Comparison of Manual and Semi-Automatic [18F]PSMA-1007 PET Based Contouring Techniques for Intraprostatic Tumor Delineation in Patients With Primary Prostate Cancer and Validation With Histopathology as Standard of Reference

PURPOSE

Accurate contouring of intraprostatic gross tumor volume (GTV) is pivotal for successful delivery of focal therapies and for biopsy guidance in patients with primary prostate cancer (PCa). Contouring of GTVs, using 18-Fluor labeled tracer prostate specific membrane antigen positron emission tomography ([18F]PSMA-1007/PET) has not been examined yet.

PATIENTS AND METHODS

Ten Patients with primary PCa who underwent [18F]PSMA-1007 PET followed by radical prostatectomy were prospectively enrolled. Coregistered histopathological gross tumor volume (GTV-Histo) was used as standard of reference. PSMA-PET images were contoured on two ways: (1) manual contouring with PET scaling SUVmin-max: 0-10 was performed by three teams with different levels of experience. Team 1 repeated contouring at a different time point, resulting in n = 4 manual contours. (2) Semi-automatic contouring approaches using SUVmax thresholds of 20-50% were performed. Interobserver agreement was assessed for manual contouring by calculating the Dice Similarity Coefficient (DSC) and for all approaches sensitivity, specificity were calculated by dividing the prostate in each CT slice into four equal quadrants under consideration of histopathology as standard of reference.

RESULTS

Manual contouring yielded an excellent interobserver agreement with a median DSC of 0.90 (range 0.87-0.94). Volumes derived from scaling SUVmin-max 0-10 showed no statistically significant difference from GTV-Histo and high sensitivities (median 87%, range 84-90%) and specificities (median 96%, range 96-100%). GTVs using semi-automatic segmentation applying a threshold of 20-40% of SUVmax showed no significant difference in absolute volumes to GTV-Histo, GTV-SUV50% was significantly smaller. Best performing semi-automatic contour (GTV-SUV20%) achieved high sensitivity (median 93%) and specificity (median 96%). There was no statistically significant difference to SUVmin-max 0-10.

CONCLUSION

Manual contouring with PET scaling SUVmin-max 0-10 and semi-automatic contouring applying a threshold of 20% of SUVmax achieved high sensitivities and very high specificities and are recommended for [18F]PSMA-1007 PET based focal therapy approaches. Providing high specificities, semi-automatic approaches applying thresholds of 30-40% of SUVmax are recommend for biopsy guidance.

Intraprostatic Tumor Segmentation on PSMA PET Images in Patients with Primary Prostate Cancer with a Convolutional Neural Network

Accurate delineation of the intraprostatic gross tumor volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cancer (PCa). Prostate-specific membrane antigen PET (PSMA PET) may outperform MRI in GTV detection. However, visual GTV delineation underlies interobserver heterogeneity and is time consuming. The aim of this study was to develop a convolutional neural network (CNN) for automated segmentation of intraprostatic tumor (GTV-CNN) in PSMA PET. Methods: The CNN (3D U-Net) was trained on the ⁶⁸Ga-PSMA PET images of 152 patients from 2 different institutions, and the training labels were generated manually using a validated technique. The CNN was tested on 2 independent internal (cohort 1: ⁶⁸Ga-PSMA PET, n = 18 and cohort 2: ¹⁸F-PSMA PET, n = 19) and 1 external (cohort 3: ⁶⁸Ga-PSMA PET, n = 20) test datasets. Accordance between manual contours and GTV-CNN was assessed with the Dice-Sørensen coefficient (DSC). Sensitivity and specificity were calculated for the 2 internal test datasets (cohort 1: n = 18, cohort 2: n = 11) using whole-mount histology. Results: The median DSCs for cohorts 1-3 were 0.84 (range: 0.32-0.95), 0.81 (range: 0.28-0.93), and 0.83 (range: 0.32-0.93), respectively. Sensitivities and specificities for the GTV-CNN were comparable with manual expert contours: 0.98 and 0.76 (cohort 1) and 1 and 0.57 (cohort 2), respectively. Computation time was around 6 s for a standard dataset. Conclusion: The application of a CNN for automated contouring of intraprostatic GTV in ⁶⁸Ga-PSMA and ¹⁸F-PSMA PET images resulted in a high concordance with expert contours and in high sensitivities and specificities in comparison with histology as a reference. This robust, accurate and fast technique may be implemented for treatment concepts in primary prostate cancer. The trained model and the study's source code are available in an open source repository.

