Revisiting the identification of tumor sub-volumes predictive of residual uptake after (chemo)radiotherapy: influence of segmentation methods on 18F-FDG PET/CT images.
ABSTRACT: Our aim was to evaluate the impact of the accuracy of image segmentation techniques on establishing an overlap between pre-treatment and post-treatment functional tumour volumes in 18FDG-PET/CT imaging. Simulated images and a clinical cohort were considered. Three different configurations (large, small or non-existent overlap) of a single simulated example was used to elucidate the behaviour of each approach. Fifty-four oesophageal and head and neck (H&N) cancer patients treated with radiochemotherapy with both pre- and post-treatment PET/CT scans were retrospectively analysed. Images were registered and volumes were determined using combinations of thresholds and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Four overlap metrics were calculated. The simulations showed that thresholds lead to biased overlap estimation and that accurate metrics are obtained despite spatially inaccurate volumes. In the clinical dataset, only 17 patients exhibited residual uptake smaller than the pre-treatment volume. Overlaps obtained with FLAB were consistently moderate for esophageal and low for H&N cases across all metrics. Overlaps obtained using threshold combinations varied greatly depending on thresholds and metrics. In both cases overlaps were variable across patients. Our findings do not support optimisation of radiotherapy planning based on pre-treatment 18FDG-PET/CT image definition of high-uptake sub-volumes. Combinations of thresholds may have led to overestimation of overlaps in previous studies.
Project description:Introduction: Locally advanced cervical cancer (CC) patients treated by chemoradiotherapy (CRT) have a significant local recurrence rate. The objective of this work was to assess the overlap between the initial high-uptake sub-volume (V1) on baseline 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scans and the metabolic relapse (V2) sites after CRT in locally advanced CC. Methods: PET/CT performed before treatment and at relapse in 21 patients diagnosed with LACC and treated with CRT were retrospectively analyzed. CT images at the time of recurrence were registered to baseline CT using the 3D Slicer TM Expert Automated Registration module. The corresponding PET images were then registered using the corresponding transform. The fuzzy locally adaptive Bayesian (FLAB) algorithm was implemented using 3 classes (one for the background and the other two for tumor) in PET1 to simultaneously define an overall tumor volume and the sub-volume V1. In PET2, FLAB was implemented using 2 classes (one for background, one for tumor), in order to define V2. Four indices were used to determine the overlap between V1 and V2 (Dice coefficients, overlap fraction, X = (V1nV2)/V1 and Y = (V1nV2)/V2). Results: The mean (±standard deviation) follow-up was 26 ± 11 months. The measured overlaps between V1 and V2 were moderate to good according to the four metrics, with 0.62-0.81 (0.72 ± 0.05), 0.72-1.00 (0.85 ± 0.10), 0.55-1.00 (0.73 ± 0.16) and 0.50-1.00 (0.76 ± 0.12) for Dice, overlap fraction, X and Y, respectively. Conclusion: In our study, the overlaps between the initial high-uptake sub-volume and the recurrent metabolic volume showed moderate to good concordance. These results now need to be confirmed in a larger cohort using a more standardized patient repositioning procedure for sequential PET/CT imaging, as there is potential for RT dose escalation exploiting the pre-treatment PET high-uptake sub-volume.
