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Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy.
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.
Afiliación
  • Spohn SKB; Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany. Simon.Spohn@uniklinik-freiburg.de.
  • Schmidt-Hegemann NS; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany. Simon.Spohn@uniklinik-freiburg.de.
  • Ruf J; Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany. Simon.Spohn@uniklinik-freiburg.de.
  • Mix M; Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.
  • Benndorf M; Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany.
  • Bamberg F; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany.
  • Makowski MR; Department of Nuclear Medicine, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany.
  • Kirste S; Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Rühle A; Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Nouvel J; Department of Radiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Sprave T; Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany.
  • Vogel MME; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany.
  • Galitsnaya P; Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany.
  • Gschwend JE; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany.
  • Gratzke C; Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany.
  • Stief C; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany.
  • Löck S; Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Robert-Koch-Straße 3, 79106, Freiburg, Germany.
  • Zwanenburg A; German Cancer Consortium (DKTK) Partner Site Freiburg, Heidelberg, Germany.
  • Trapp C; Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Bernhardt D; German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.
  • Nekolla SG; Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Li M; German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.
  • Belka C; Department of Urology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
  • Combs SE; Department of Urology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Eiber M; Department of Urology, University Hospital, LMU Munich, Munich, Germany.
  • Unterrainer L; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
  • Unterrainer M; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
  • Bartenstein P; National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
  • Grosu AL; German Cancer Consortium (DKTK) Partner Site Dresden, Heidelberg, Germany.
  • Zamboglou C; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
  • Peeken JC; Helmholtz Association/Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany.
Eur J Nucl Med Mol Imaging ; 50(8): 2537-2547, 2023 07.
Article en En | MEDLINE | ID: mdl-36929180
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Próstata / Radioisótopos de Galio Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans / Male Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Alemania
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Próstata / Radioisótopos de Galio Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans / Male Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Alemania