Intraindividual comparison between 68Ga-PSMA-PET/CT and mpMRI for intraprostatic tumor delineation in patients with primary prostate cancer: a retrospective analysis in 101 patients

PURPOSE

Accurate delineation of intraprostatic gross tumor volume (GTV) is mandatory for successful fusion biopsy guidance and focal therapy planning of prostate cancer (PCa). Multiparametric magnetic resonance imaging (mpMRI) is the current gold standard for GTV delineation; however, prostate-specific membrane antigen positron emission tomography (PSMA-PET) is emerging as a promising alternative. This study compares GTV delineation between mpMRI and ⁶⁸Ga-PSMA-PET in a large number of patients using validated contouring approaches.

METHODS

One hundred one patients with biopsy-proven primary PCa who underwent mpMRI and ⁶⁸Ga-PSMA-PET within 3 months before primary treatment were retrospectively enrolled. Clinical parameters (age, PSA, Gleason score in biopsy) were documented. GTV based on MRI and PET images were delineated; volumes measured and laterality determined. Additionally, biopsy data from 77 patients was analyzed. Univariate and multivariate binary logistic regression analyses were performed using concordance in laterality as the endpoint.

RESULTS

In total mpMRI and ⁶⁸Ga-PSMA-PET detected 151 and 159 lesions, respectively. Median GTV-MRI (2.8 ml, 95% CI 2.31-3.38 ml) was significantly (p < 0.0001) smaller than median GTV-PET (4.9 ml, 95% CI 3.9-6.6 ml). ⁶⁸Ga-PSMA-PET detected significantly more bilateral lesions than mpMRI (71 vs 57, p = 0.03). Analysis of patients with bilateral lesions in biopsy showed a significant higher concordance of laterality in ⁶⁸Ga-PSMA-PET (p = 0.03). In univariate analysis, PSA level and volume of GTV-MRI had an impact on concordance in laterality (p = 0.02 and p = 0.01), whereas in multivariate analysis, only GTV-MRI volume remained significant (p = 0.04).

CONCLUSION

MpMRI and ⁶⁸Ga-PSMA-PET detect a similar amount of PCa lesions. However, GTV-PET had approximately twice the volume (median 4.9 ml vs 2.8 ml) and detected significantly more bilateral lesions than mpMRI. Thus, ⁶⁸Ga-PSMA-PET gives highly important complementary information. Since we could not find any strong evidence for parameters to guide when ⁶⁸Ga-PSMA-PET is dispensable, it should be performed additionally to MRI in patients with intermediate and high-risk PCa according to D'Amico classification to improve GTV delineation.

Validation of different PSMA-PET/CT-based contouring techniques for intraprostatic tumor definition using histopathology as standard of reference

PURPOSE

Accurate definition of the intraprostatic gross tumor volume (GTV) is crucial for diagnostic and therapeutic approaches in patients with primary prostate cancer (PCa). The optimal methodology for contouring of GTV using Prostate specific membrane antigen positron emission tomography (PSMA-PET) information has not yet been defined.

METHODS AND MATERIALS

PCa patients who underwent a [68Ga]PSMA-11-PET/CT followed by radical prostatectomy were prospectively enrolled (n = 20). Six observer teams with different levels of experience and using different PET image scaling techniques performed manual contouring of GTV. Additionally, semi-automatic segmentation of GTVs was performed using SUVmax thresholds of 20-50%. Coregistered histopathological gross tumor volume (GTV-Histo) served as reference. Inter-observer agreement was assessed by calculating the Dice similarity coefficient (DSC).

RESULTS

Most contouring methods provided high sensitivity and specificity. For manual delineation, scaling the PET images from SUVmin-max: 0-5 resulted in high sensitivity (>86%). The highest specificity (100%) was obtained by scaling the PET images from SUVmin-max: 0-SUVmax. High interobserver agreement (median DSC 0.8) was observed when using the same PET image scaling technique (PET images SUVmin-max: 0-5). For semi-automatic segmentation, a low SUVmax threshold of 20% optimized sensitivity (SUVmax threshold 20%, 100% sensitivity, 32% of prostatic volume), whereas a higher threshold optimized specificity (SUVmax threshold 40%-50%, 100% specificity).

CONCLUSIONS

Contouring of regions with high tracer-uptake resulted in very high specificities and should be used for biopsy guidance. Both manual and semi-automatic approaches using validated SUV scaling (SUVmin-max: 0-5) or thresholding (20%) may provide high sensitivity, and should be considered for PSMA-PET-based focal therapy approaches.

