ESTRO 38 Abstract book

S79 ESTRO 38

M. Vogel 1 , S.G.C. Kroeze 2 , C. Henkenberens 3 , N.S. Schmidt-Hegemann 4 , S. Kirste 5 , J. Becker 6 , H. Christiansen 3 , C. Belka 4 , A.L. Grosu 5 , A.-C. Müller 6 , M. Guckenberger 2 , S.E. Combs 1 1 Klinikum rechts der Isar- Technical University of Munich TUM, Department of Radiation Oncology, Munich, Germany ; 2 University Hospital Zürich, Department of Radiation Oncology, Zürich, Switzerland ; 3 Medical School Hannover, Department of Radiotherapy and Special Oncology, Hannover, Germany; 4 University Hospital Munich LMU, Department of Radiation Oncology, Munich, Germany; 5 University of Freiburg, Department of Radiation Oncology, Freiburg, Germany; 6 University Hospital Tübingen, Department of Radiation Oncology, Tübingen, Germany Purpose or Objective PSMA-PET-Imaging has changed the treatment for patients with few metastases, in particular in form of radical radiotherapy (RT) for oligorecurrent prostate cancer (PC) after prior definitive therapy. However, the majority of patients will develop progressive disease, despite accurate PSMA-PET-Staging and stereotactic RT; how to optimally select patients is unknown. In this analysis, we aimed to develop a risk classification predicting biochemical relapse free survival (BCRFS) after PSMA-PET- guided RT. Material and Methods Data of 379 patients were collected at six radiation oncology departments. In this analysis we included 294 Patients with initial radical prostatectomy (RP) and subsequent diagnosis of oligorecurrent PC with positive findings in PSMA-PET-Imaging followed by radical RT. We used univariate and multiple Cox regression to determine significance for known risk factors. Significant factors were analyzed and grouped using recursive partitioning analysis (RPA) with classification and regression (CRT) method. Risk classes I to IV (low to very high risk) were generated using Kaplan-Meier estimator. Results In univariate Cox regression initial nodal status (N0 vs. N1, HR: 0.59, 95%-CI: 0.38-0.90, p=0.02), PSA Persistence ≥0.1 ng/ml after RP (yes vs. no, HR: 1.61, 95%-CI: 1.05-2.47, p=0.03), PSA levels ≥0.8 ng/ml at PSMA-PET-based diagnosis of oligorecurrent disease (no vs. yes, HR: 0.51, 95%-CI: 0.33-0.81, p=0.004), presence of bone metastases (no vs. yes, HR: 0.38, 95%-CI:0.23-0.62, p=0.0001), presence of other metastases than bone or lymph node lesions (no vs. yes, HR: 0.19, 95%-CI, 0.05-0.77, p=0.02), and total number of lesions (HR: 0.65, 95%-CI: 0.42-0.99, p=0.04) were significantly associated with relapse. PSA level at PSMA-PET-Imaging, bone metastases, and other metastases remained significant predictors in multiple regression. Figure 1 shows RPA for BCRFS at 24 months (mos) with a decision-making tree comprising end node groups A to E. 10-fold cross validation showed a risk for miscalculation of 0.295 (Standard error: 0.027), which results in 70.5% accuracy. Kaplan-Meier estimator showed a mean BCRFS of 15.6 mos (95%-CI: 11.2-30.0 mos) in group A, of 36.3 mos (95%-CI: 32.4-40.1 mos) in group B, of 5.7 mos (95%-CI: 2.6-8.7 mos) in group C, of 26.9 mos (95%-CI: 23.4-30.4 mos) in group D, and of 16.6 mos (95%-CI: 11.2- 22.0 mos) in Group E. Subsequently, we built risk classes I (Group B), II (Group D), III (Group A and E), and IV (Group C). Kaplan-Meier curve and mean BCRFS stratified for risk classes (p<0.0001) is shown in figure 2 respectively.

Germany; 5 Medical Center - University of Freiburg, Department of Nuclear Medicine, Freiburg, Germany Purpose or Objective The usage of radionuclide-labelled inhibitors of prostate- specific membrane antigen for positron-emission tomography (PSMA PET) may enable accurate intraprostatic gross tumor volume (GTV) delineation and the characterization of its biological properties. To test these hypotheses we co-registered the PET images with whole-mount prostate sections after surgery in order to perform a correlation study between histology and PSMA PET information, including radiomic features. Material and Methods 20 patients with intermediate and high-risk PCa underwent 68Ga-HBED-CC-PSMA PET/CT followed by radical prostatectomy. Histopathological information from resected prostates was processed and digitalized to obtain a 3D volume of PCa distribution. On each PET scan 5 contours were created: GTV-PET (expert contour of intraprostratic GTV based on PET information), GTV-histo (coregistered histopathology information, see figure 1A), GTV-histo-index (considering only lesions >5 mm in histology) and the subtraction volumes between the prostatic gland and GTV-histo and GTV-PET, respectively. To assess sensitivity and specificity in each CT slice the prostate was separated into 4 equal segments and the distribution of GTV-PET was compared with GTV-histo and GTV-histo-index, respectively. Furthermore, 133 radiomic features (including texture features) from PSMA PET were extracted from the respective volumes. False discovery rate-controlling procedures were implemented to account for multiple testing. Results PSMA PET detected PCa in all patients. Mean sensitivity/specificity for GTV-PET were 81%/86% and 91%/88% considering GTV-histo and GTV-histo-index, respectively. In 83% of image features a strong correlation (Spearman rho>0.7, p<0.05) between GTV-PET and GTV- histo was observed. Pairwise testing showed that 68% and 81% of image features had significant differences (p<0.05) between PCa and non PCa tissue considering GTV-histo and GTV-PET, respectively. 21% of image features derived from GTV-PET had a strong correlation (Spearman rho>0.7, p<0.05) with the Gleason score (GS) and 70% of those image features had significant differences (p<0.05) between GS 7 and GS > 7 PCa lesions (see exemplary figure 1B for feature: Long-Run High Gray-level Emphasis, QLRHGE).

Conclusion Based

on high sensitivity/specificity for PSMA PET-based GTV delineation was observed. In line with this observation we detected a strong correlation between image features extracted from GTV-PET and GTV-histo. The excellent diagnostic performance of PSMA PET enabled the usage of radiomic features for discrimination between PCa and non PCa tissue and for characterization of its biological aggressiveness. OC-0163 Risk classification for PSA relapse after PSMA- PET-guided RT for oligorecurrent prostate cancer histological validation a