Project description:Positron emission tomography (PET) of lung tumors suffers from breathing-motion induced blurring. Respiratory-correlated PET ameliorates motion blurring and enables visualization of lung tumor functional uptake throughout the breathing cycle but has achieved limited clinical use in radiotherapy planning. In this work, the authors propose a process for generating a gated PET maximum intensity projection (MIP), a breathing-phase projection of the 4D image set comprising gated PET images, as a technique to quantitatively and efficiently incorporate respiratory-correlated PET information into radiotherapy treatment planning.4D-CT and respiratory-gated PET using [(18)F]fluorodeoxyglucose (FDG) were acquired of three patients with a total of four small (4-18 cc), clearly defined lower-lobe lung tumors. Internal target volumes (ITVs) for the lung tumors were generated by threshold-based segmentation of PET-MIP images and ungated PET images (ITV(PET-MIP) and ITV(3D-PET), respectively), and by manual contouring of CT-MIP and end-exhale and end-inhale phases of 4D-CT (ITV(CT-MIP)) by a radiation oncologist. Because of the sensitivity of tumor segmentation to threshold value, several different thresholds were tested for ITV generation, including 40%, 30%, and 20% of maximum standardized uptake value (SUV(max)) for FDG as well as absolute SUV thresholds of 2.5 and 3.0. The normalized overlap and relative volumes of ITV(PET-MIP) and ITV(3D-PET) with respect to ITV(CT-MIP) were compared. The images were also visually compared. ITV(CT-MIP) was considered a gold standard for these tumors with CT-visible morphology.The mean and standard deviation normalized overlap and relative volumes between ITV(PET-MIP) and ITV(CT-MIP) were 0.68 ± 0.07 and 1.07 ± 0.42, respectively, averaged over all four tumors and all five threshold values. The mean and standard deviation normalized overlap and relative volumes of ITV(3D-PET) and ITV(CT-MIP) were 0.47 ± 0.12 and 0.69 ± 0.56, respectively.PET-MIP images better match CT-MIP images for this sample of four small CT-visible tumors as compared to ungated PET images, based on the metrics of volumetric overlap and relative volumes as well as visual interpretation. The PET-MIP is a way to incorporate 4D-PET imaging into the process of lung tumor contouring that is time-efficient for the radiation oncologist and involves minimal effort to implement in treatment planning software, because it requires only a single PET image beyond contouring on CT alone.
Project description:<h4>Purpose</h4>Head and neck cancers radiotherapy (RT) is associated with inevitable injury to parotid glands and subsequent xerostomia. We investigated the utility of SUV derived from <sup>18</sup>FDG-PET to develop metabolic imaging biomarkers (MIBs) of RT-related parotid injury.<h4>Methods</h4>Data for oropharyngeal cancer (OPC) patients treated with RT at our institution between 2005 and 2015 with available planning computed tomography (CT), dose grid, pre- & first post-RT <sup>18</sup>FDG-PET-CT scans, and physician-reported xerostomia assessment at 3-6 months post-RT (Xero 3-6 ms) per CTCAE, was retrieved, following an IRB approval. A CT-CT deformable image co-registration followed by voxel-by-voxel resampling of pre & post-RT <sup>18</sup>FDG activity and dose grid were performed. Ipsilateral (Ipsi) and contralateral (contra) parotid glands were sub-segmented based on the received dose in 5 Gy increments, i.e. 0-5 Gy, 5-10 Gy sub-volumes, etc. Median and dose-weighted SUV were extracted from whole parotid volumes and sub-volumes on pre- & post-RT PET scans, using in-house code that runs on MATLAB. Wilcoxon signed-rank and Kruskal-Wallis tests were used to test differences pre- and post-RT.<h4>Results</h4>432 parotid glands, belonging to 108 OPC patients treated with RT, were sub-segmented & analyzed. Xero 3-6 ms was reported as: non-severe (78.7%) and severe (21.3%). SUV- median values were significantly reduced post-RT, irrespective of laterality (p = 0.02). A similar pattern was observed in parotid sub-volumes, especially ipsi parotid gland sub-volumes receiving doses 10-50 Gy (p < 0.05). Kruskal-Wallis test showed a significantly higher mean RT dose in the contra parotid in the patients with more severe Xero 3-6mo (p = 0.03). Multiple logistic regression showed a combined clinical-dosimetric-metabolic imaging model could predict the severity of Xero 3-6mo; AUC = 0.78 (95%CI: 0.66-0.85; p < 0.0001).<h4>Conclusion</h4>We sought to quantify pre- and post-RT <sup>18</sup>FDG-PET metrics of parotid glands in patients with OPC. Temporal dynamics of PET-derived metrics can potentially serve as MIBs of RT-related xerostomia in concert with clinical and dosimetric variables.
