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European Journal of Nuclear Medicine and Molecular Imaging

01-05-2024 | Prostate Cancer | Original Article

Development and validation of [18 F]-PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy

Authors: Tiancheng Li, Mimi Xu, Shuye Yang, Guolin Wang, Yinuo Liu, Kaifeng Liu, Kui Zhao, Xinhui Su

Published in: European Journal of Nuclear Medicine and Molecular Imaging

Abstract

Purpose

Biochemical recurrence (BCR) following radical prostatectomy (RP) is a significant concern for patients with prostate cancer. Reliable prediction models are needed to identify patients at risk for BCR and facilitate appropriate management. This study aimed to develop and validate a clinical-radiomics model based on preoperative [18 F]PSMA-1007 PET for predicting BCR-free survival (BRFS) in patients who underwent RP for prostate cancer.

Materials and methods

A total of 236 patients with histologically confirmed prostate cancer who underwent RP were retrospectively analyzed. All patients had a preoperative [18 F]PSMA-1007 PET/CT scan. Radiomics features were extracted from the primary tumor region on PET images. A radiomics signature was developed using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The performance of the radiomics signature in predicting BRFS was assessed using Harrell’s concordance index (C-index). The clinical-radiomics nomogram was constructed using the radiomics signature and clinical features. The model was externally validated in an independent cohort of 98 patients.

Results

The radiomics signature comprised three features and demonstrated a C-index of 0.76 (95% CI: 0.60–0.91) in the training cohort and 0.71 (95% CI: 0.63–0.79) in the validation cohort. The radiomics signature remained an independent predictor of BRFS in multivariable analysis (HR: 2.48, 95% CI: 1.47–4.17, p < 0.001). The clinical-radiomics nomogram significantly improved the prediction performance (C-index: 0.81, 95% CI: 0.66–0.95, p = 0.007) in the training cohort and (C-index: 0.78 95% CI: 0.63–0.89, p < 0.001) in the validation cohort.

Conclusion

We developed and validated a novel [18 F]PSMA-1007 PET-based clinical-radiomics model that can predict BRFS following RP in prostate cancer patients. This model may be useful in identifying patients with a higher risk of BCR, thus enabling personalized risk stratification and tailored management strategies.

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Title: Development and validation of [18 F]-PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy
Authors: Tiancheng Li
Mimi Xu
Shuye Yang
Guolin Wang
Yinuo Liu
Kaifeng Liu
Kui Zhao
Xinhui Su
Publication date: 01-05-2024
Publisher: Springer Berlin Heidelberg
Keywords: Prostate Cancer
Prostate Cancer
Prostatectomy
Prostatectomy
Computed Tomography
Computed Tomography
Published in: European Journal of Nuclear Medicine and Molecular Imaging
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-024-06734-6

At a glance: The STEP trials

Springer Medicine

Development and validation of [18 F]-PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy

Abstract

Purpose

Materials and methods

Results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Purpose

Materials and methods

Results

Conclusion

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