are used at 13 different institutions to contour functional VOIs in clinical PET/CT and a custom-built PET phantom representing typical problems in image guided radiotherapy. Contouring methods are grouped according to algorithmic type, level of interactivity and how they exploit structural information in hybrid images. Experiments reveal benefits of high levels of user interaction, as well as simultaneous visualisation of CT images and PET gradients to guide interactive procedures. Method-wise evaluation identifies the danger of over-automation and the value of prior knowledge built into an algorithm.

Exploratory prospective trial of hypoxia-specific PET imaging during radiochemotherapy in patients with locally advanced head-and-neck cancer

PURPOSE

To explore in a prospective trial the prognostic value of hypoxia imaging before and during radiochemotherapy in patients with locally advanced head and neck cancer.

PATIENTS AND METHODS

Twenty-five patients with stage III/IV head and neck cancer were investigated with [(18)F]-fluoromisonidazole (FMISO) PET/CT at four time points during radiochemotherapy (baseline, 8-10 Gy, 18-20 Gy,50-60 Gy). FMISO PET/CT image parameters were extracted including maximum-tumour-to-background (TBR(max)) and thresholded volume at different TBR ratios. CT volume and baseline FDG-PET/CT image parameters were also included. Parameters at all time points were investigated for their prognostic value with the local-progression-free-survival endpoint (LPFS). Significance was evaluated with multivariate Cox (including clinical parameters) and Log-rank tests.

RESULTS

FMISO-image parameters were found to have a strong association with the LPFS endpoint, and were strongest at the week 1 and 2 time points (p = 0.023-0.048 and 0.042-0.061 respectively on multivariate Cox). Parameters measured at baseline were only significant on univariate analysis. None of the clinical parameters, and also FDG- or CT-delineated volumes, were significantly associated with LPFS.

CONCLUSION

This prospective, exploratory study demonstrated that FMISO-PET/CT imaging during the initial phase of treatment carries strong prognostic value. FMISO-PET/CT imaging at 1 or 2 weeks during treatment could be promising way to select patients that would benefit from hypoxia modification or dose-escalated treatment. A validation study is on-going.

Endometrial recurrence in the proximal vagina: brachytherapy volume delineation with 18FDG PET-CT

Background: Endometrial cancer vaginal recurrence in a patient deemed unsuitable for EBRT. Brachytherapy proposed although standard image-guidance insufficient.

Proposed Solution: PET-CT image-guidance.

Results: PET-CT acquired with brachytherapy applicator in situ. BTV delineated by the Nuclear Medicine physician. All subsequent volumes delineated by the Clinical Oncologist. 2 phase plan delivered with minimal toxicity.

Response assessment using 18F-FDG PET early in the course of radiotherapy correlates with survival in advanced-stage non-small cell lung cancer

This study investigated the possibility of early response assessment based on (18)F-FDG uptake during radiotherapy with respect to overall survival in patients with non-small cell lung cancer.

METHODS

(18)F-FDG PET/CT was performed before radiotherapy and was repeated in the second week of radiotherapy for 34 consecutive lung cancer patients. The CT volume and standardized uptake value (SUV) parameters of the primary tumor were quantified at both time points. Changes in volume and SUV parameters correlated with 2-y overall survival.

RESULTS

The average change in mean SUV in the primary tumor of patients with a 2-y survival was a decrease by 20% ± 21%-significantly different (P < 0.007) from nonsurvivors, who had an increase by 2% ± 22%. A sensitivity and specificity of 63% and 93%, respectively, to separate the 2 groups was reached for a decrease in mean SUV of 15%. Survival curves were significantly different using this cutoff (P = 0.001). The hazard ratio for a 1% decrease in mean SUV was 1.032 (95% confidence interval, 1.010-1.055). Changes in tumor volume defined on CT did not correlate with overall survival.

CONCLUSION

The use of repeated (18)F-FDG PET to assess treatment response early during radiotherapy is possible in patients undergoing radiotherapy or sequential or concurrent chemoradiotherapy. A decrease in (18)F-FDG uptake by the primary tumor correlates with higher long-term overall survival.

Gaussian process models of dynamic PET for functional volume definition in radiation oncology

In routine oncologic positron emission tomography (PET), dynamic information is discarded by time-averaging the signal to produce static images of the "standardised uptake value" (SUV). Defining functional volumes of interest (VOIs) in terms of SUV is flawed, as values are affected by confounding factors and the chosen time window, and SUV images are not sensitive to functional heterogeneity of pathological tissues. Also, SUV iso-contours are highly affected by the choice of threshold and no threshold, or other SUV-based segmentation method, is universally accepted for a given VOI type. Gaussian Process (GP) time series models describe macro-scale dynamic behavior arising from countless interacting micro-scale processes, as is the case for PET signals from heterogeneous tissue. We use GPs to model time-activity curves (TACs) from dynamic PET and to define functional volumes for PET oncology. Probabilistic methods of tissue discrimination are presented along with novel contouring methods for functional VOI segmentation. We demonstrate the value of GP models for voxel classification and VOI contouring of diseased and metastatic tissues with functional heterogeneity in prostate PET. Classification experiments reveal superior sensitivity and specificity over SUV calculation and a TAC-based method proposed in recent literature. Contouring experiments reveal differences in shape between gold-standard and GP VOIs and correlation with kinetic models shows that the novel VOIs contain extra clinically relevant information compared to SUVs alone. We conclude that the proposed models offer a principled data analysis technique that improves on SUVs for oncologic VOI definition. Continuing research will generalize GP models for different oncology tracers and imaging protocols with the ultimate goal of clinical use including treatment planning.