The dose distribution in dominant intraprostatic tumour lesions defined by multiparametric MRI and PSMA PET/CT correlates with the outcome in patients treated with primary radiation therapy for prostate cancer.
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ABSTRACT:
SUBMITTER: Zamboglou C
PROVIDER: S-EPMC5898009 | biostudies-literature | 2018 Apr
REPOSITORIES: biostudies-literature
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The dose distribution in dominant intraprostatic tumour lesions defined by multiparametric MRI and PSMA PET/CT correlates with the outcome in patients treated with primary radiation therapy for prostate cancer.
Zamboglou Constantinos C Klein Christina Marie CM Thomann Benedikt B Fassbender Thomas Franz TF Rischke Hans C HC Kirste Simon S Henne Karl K Volegova-Neher Natalja N Bock Michael M Langer Mathias M Meyer Philipp T PT Baltas Dimos D Grosu Anca L AL
Radiation oncology (London, England) 20180412 1
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Project description:BackgroundBiology-guided radiotherapy (BgRT) delivers dose to tumours triggered from positron emission tomography (PET) detection. Prostate specific membrane antigen (PSMA) PET uptake is abundant in the dominant intraprostatic lesion (DIL). This study investigates the feasibility of BgRT to PSMA-avid subvolume in the prostate region.MethodsPatients enrolled in the prospective randomized trial ProPSMA at our institution were included (ID: ANZCTR12617000005358). Gross tumour volumes (GTVs) were delineated on the PET component of a PET/CT scan from a standardized uptake value (SUV) threshold technique. Suitability for BgRT requires a strong signal-to-background ratio with a surrounding tissue free of significant PSMA uptake. The signal-to-background ratio was quantified from the calculation of the normalized SUV (nSUV), defined as the ratio between SUVmax within the GTV and SUVmean inside a 3D margin expansion of the GTV. The PSMA distribution surrounding the tumour was quantified as a function of the distance from the GTV.ResultsIn this cohort of 84 patients, 83 primary tumours were included. Prostate volume ranged from 19 cm3 to 148 cm3 (median = 52 cm3; IQR = 39 cm3 - 63 cm3). SUVmax inside the prostate was between 2 and 125 (median = 19; IQR = 11 - 30). More than 50% of GTVs generated with threshold between 25%SUVmax (median volume = 10.0 cm3; IQR = 4.5 cm3 - 20.0 cm3) and 50%SUVmax (median volume = 1.9 cm3; IQR = 1.1 cm3 - 3.8 cm3) were suitable for BgRT by using nSUV ≥ 3 and a margin expansion of 5 mm.ConclusionsIt is feasible to identify GTVs suitable for BgRT in the prostate. These GTVs are characterized by a strong signal-to-background ratio and a surrounding tissue free of PSMA uptake.
| S-EPMC9156937 | biostudies-literature
Project description:PurposeProstate cancer is multifocal. However, there often exists a single dominant focus in the gland responsible for driving the biology of the disease. Dose escalation to the dominant lesion is a proposed strategy to increase tumor control. We applied radiobiological modeling to evaluate the dosimetric feasibility and benefit of dominant intraprostatic lesion simultaneous in-field boosts (DIL-SIB) to the gross tumor volume (GTV), defined using a novel molecular positron emission tomography (PET) probe (18F-DCFPyL) directed against prostate specific membrane antigen (PSMA).Methods and materialsPatients with clinically localized, biopsy-proven prostate cancer underwent preoperative [18F]-DCFPyL PET/computed tomography (CT). DIL-SIB plans were generated by importing the PET/CT into the RayStation treatment planning system. GTV-PET for the DIL-SIB was defined by the highest %SUVmax (percentage of maximum standardized uptake value) that generated a biologically plausible volume. Volumetric arc-based plans incorporating prostate plus DIL-SIB treatment were generated. Tumor control probability (TCP) and normal tissue complication probability (NTCP) with fractionation schemes and boost doses specified in the FLAME (Investigate the Benefit of a Focal Lesion Ablative Microboost in Prostate Cancer; NCT01168479), PROFIT (Prostate Fractionated Irradiation Trial; NCT00304759), PACE (Prostate Advances in Comparative Evidence; NCT01584258), and hypoFLAME (Hypofractionated Focal Lesion Ablative Microboost in prostatE Cancer 2.0; NCT02853110) protocols were compared.ResultsComparative DIL-SIB plans for 6 men were generated from preoperative [18F]-DCFPyL PET/CT. Median boost GTV volume was 1.015 cm3 (0.42-1.83 cm3). Median minimum (D99%) DIL-SIB dose for F35BS, F20BS, F5BS, and