Predicting side-specific extraprostatic extension in prostate cancer using an 18F-DCFPyL PSMA-PET/CT-based nomogram

Background: Extraprostatic extension (EPE) in prostate cancer (PCa) has implications for nerve-sparing approaches. mpMRI-based nomograms show modest accuracy, highlighting the need for improved predictive models. This study evaluates F-DCFPyL prostate-specific membrane antigen (PSMA) positron emission tomography/ computed tomography (PET/CT) for predicting side-specific EPE using maximum standardized uptake value (SUVmax). Methods: This single-center cohort study included patients undergoing RALP by a single surgeon (AKT) from January 2022 to September 2024. Baseline variables included demographics, PSA, biopsy, MRI, and PSMA parameters (SUVmax, EPE, SVI). The primary endpoint was side-specific EPE on final pathology. Univariable and multivariable logistic regression identified significant predictors. A nomogram was built based on this. To evaluate model performance, a 1000-iteration bootstrap approach was used to compare (1) the institutional MRI-only 2018 model, (2) an MRI + PSMA Fixed Model, and (3) a retrained MRI + PSMA Model built on each bootstrap sample. Conclusion: We developed a nomogram integrating PSMA PET with MRI and clinicopathological variables, outperforming our institutional model. PSMA uptake strongly predicts side-specific EPE, which can enhance preoperative assessment and improve postoperative functional outcomes.

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Publication Details

Journal
Universität Zürich, ZORA
Published
2025-07-23
DOI
https://doi.org/10.5167/uzh-284370
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
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article

Predicting side-specific extraprostatic extension in prostate cancer using an 18F-DCFPyL PSMA-PET/CT-based nomogram

Hannah Sur, Himanshu Joshi, Coşkun Kaçağan, Brenda Hug et al.
Universität Zürich, ZORA
Prostate Cancer Diagnosis and Treatment
article

Predicting side-specific extraprostatic extension in prostate cancer using an 18F-DCFPyL PSMA-PET/CT-based nomogram

Hannah Sur, Himanshu Joshi, Coşkun Kaçağan, Brenda Hug, Shokhi Goel, Lianne Ohayon, Kaushik P. Kolanukuduru, Reuben BEN-DAVID, Asher L. Mandel, Yashaswini Agarwal, Henry Jodka, Murilo de Almeida Luz, Ashutosh K Tewari, Basil Paul Kaufmann, Neeraja Tillu, Ashutosh Maheshwari, Susanna Baek, Manish Choudhary, Vinayak G Wagaskar
article en

Abstract

Background: Extraprostatic extension (EPE) in prostate cancer (PCa) has implications for nerve-sparing approaches. mpMRI-based nomograms show modest accuracy, highlighting the need for improved predictive models. This study evaluates F-DCFPyL prostate-specific membrane antigen (PSMA) positron emission tomography/ computed tomography (PET/CT) for predicting side-specific EPE using maximum standardized uptake value (SUVmax). Methods: This single-center cohort study included patients undergoing RALP by a single surgeon (AKT) from January 2022 to September 2024. Baseline variables included demographics, PSA, biopsy, MRI, and PSMA parameters (SUVmax, EPE, SVI). The primary endpoint was side-specific EPE on final pathology. Univariable and multivariable logistic regression identified significant predictors. A nomogram was built based on this. To evaluate model performance, a 1000-iteration bootstrap approach was used to compare (1) the institutional MRI-only 2018 model, (2) an MRI + PSMA Fixed Model, and (3) a retrained MRI + PSMA Model built on each bootstrap sample. Conclusion: We developed a nomogram integrating PSMA PET with MRI and clinicopathological variables, outperforming our institutional model. PSMA uptake strongly predicts side-specific EPE, which can enhance preoperative assessment and improve postoperative functional outcomes.

Universität Zürich, ZORA
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Prostate Cancer Diagnosis and Treatment
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Predicting side-specific extraprostatic extension in prostate cancer using an 18F-DCFPyL PSMA-PET/CT-based nomogram — Hannah Sur, Himanshu Joshi, et al. · Universität Zürich, ZORA (2025) | TGRS Research Map | TGRS