Back to Search Start Over

Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy.

Authors :
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
Source :
European Journal of Nuclear Medicine & Molecular Imaging. Jul2023, Vol. 50 Issue 8, p2537-2547. 11p. 1 Color Photograph, 1 Diagram, 4 Charts, 5 Graphs.
Publication Year :
2023

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16197070
Volume :
50
Issue :
8
Database :
Academic Search Index
Journal :
European Journal of Nuclear Medicine & Molecular Imaging
Publication Type :
Academic Journal
Accession number :
164176969
Full Text :
https://doi.org/10.1007/s00259-023-06195-3