F5BSH were 97.3 Gy, 80.8 Gy, 46.5 Gy, and 51.5Gy. TCP within the GTV ranged from 84% to 88% for the standard plan and 95% to 96% for the DIL-SIB plans. Within the rest of the prostate, TCP ranged from 89% to 91% for the standard plans and 90% to 92% for the DIL-SIB plans. NTCP for the rectum NTCP was similar for the DIL-SIB plans (0.3%-2.7%) compared with standard plans (0.7%-2.6%). Overall, DIL-SIB plans yielded higher uncomplicated TCP (NTCP, 90%-94%) versus standard plans (NTCP, 83%-85%).ConclusionsPSMA PET provides a novel approach to define GTV for SIB-DIL dose escalation. Work is ongoing to validate PSMA PET-delineated GTV through correlation to coregistered postprostatectomy digitized histopathology.
| S-EPMC7136625 | biostudies-literature
Project description:Background and purposeDose escalation in external radiotherapy of prostate cancer shows promising results in terms of biochemical disease-free survival. Boost volume delineation guidelines are sparse which may cause high interobserver variability. The aim of this research was to characterize gross tumor volume (GTV) delineations based on multiparametric magnetic resonance imaging (mpMRI) and prostate specific membrane antigen-positron emission tomography (PSMA-PET) in relation to histopathology-validated Gleason grade 4 and 5 regions.Material and methodsThe study participants were examined with [68Ga]PSMA-PET/mpMRI prior to radical prostatectomy. Four radiation oncologists delineated GTVs in 15 study participants, on four different image types; T2-weighted (T2w), diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and PSMA-PET scans separately. The simultaneous truth and performance level estimation (STAPLE) algorithm was used to generate combined GTVs. GTVs were subsequently compared to histopathology. We analysed how Dice similarity coefficient (DSC) and lesion coverage are affected by using single versus multiple image types as well as by adding a clinical target volume (CTV) margin.ResultsMedian DSC (STAPLE) for different GTVs varied between 0.33 and 0.52. GTVPSMA-PET/mpMRI generated the highest median lesion coverage at 0.66. Combining different image types achieved similar lesion coverage as adding a CTV margin to contours from a single image type, while reducing non-malignant tissue inclusion within the target volume.ConclusionThe combined use of mpMRI or PSMA-PET/mpMRI shows promise, achieving higher DSC and lesion coverage while minimizing non-malignant tissue inclusion, in comparison to the use of a single image type with an added CTV margin.
| S-EPMC11402543 | biostudies-literature
Project description:BackgroundRoutine prostate-specific membrane antigen (PSMA) positron emission tomography (PET) performed for primary staging or restaging of prostate cancer patients is usually done as a single static image acquisition 60 min after tracer administration. In this study, we employ dynamic whole-body (D-WB) PET imaging to compare the pharmacokinetics of [68Ga]Ga-PSMA-11 and [18F]PSMA-1007 in various tissues and lesions, and to assess whether Patlak parametric images are quantitative and improve lesion detection and image readability.MethodsTwenty male patients with prostate cancer were examined using a D-WB PSMA PET protocol. Ten patients were scanned with [68Ga]Ga-PSMA-11 and ten with [18F]PSMA-1007. Kinetic analyses were made using time-activity curves (TACs) extracted from organs (liver, spleen, bone, and muscle) and lesions. For each patient, three images were produced: SUV + Patlak parametric images (Ki and DV). All images were reviewed visually to compare lesion detection, image readability was quantified using target-to-background ratios (TBR), and Ki and DV values were compared.ResultsThe two PSMA tracers exhibited markedly different pharmacokinetics in organs: reversible for [68Ga]Ga-PSMA-11 and irreversible for [18F]PSMA-1007. For both tracers, lesions kinetics were best described by an irreversible model. All parametric images were of good visual quality using both radiotracers. In general, Ki images were characterized by reduced vascular signal and increased lesion TBR compared with SUV images. No additional malignant lesions were identified on the parametric images.ConclusionD-WB PET/CT is feasible for both PSMA tracers allowing for direct reconstruction of parametric Ki images. The use of multiparametric PSMA images increased TBR but did not lead to the detection of more lesions. For quantitative whole-body Ki imaging, [18F]PSMA-1007 should be preferred over [68Ga]Ga-PSMA-11 due to its irreversible kinetics in organs and lesions.
