Author:
Spohn Simon K. B.,Schmidt-Hegemann Nina-Sophie,Ruf Juri,Mix Michael,Benndorf Matthias,Bamberg Fabian,Makowski Marcus R.,Kirste Simon,Rühle Alexander,Nouvel Jerome,Sprave Tanja,Vogel Marco M. E.,Galitsnaya Polina,Gschwend Jürgen E.,Gratzke Christian,Stief Christian,Löck Steffen,Zwanenburg Alex,Trapp Christian,Bernhardt Denise,Nekolla Stephan G.,Li Minglun,Belka Claus,Combs Stephanie E.,Eiber Matthias,Unterrainer Lena,Unterrainer Marcus,Bartenstein Peter,Grosu Anca-L.,Zamboglou Constantinos,Peeken Jan C.
Abstract
Abstract
Purpose
To develop a CT-based radiomic signature to predict biochemical recurrence (BCR) in prostate cancer patients after sRT guided by positron-emission tomography targeting prostate-specific membrane antigen (PSMA-PET).
Material and methods
Consecutive patients, who underwent 68Ga-PSMA11-PET/CT-guided sRT from three high-volume centers in Germany, were included in this retrospective multicenter study. Patients had PET-positive local recurrences and were treated with intensity-modulated sRT. Radiomic features were extracted from volumes of interests on CT guided by focal PSMA-PET uptakes. After preprocessing, clinical, radiomics, and combined clinical-radiomic models were developed combining different feature reduction techniques and Cox proportional hazard models within a nested cross validation approach.
Results
Among 99 patients, median interval until BCR was the radiomic models outperformed clinical models and combined clinical-radiomic models for prediction of BCR with a C-index of 0.71 compared to 0.53 and 0.63 in the test sets, respectively. In contrast to the other models, the radiomic model achieved significantly improved patient stratification in Kaplan-Meier analysis. The radiomic and clinical-radiomic model achieved a significantly better time-dependent net reclassification improvement index (0.392 and 0.762, respectively) compared to the clinical model. Decision curve analysis demonstrated a clinical net benefit for both models. Mean intensity was the most predictive radiomic feature.
Conclusion
This is the first study to develop a PSMA-PET-guided CT-based radiomic model to predict BCR after sRT. The radiomic models outperformed clinical models and might contribute to guide personalized treatment decisions.
Funder
Deutschen Konsortium für Translationale Krebsforschung
Universitätsklinikum Freiburg
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine,Radiology, Nuclear Medicine and imaging,General Medicine