Project description:BACKGROUND:To identify the radio-resistant subvolumes in pretreatment FDG-PET by mapping the spatial location of the origin of tumor recurrence after IMRT for head-and-neck squamous cell cancer to the pretreatment FDG-PET/CT. METHODS:Patients with local/regional recurrence after IMRT with available FDG-PET/CT and post-failure CT were included. For each patient, both pre-therapy PET/CT and recurrence CT were co-registered with the planning CT (pCT). A 4-mm radius was added to the centroid of mapped recurrence growth target volumes (rGTV's) to create recurrence nidus-volumes (NVs). The overlap between boost-tumor-volumes (BTV) representing different SUV thresholds/margins combinations and NVs was measured. RESULTS:Forty-seven patients were eligible. Forty-two (89.4%) had type A central high dose failure. Twenty-six (48%) of type A rGTVs were at the primary site and 28 (52%) were at the nodal site. The mean dose of type A rGTVs was 71Gy. BTV consisting of 50% of the maximum SUV plus 10mm margin was the best subvolume for dose boosting due to high coverage of primary site NVs (92.3%), low average relative volume to CTV1 (41%), and least average percent voxels outside CTV1 (19%). CONCLUSIONS:The majority of loco-regional recurrences originate in the regions of central-high-dose. When correlated with pretreatment FDG-PET, the majority of recurrences originated in an area that would be covered by additional 10mm margin on the volume of 50% of the maximum FDG uptake.
Project description:<h4>Background and purpose</h4>Diffusion weighted (DW) MRI may facilitate target volume delineation for head-and-neck (HN) radiation treatment planning. In this study we assessed the use of a dedicated, geometrically accurate, DW-MRI sequence for target volume delineation. The delineations were compared with semi-automatic segmentations on <sup>18</sup>F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images and evaluated for interobserver variation.<h4>Methods and materials</h4>Fifteen HN cancer patients underwent both DW-MRI and FDG-PET for RT treatment planning. Target delineation on DW-MRI was performed by three observers, while for PET a semi-automatic segmentation was performed using a Gaussian mixture model. For interobserver variation and intermodality variation, volumes, overlap metrics and Hausdorff distances were calculated from the delineations.<h4>Results</h4>The median volumes delineated by the three observers on DW-MRI were 10.8, 10.5 and 9.0?cm<sup>3</sup> respectively, and was larger than the median PET volume (8.0?cm<sup>3</sup>). The median conformity index of DW-MRI for interobserver variation was 0.73 (range 0.38-0.80). Compared to PET, the delineations on DW-MRI by the three observers showed a median dice similarity coefficient of 0.71, 0.69 and 0.72 respectively. The mean Hausdorff distance was small with median (range) distances between PET and DW-MRI of 2.3 (1.5-6.8), 2.5 (1.6-6.9) and 2.0 (1.35-7.6) mm respectively. Over all patients, the median 95th percentile distances were 6.0 (3.0-13.4), 6.6 (4.0-24.0) and 5.3 (3.4-26.0)?mm.<h4>Conclusion</h4>Using a dedicated DW-MRI sequence, target volumes could be defined with good interobserver agreement and a good overlap with PET. Target volume delineation using DW-MRI is promising in head-and-neck radiotherapy, combined with other modalities, it can lead to more precise target volume delineation.