| S-EPMC10105814 | biostudies-literature
Project description:PurposeTo evaluate the interobserver variability of gross tumor volume (GTV) - delineation of Dominant Intraprostatic Lesions (DIPL) in patients with prostate cancer using published MRI criteria for multiparametric MRI at 3 Tesla by 6 different observers.Material and methods90 GTV-datasets based on 15 multiparametric MRI sequences (T2w, diffusion weighted (DWI) and dynamic contrast enhanced (DCE)) of 5 patients with prostate cancer were generated for GTV-delineation of DIPL by 6 observers. The reference GTV-dataset was contoured by a radiologist with expertise in diagnostic imaging of prostate cancer using MRI. Subsequent GTV-delineation was performed by 5 radiation oncologists who received teaching of MRI-features of primary prostate cancer before starting contouring session. GTV-datasets were contoured using Oncentra Masterplan® and iplan® Net. For purposes of comparison GTV-datasets were imported to the Artiview® platform (Aquilab®), GTV-values and the similarity indices or Kappa indices (KI) were calculated with the postulation that a KI > 0.7 indicates excellent, a KI > 0.6 to < 0.7 substantial and KI > 0.5 to < 0.6 moderate agreement. Additionally all observers rated difficulties of contouring for each MRI-sequence using a 3 point rating scale (1 = easy to delineate, 2 = minor difficulties, 3 = major difficulties).ResultsGTV contouring using T2w (KI-T2w = 0.61) and DCE images (KI-DCE = 0.63) resulted in substantial agreement. GTV contouring using DWI images resulted in moderate agreement (KI-DWI = 0.51). KI-T2w and KI-DCE was significantly higher than KI-DWI (p = 0.01 and p = 0.003). Degree of difficulty in contouring GTV was significantly lower using T2w and DCE compared to DWI-sequences (both p < 0.0001). Analysis of delineation differences revealed inadequate comparison of functional (DWI, DCE) to anatomical sequences (T2w) and lack of awareness of non-specific imaging findings as a source of erroneous delineation.ConclusionsUsing T2w and DCE sequences at 3 Tesla for GTV-definition of DIPL in prostate cancer patients by radiation oncologists with knowledge of MRI features results in substantial agreement compared to an experienced MRI-radiologist, but for radiotherapy purposes higher KI are desirable, strengthen the need for expert surveillance. DWI sequence for GTV delineation was considered as difficult in application.
| S-EPMC3828667 | biostudies-literature
Project description:PurposeWith the increased use of focal radiation dose escalation for primary prostate cancer (PCa), accurate delineation of gross tumor volume (GTV) in prostate-specific membrane antigen PET (PSMA-PET) becomes crucial. Manual approaches are time-consuming and observer dependent. The purpose of this study was to create a deep learning model for the accurate delineation of the intraprostatic GTV in PSMA-PET.MethodsA 3D U-Net was trained on 128 different 18F-PSMA-1007 PET images from three different institutions. Testing was done on 52 patients including one independent internal cohort (Freiburg: n = 19) and three independent external cohorts (Dresden: n = 14 18F-PSMA-1007, Boston: Massachusetts General Hospital (MGH): n = 9 18F-DCFPyL-PSMA and Dana-Farber Cancer Institute (DFCI): n = 10 68Ga-PSMA-11). Expert contours were generated in consensus using a validated technique. CNN predictions were compared to expert contours using Dice similarity coefficient (DSC). Co-registered whole-mount histology was used for the internal testing cohort to assess sensitivity/specificity.ResultsMedian DSCs were Freiburg: 0.82 (IQR: 0.73-0.88), Dresden: 0.71 (IQR: 0.53-0.75), MGH: 0.80 (IQR: 0.64-0.83) and DFCI: 0.80 (IQR: 0.67-0.84), respectively. Median sensitivity for CNN and expert contours were 0.88 (IQR: 0.68-0.97) and 0.85 (IQR: 0.75-0.88) (p = 0.40), respectively. GTV volumes did not differ significantly (p > 0.1 for all comparisons). Median specificity of 0.83 (IQR: 0.57-0.97) and 0.88 (IQR: 0.69-0.98) were observed for CNN and expert contours (p = 0.014), respectively. CNN prediction took 3.81 seconds on average per patient.ConclusionThe CNN was trained and tested on internal and external datasets as well as histopathology reference, achieving a fast GTV segmentation for three PSMA-PET tracers with high diagnostic accuracy comparable to manual experts.