Radiomic features from PSMA PET for non-invasive intraprostatic tumor discrimination and characterization in patients with intermediate- and high-risk prostate cancer - a comparison study with histology reference

Purpose: To evaluate the performance of radiomic features (RF) derived from PSMA PET for intraprostatic tumor discrimination and non-invasive characterization of Gleason score (GS) and pelvic lymph node status. Patients and methods: Patients with prostate cancer (PCa) who underwent [⁶⁸Ga]-PSMA-11 PET/CT followed by radical prostatectomy and pelvic lymph node dissection were prospectively enrolled (n=20). Coregistered histopathological gross tumor volume (GTV-Histo) in the prostate served as reference. 133 RF were derived from GTV-Histo and from manually created segmentations of the intraprostatic tumor volume (GTV-Exp). Spearman´s correlation coefficients (ρ) were assessed between RF derived from the different GTVs. We additionally analyzed the differences in RF values for PCa and non-PCa tissues. Furthermore, areas under receiver-operating characteristics curves (AUC) were calculated and uni- and multivariate analyses were performed to evaluate the RF based discrimination of GS 7 and ≥8 disease and of patients with nodal spread (pN1) and non-nodal spread (pN0) in surgical specimen. The results found in the latter analyses were validated by a retrospective cohort of 40 patients. Results: Most RF from GTV-Exp showed strong correlations with RF from GTV-Histo (86% with ρ>0.7). 81% and 76% of RF from GTV-Exp and GTV-Histo significantly discriminated between PCa and non-PCa tissue. The texture feature QSZHGE discriminated between GS 7 and ≥8 considering GTV-Histo (AUC=0.93) and GTV-Exp (prospective cohort: AUC=0.91 / validation cohort: AUC=0.84). QSZHGE also discriminated between pN1 and pN0 disease considering GTV-Histo (AUC=0.85) and GTV-Exp (prospective cohort: AUC=0.87 / validation cohort: AUC=0.85). In uni- and multivariate analyses including patients of both cohorts QSZHGE was a statistically significant (p<0.01) predictor for PCa patients with GS ≥8 tumors and pN1 status. Conclusion: RF derived from PSMA PET discriminated between PCa and non-PCa tissue within the prostate. Additionally, the texture feature QSZHGE discriminated between GS 7 and GS ≥8 tumors and between patients with pN1 and pN0 disease. Our results support the role of RF in PSMA PET as a new tool for non-invasive PCa discrimination and characterization of its biological properties.

Accuracy of [68Ga]Ga-RM2-PET/CT for diagnosis of primary prostate cancer compared to histopathology

INTRODUCTION

Prostate cancer (PCa) often shows an overexpression of the gastrin-releasing peptide receptor (GRPr). Therefore, GRPr is a possible theragnostic target. An interesting antagonist GRPr-ligand is RM2 or BAY86-7548. This study examines the accuracy of positron emission tomography (PET) with [⁶⁸Ga]Ga-RM2 for diagnostic imaging of primary PCa (pPCa) compared to histopathology in patients undergoing radical prostatectomy (RP).

METHODS

[⁶⁸Ga]Ga-RM2-PET examinations were performed in 15 patients before RP. All prostate specimens were histopathologically examined based on predefined spatial octants. Each prostate volume on PET was subdivided into octants, which were correlated to histopathology and evaluated according to presence of tumor by two experienced examiners. Additionally, PET data was evaluated by volume of interest (VOI) analyses in terms of maximum standardized uptake value (SUVmax) and normalized SUVmax relative to background activity (rSUVmax). Receiver operating characteristic (ROC) curves for SUVmax and rSUVmax were calculated.

RESULTS

At least one focus of increased [⁶⁸Ga]Ga-RM2 uptake corresponding to a tumor manifestation on histology was found in 14 of 15 patients (93%). Spatial concordance of visual PET readings with histopathology was very variable. Intraindividual agreement reached from ≤2 octants in three, 3-5 octants in six to ≥6 octants in six patients, resulting in a relatively low correlation of visual PET readings with histopathology (accuracy = 0.63; p = 0.0018). Lesion-based analysis found a sensitivity of 69% and a positive predictive value of 73%. Concordantly, the octant-based ROC curves for SUVmax and rSUVmax indicated a relatively low diagnostic performance (area under the curve of 0.59 and 0.61, respectively).

CONCLUSIONS

[⁶⁸Ga]Ga-RM2-PET shows only a relatively low diagnostic accuracy for pPCa compared to histopathology on an octant basis, which may be explained to some extent by methodological weaknesses. Further studies need to explore, whether the observed high interindividual variability of agreement between [⁶⁸Ga]Ga-RM2-PET and histopathology can be explained by different tumor biologies or other coincident prostatic pathologies.