Project description:<h4>Objectives</h4>This study assessed 5 frequently applied arterial <sup>18</sup>fluorodeoxyglucose (<sup>18</sup>F-FDG) uptake metrics in healthy control subjects, those with risk factors and patients with cardiovascular disease (CVD), to derive uptake thresholds in each subject group. Additionally, we tested the reproducibility of these measures and produced recommended sample sizes for interventional drug studies.<h4>Background</h4><sup>18</sup>F-FDG positron emission tomography (PET) can identify plaque inflammation as a surrogate endpoint for vascular interventional drug trials. However, an overview of <sup>18</sup>F-FDG uptake metrics, threshold values, and reproducibility in healthy compared with diseased subjects is not available.<h4>Methods</h4><sup>18</sup>F-FDG PET/CT of the carotid arteries and ascending aorta was performed in 83 subjects (61 ± 8 years) comprising 3 groups: 25 healthy controls, 23 patients at increased CVD risk, and 35 patients with known CVD. We quantified <sup>18</sup>F-FDG uptake across the whole artery, the most-diseased segment, and within all active segments over several pre-defined cutoffs. We report these data with and without background corrections. Finally, we determined measurement reproducibility and recommended sample sizes for future drug studies based on these results.<h4>Results</h4>All <sup>18</sup>F-FDG uptake metrics were significantly different between healthy and diseased subjects for both the carotids and aorta. Thresholds of physiological <sup>18</sup>F-FDG uptake were derived from healthy controls using the 90th percentile of their target to background ratio (TBR) value (TBR<sub>max</sub>); whole artery TBR<sub>max</sub> is 1.84 for the carotids and 2.68 in the aorta. These were exceeded by >52% of risk factor patients and >67% of CVD patients. Reproducibility was excellent in all study groups (intraclass correlation coefficient >0.95). Using carotid TBR<sub>max</sub> as a primary endpoint resulted in sample size estimates approximately 20% lower than aorta.<h4>Conclusions</h4>We report thresholds for physiological <sup>18</sup>F-FDG uptake in the arterial wall in healthy subjects, which are exceeded by the majority of CVD patients. This remains true, independent of readout vessel, signal quantification method, or the use of background correction. We also confirm the high reproducibility of <sup>18</sup>F-FDG PET measures of inflammation. Nevertheless, because of overlap between subject categories and the relatively small population studied, these data have limited generalizability until substantiated in larger, prospective event-driven studies. (Vascular Inflammation in Patients at Risk for Atherosclerotic Disease; NTR5006).
Project description:<h4>Background and purpose</h4>Prognosis of locally advanced non-small cell lung cancer remains poor despite chemoradiation. This planning study evaluated a stereotactic boost after concurrent chemoradiotherapy (30?×?2?Gy) to improve local control. The maximum achievable boost directed to radioresistant primary tumor subvolumes based on pre-treatment fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (<sup>18</sup>F-FDG-PET/CT) (pre-treatment-PET) and on early response monitoring <sup>18</sup>F-FDG-PET/CT (ERM-PET) was compared.<h4>Materials and methods</h4>For ten patients, a stereotactic boost (VMAT) was planned on ERM-PET (PTV<sub>boost;ERM</sub>) and on pre-treatment-PET (PTV<sub>boost;pre-treatment</sub>), using a 70% SUV<sub>max</sub> threshold with 7?mm margin to segmentate radioresistant subvolumes. Dose was escalated till organ at risk (OAR) constraints were met, aiming to plan at least 18?Gy in 3 fractions (EQD<sub>2</sub> 84?Gy/BED 100.8?Gy).<h4>Results</h4>In five patients, PTV<sub>boost;ERM</sub> was 9-40% smaller relative to PTV<sub>boost;pre-treatment</sub>. Overlap of PTV<sub>boost;ERM</sub> with OARs decreased also compared to overlap of PTV<sub>boost;pre-treatment</sub> with OARs. However, any overlap with OAR remained in 4/5 patients resulting in minimal differences between planned dose before and during treatment. Median dose (EQD<sub>2</sub>) covering 99% and 95% of PTV<sub>boost;ERM</sub> were 15?Gy and 18?Gy respectively. Median boost volume receiving a physical dose of? ??18?Gy (V18) was 88%. V18 was???80% for PTV<sub>boost</sub> in six patients.<h4>Conclusions</h4>A significant stereotactic boost to volumes with high initial or persistent <sup>18</sup>F-FDG-uptake could be planned above 60?Gy chemoradiation. Differences between planned dose before and during treatment were minimal. However, as an ERM-PET also monitors changes in tumor position, we recommend to plan the boost on the ERM-PET.