| S-EPMC10862258 | biostudies-literature
Project description:ObjectiveThe objective of this study was to characterize exclusive costal lesions detected by 68 Gallium-labelled prostate-specific membrane antigen ([ 68 Ga]Ga-PSMA-11) PET/computed tomography (CT) at initial staging or biochemical recurrence (BCR) in prostate cancer (PCa) patients, and to identify clinical and/or PET/CT criteria associated with benign and malignant lesions.MethodsWe retrospectively identified 54 patients with PCa who underwent [ 68 Ga]Ga-PSMA-11 PET/CT for initial staging ( N = 39) or BCR ( N = 15) and whose reports described rib lesions, at the exclusion of any other lesions, whether doubtful, suspicious, or established. Posttherapy prostate-specific antigen (PSA) levels were used to determine whether those lesions were benign or malignant. Each patient's prostate-specific membrane antigen PET/CT report was classified as true positive, true negative, false positive, or false negative based on the posttherapy PSA level. We then assessed whether any clinical and/or PET/CT criteria could help differentiate benign from malignant lesions, and if any criteria were misleading.ResultsAmong the 54 patients, 46 (85.2%) had 64 benign costal lesions, and eight (14.8%) had 10 malignant lesions. PET/CT reports indicated rib lesions as benign/equivocal in 38/54 (55.6%) patients and malignant in 16/54 (29.6%). Benign features on CT were the only parameter significantly associated with the final diagnosis. Factors such as patient age, maximum standardized uptake value of lesions, lesion dispersion, and malignant features described on CT were found to be misleading when deciding the malignant or benign status.ConclusionMost exclusive costal lesions detected by [ 68 Ga]Ga-PSMA-11 PET/CT are benign. Apart from specific benign CT features, no clinical or PET/CT criteria reliably differentiate benign from malignant costal lesions.
| S-EPMC11634074 | biostudies-literature
Project description:ObjectiveThe objective of this study was to assess the accuracy of 68Ga-PSMA-11 PET/MRI, 18F-PSMA-1007 PET/CT, 68Ga-PSMA-11 PET/CT, and multiparametric (mp)MRI for the delineating of dominant intraprostatic lesions (IPL).Materials and methods35 patients with organ-confined prostate cancer who were assigned to definitive radiotherapy (RT) were divided into three groups based on imaging techniques: 68Ga-PSMA-PET/MRI (n = 9), 18F-PSMA-PET/CT (n = 16) and 68Ga-PSMA-PET/CT (n = 10). All patients without PSMA-PET/MRI received an additional mpMRI. PSMA-PET-based automatic isocontours and manual contours of the dominant IPLs were generated for each modality. The biopsy results were then used to validate whether any of the prostate biopsies were positive in the marked lesion using Dice similarity coefficient (DSC), Youden index (YI), sensitivity and specificity. Factors that can predict the accuracy of IPLs contouring were analysed.ResultsDiagnostic performance was significantly superior both for manual and automatic IPLs contouring using 68Ga-PSMA-PET/MRI (DSC/YI SUV70%-0.62/0.51), 18F-PSMA-PET/CT (DSC/YI SUV70%-0.67/0.53) or 68Ga-PSMA-PET/CT (DSC/YI SUV70%-0.63/0.51) compared to mpMRI (DSC/YI-0.47/0.41; p < 0.001). The accuracy for delineating IPLs was not improved by combination of PET/CT and mpMRI images compared to PET/CT alone. Significantly superior diagnostic accuracy was found for large prostate lesions (at least 15% from the prostate volume) and higher Gleason score (at least 7b) comparing to smaller lesions with lower GS.ConclusionIPL localization was significantly improved when using PSMA-imaging procedures compared to mpMRI. No significant difference for delineating IPLs was found between hybrid method PSMA-PET/MRI and PSMA-PET/CT. PSMA-based imaging technique should be considered for the diagnostics of IPLs and focal treatment modality.
