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

被引:10
|
作者
Spohn, Simon K. B. [1 ,2 ,3 ]
Schmidt-Hegemann, Nina-Sophie [4 ]
Ruf, Juri [5 ]
Mix, Michael [2 ,5 ]
Benndorf, Matthias [6 ]
Bamberg, Fabian [6 ]
Makowski, Marcus R. R. [7 ]
Kirste, Simon [1 ,2 ]
Ruehle, Alexander [1 ,2 ]
Nouvel, Jerome [1 ,2 ]
Sprave, Tanja [1 ,2 ]
Vogel, Marco M. E. [8 ,9 ]
Galitsnaya, Polina [8 ,9 ]
Gschwend, Juergen E. [10 ]
Gratzke, Christian [11 ]
Stief, Christian [12 ]
Loeck, Steffen [13 ,14 ]
Zwanenburg, Alex [13 ,14 ,15 ,16 ,17 ,18 ,19 ]
Trapp, Christian [4 ]
Bernhardt, Denise [8 ,9 ]
Nekolla, Stephan G. G. [20 ]
Li, Minglun [4 ]
Belka, Claus [4 ]
Combs, Stephanie E. E. [8 ,9 ]
Eiber, Matthias [20 ]
Unterrainer, Lena [22 ]
Unterrainer, Marcus [22 ]
Bartenstein, Peter [22 ]
Grosu, Anca-L. [1 ,2 ]
Zamboglou, Constantinos [1 ,2 ,3 ,23 ]
Peeken, Jan C. [8 ,9 ,21 ]
机构
[1] Univ Freiburg, Univ Med Ctr Freiburg, Fac Med, Dept Radiat Oncol, Robert Koch Str 3, D-79106 Freiburg, Germany
[2] German Canc Consortium DKTK, Partner Site Freiburg, Heidelberg, Germany
[3] Univ Freiburg, Fac Med, Berta Ottenstein Programme, Freiburg, Germany
[4] Ludwig Maximilians Univ Munchen, Univ Hosp, Dept Radiat Oncol, Munich, Germany
[5] Univ Freiburg, Fac Med, Med Ctr, Dept Nucl Med, Freiburg, Germany
[6] Univ Freiburg, Univ Med Ctr Freiburg, Fac Med, Dept Radiol, Freiburg, Germany
[7] Tech Univ Munich, Dept Radiol, Klinikum Rechts Isar, Munich, Germany
[8] Tech Univ Munich, Dept Radiat Oncol, Klinikum Rechts Isar, Munich, Germany
[9] German Canc Consortium DKTK, Partner Site Munich, Munich, Germany
[10] Tech Univ Munich, Dept Urol, Klinikum rechts Isar, Munich, Germany
[11] Univ Freiburg, Univ Med Ctr Freiburg, Fac Med, Dept Urol, Freiburg, Germany
[12] Ludwig Maximilians Univ Munchen, Univ Hosp, Dept Urol, Munich, Germany
[13] Tech Univ Dresden, Fac Med, OncoRay Natl Ctr Radiat Res Oncol, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany
[14] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany
[15] Natl Ctr Tumor Dis NCT, Partner Site Dresden, Dresden, Germany
[16] German Canc Consortium DKTK, Partner Site Dresden, Heidelberg, Germany
[17] Tech Univ Dresden, Fac Med, Dresden, Germany
[18] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Dresden, Germany
[19] Helmholtz Zentrum Dresden Rossendorf HZDR, Helmholtz Assoc, Dresden, Germany
[20] Tech Univ Munich, Dept Nucl Med, Klinikum Rechts Isar, Munich, Germany
[21] Helmholtz Zentrum Munchen, Inst Radiat Med, Munich, Germany
[22] Ludwig Maximilians Univ Munchen, Univ Hosp, Dept Nucl Med, Munich, Germany
[23] European Univ Cyprus, German Oncol Ctr, Limassol, Cyprus
关键词
PSMA-PET/CT; Salvage radiotherapy; Prostate cancer; Radiomics; Outcome prediction; Personalization; PROSTATE-CANCER; VALIDATION;
D O I
10.1007/s00259-023-06195-3
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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 Ga-68-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.
引用
收藏
页码:2537 / 2547
页数:11
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