Project description:<h4>Purpose</h4>Quantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [<sup>18</sup>F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features.<h4>Methods</h4>In a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [<sup>18</sup>F]DCFPyL PET-CT. Primary tumors were delineated using 50-70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ??8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC.<h4>Results</h4>The radiomics-based machine learning models predicted LNI (AUC 0.86?±?0.15, p <?0.01), nodal or distant metastasis (AUC 0.86?±?0.14, p <?0.01), Gleason score (0.81?±?0.16, p <?0.01), and ECE (0.76?±?0.12, p <?0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance.<h4>Conclusion</h4>Machine learning-based analysis of quantitative [<sup>18</sup>F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice.
Project description:BACKGROUND:The best method of identifying regions within pancreatic tumours that might benefit from an increased radiotherapy dose is not known. We investigated the utility of pre-treatment FDG-PET in predicting the spatial distribution of residual metabolic activity following chemoradiotherapy (CRT) in locally advanced pancreatic cancer (LAPC). METHODS:17 patients had FDG-PET/CT scans at baseline and six weeks post-CRT. Tumour segmentation was performed at 40% and 50% of SUVmax at baseline and 60%, 70%, 80% and 90% post-CRT. FDG-PET scans were non-rigidly registered to the radiotherapy planning CT using the CT component of the FDG-PET/CT. Percentage overlap of the post-CRT volumes with the pre-CRT volumes with one another and the gross tumour volume (GTV) was calculated. RESULTS:SUVmax decreased during CRT (median pre- 8.0 and post- 3.6, p?<?0.0001). For spatial correlation analysis, 9 pairs of scans were included (Four were excluded following complete metabolic response, one patient had a non-FDG avid tumour, one had no post-CRT imaging, one had diffuse FDG uptake that could not be separated from normal tissues and one had an elevated blood glucose). The Pre40% and 50% of SUVmax volumes covered a mean of 50.8% and 30.3% of the GTV respectively. The mean% overlap of the 90%, 80%, 70%, 60% of SUVmax post-CRT with the Pre40% and Pre50% volumes were 83.3%, 84.0%, 83.7%, 77.9% and 77.8%, 69.9%, 74.5%, 64.8% respectively. CONCLUSIONS:Regions of residual metabolic activity following CRT can be predicted from the baseline FDG-PET and could aid definition of a biological target volume for non-uniform dose prescriptions.
Project description:<h4>Purpose</h4>Hypoxia is a major factor in prostate cancer aggressiveness and radioresistance. Predicting which patients might be bad candidates for radiotherapy may help better personalize treatment decisions in intermediate-risk prostate cancer patients. We assessed spatial distribution of <sup>18</sup>F-Misonidazole (FMISO) PET/CT uptake in the prostate prior to radiotherapy treatment.<h4>Materials and methods</h4>Intermediate-risk prostate cancer patients about to receive high-dose (>74 Gy) radiotherapy to the prostate without hormonal treatment were prospectively recruited between 9/2012 and 10/2014. Prior to radiotherapy, all patients underwent a FMISO PET/CT as well as a MRI and <sup>18</sup>F-choline-PET. <sup>18</sup>F-choline and FMISO-positive volumes were semi-automatically determined using the fuzzy locally adaptive Bayesian (FLAB) method. In FMISO-positive patients, a dynamic analysis of early tumor uptake was performed. Group differences were assessed using the Wilcoxon signed rank test. Parameters were correlated using Spearman rank correlation.<h4>Results</h4>Of 27 patients (median age 76) recruited to the study, 7 and 9 patients were considered positive at 2.5h and 3.5h FMISO PET/CT respectively. Median SUV<sub>max</sub> and SUV<sub>max</sub> tumor to muscle (T/M) ratio were respectively 3.4 and 3.6 at 2.5h, and 3.2 and 4.4 at 3.5h. The median FMISO-positive volume was 1.1 ml.<h4>Conclusions</h4>This is the first study regarding hypoxia imaging using FMISO in prostate cancer showing that a small FMISO-positive volume was detected in one third of intermediate-risk prostate cancer patients.