| S-EPMC8079339 | biostudies-literature
Project description:IntroductionState of the art artificial intelligence (AI) models have the potential to become a "one-stop shop" to improve diagnosis and prognosis in several oncological settings. The external validation of AI models on independent cohorts is essential to evaluate their generalization ability, hence their potential utility in clinical practice. In this study we tested on a large, separate cohort a recently proposed state-of-the-art convolutional neural network for the automatic segmentation of intraprostatic cancer lesions on PSMA PET images.MethodsEighty-five biopsy proven prostate cancer patients who underwent 68Ga PSMA PET for staging purposes were enrolled in this study. Images were acquired with either fully hybrid PET/MRI (N = 46) or PET/CT (N = 39); all participants showed at least one intraprostatic pathological finding on PET images that was independently segmented by two Nuclear Medicine physicians. The trained model was available at https://gitlab.com/dejankostyszyn/prostate-gtv-segmentation and data processing has been done in agreement with the reference work.ResultsWhen compared to the manual contouring, the AI model yielded a median dice score = 0.74, therefore showing a moderately good performance. Results were robust to the modality used to acquire images (PET/CT or PET/MRI) and to the ground truth labels (no significant difference between the model's performance when compared to reader 1 or reader 2 manual contouring).DiscussionIn conclusion, this AI model could be used to automatically segment intraprostatic cancer lesions for research purposes, as instance to define the volume of interest for radiomics or deep learning analysis. However, more robust performance is needed for the generation of AI-based decision support technologies to be proposed in clinical practice.
| S-EPMC9995820 | biostudies-literature
Project description:BackgroundThere are some limitations in the commonly used methods for the detection of prostate cancer. There is a lack of nomograms based on multiparametric magnetic resonance imaging (mpMRI) and 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography-computed tomography (PET-CT) for the prediction of prostate cancer. The study seeks to compare the performance of mpMRI and 68Ga-PSMA PET-CT, and design a novel predictive model capable of predicting clinically significant prostate cancer (csPCa) before biopsy based on a combination of 68Ga-PSMA PET-CT, mpMRI, and patient clinical parameters.MethodsFrom September 2020 to June 2021, we prospectively enrolled 112 consecutive patients with no prior history of prostate cancer who underwent both 68Ga-PSMA PET-CT and mpMRI prior to biopsy at our clinical center. Univariate and multivariate regression analyses were used to identify predictors of csPCa, with a predictive model and its nomogram incorporating 68Ga-PSMA PET-CT, mpMRI, and the clinical predictors then being generated. The constructed model was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis, and further validated with the internal and external cohorts.ResultsThe model incorporated prostate-specific antigen density (PSAd), Prostate Imaging Reporting and Data System (PI-RADS) category, and maximum standardized uptake value (SUVmax), and it exhibited excellent predictive efficacy when applying to evaluate both training and validation cohorts [area under the curve (AUC): 0.936 and 0.940, respectively]. Compared with SUVmax alone, the model demonstrated excellent diagnostic performance with improved specificity (0.910, 95% CI: 0.824-0.963) and positive predictive values (0.811, 95% CI: 0.648-0.920). Calibration curve and decision curve analysis further confirmed that the model exhibited a high degree of clinical net benefit and low error rate.ConclusionsThe constructed model in this study was capable of accurately predicting csPCa prior to biopsy with excellent discriminative ability. As such, this model has the potential to be an effective non-invasive approach for the diagnosis of csPCa.
| S-EPMC10406546 | biostudies-literature