{"title":"使用18F-DCFPyL PSMA-PET/ ct图预测前列腺癌侧特异性前列腺外展。","authors":"Neeraja Tillu, Ashutosh Maheshwari, Kaushik Kolanukuduru, Manish Choudhary, Yashaswini Agarwal, Himanshu Joshi, Shokhi Goel, Hannah Sur, Reuben Ben-David, Basil Kaufmann, Asher Mandel, Henry Jodka, Brenda Hug, Lianne Ohayon, Susanna Baek, Coskun Kacagan, Vinayak Wagaskar, Murilo de Almeida Luz, Ashutosh Tewari","doi":"10.1038/s41391-025-01001-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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 <sup>18</sup>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).</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>Three hundred fifty-five patients were analyzed. EPE was detected in 18.9% by MRI and 5.4% by PSMA PET. Median intraprostatic SUVmax was 11.30. EPE-positive sides were more likely to have MRI/PSMA-detected EPE (p < 0.001), PIRADS 5 lesions (p < 0.001), aggressive biopsy GGG (p < 0.001), higher positive cores (p < 0.001), and greater percent tumor involvement (p < 0.001). Median SUVmax was significantly higher in the EPE group (9.1 vs. 5.4; p < 0.001). Multivariable analysis identified PSA, MRI-detected EPE, GGG, tumor involvement percentage, and SUVmax ≥13 as significant predictors. The PSMA + MRI Fixed Model outperformed the MRI-only model (median AUC: 0.7542 vs. 0.7350) with p < 0.001. Calibration plots showed strong agreement between predicted and observed probabilities, and decision curve analysis demonstrated greater net clinical benefit across relevant thresholds.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":20727,"journal":{"name":"Prostate Cancer and Prostatic Diseases","volume":" ","pages":""},"PeriodicalIF":5.8000,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting side-specific extraprostatic extension in prostate cancer using an 18F-DCFPyL PSMA-PET/CT-based nomogram.\",\"authors\":\"Neeraja Tillu, Ashutosh Maheshwari, Kaushik Kolanukuduru, Manish Choudhary, Yashaswini Agarwal, Himanshu Joshi, Shokhi Goel, Hannah Sur, Reuben Ben-David, Basil Kaufmann, Asher Mandel, Henry Jodka, Brenda Hug, Lianne Ohayon, Susanna Baek, Coskun Kacagan, Vinayak Wagaskar, Murilo de Almeida Luz, Ashutosh Tewari\",\"doi\":\"10.1038/s41391-025-01001-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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 <sup>18</sup>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).</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>Three hundred fifty-five patients were analyzed. EPE was detected in 18.9% by MRI and 5.4% by PSMA PET. Median intraprostatic SUVmax was 11.30. EPE-positive sides were more likely to have MRI/PSMA-detected EPE (p < 0.001), PIRADS 5 lesions (p < 0.001), aggressive biopsy GGG (p < 0.001), higher positive cores (p < 0.001), and greater percent tumor involvement (p < 0.001). Median SUVmax was significantly higher in the EPE group (9.1 vs. 5.4; p < 0.001). Multivariable analysis identified PSA, MRI-detected EPE, GGG, tumor involvement percentage, and SUVmax ≥13 as significant predictors. The PSMA + MRI Fixed Model outperformed the MRI-only model (median AUC: 0.7542 vs. 0.7350) with p < 0.001. Calibration plots showed strong agreement between predicted and observed probabilities, and decision curve analysis demonstrated greater net clinical benefit across relevant thresholds.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":20727,\"journal\":{\"name\":\"Prostate Cancer and Prostatic Diseases\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Prostate Cancer and Prostatic Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41391-025-01001-7\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Prostate Cancer and Prostatic Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41391-025-01001-7","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
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 18F-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.
Results: Three hundred fifty-five patients were analyzed. EPE was detected in 18.9% by MRI and 5.4% by PSMA PET. Median intraprostatic SUVmax was 11.30. EPE-positive sides were more likely to have MRI/PSMA-detected EPE (p < 0.001), PIRADS 5 lesions (p < 0.001), aggressive biopsy GGG (p < 0.001), higher positive cores (p < 0.001), and greater percent tumor involvement (p < 0.001). Median SUVmax was significantly higher in the EPE group (9.1 vs. 5.4; p < 0.001). Multivariable analysis identified PSA, MRI-detected EPE, GGG, tumor involvement percentage, and SUVmax ≥13 as significant predictors. The PSMA + MRI Fixed Model outperformed the MRI-only model (median AUC: 0.7542 vs. 0.7350) with p < 0.001. Calibration plots showed strong agreement between predicted and observed probabilities, and decision curve analysis demonstrated greater net clinical benefit across relevant thresholds.
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.
期刊介绍：
Prostate Cancer and Prostatic Diseases covers all aspects of prostatic diseases, in particular prostate cancer, the subject of intensive basic and clinical research world-wide. The journal also reports on exciting new developments being made in diagnosis, surgery, radiotherapy, drug discovery and medical management.
Prostate Cancer and Prostatic Diseases is of interest to surgeons, oncologists and clinicians treating patients and to those involved in research into diseases of the prostate. The journal covers the three main areas - prostate cancer, male LUTS and prostatitis.
Prostate Cancer and Prostatic Diseases publishes original research articles, reviews, topical comment and critical appraisals of scientific meetings and the latest books. The journal also contains a calendar of forthcoming scientific meetings. The Editors and a distinguished Editorial Board ensure that submitted articles receive fast and efficient attention and are refereed to the highest possible scientific standard. A fast track system is available for topical articles of particular significance.
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