Urology · 2026
Development of a Prognostic Prediction Model for Clinically Significant Prostate Cancer Based on Lesion Zone and Apparent Diffusion Coefficient Value Quantification.
СтатьяНазвание и аннотация: Перевод в очереди
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Ashouri Rani, Reynolds Penny S, Rajavel Shay, Hanchate Kunal, Snead William, DiBianco John M, Joseph Jason, Crispen Paul, O'Malley Padraic, Grajo Joseph R, Falzarano Sara M, Stringer Thomas F, Su Li-Ming, Weight Christopher J, Benidir Tarik
Аннотация
OBJECTIVE: To guide biopsy decision making via a predictive model for clinically significant prostate cancer (csPCa) in men with positive imaging (PI-RADS 3-5). We aim to elucidate the influence of zone on the predictive accuracy of PI-RADS v2.1, establish a threshold of quantified apparent diffusion coefficient (ADC) values suspicious for csPCa, and create a logistic-regression model, unique in its inclusion of lesion zone and quantified ADC.
METHODS: Data were retrospectively collected from a single cancer center, with institutional review board review and exemption waiver, on a lesion-level retrospective analysis of prostate multiparametric magnetic resonance imaging (mpMRI) of N = 429 men, harboring N = 546 lesions. MRIs were read and reviewed by a fellowship-trained genitourinary/abdominal imaging radiologist. Pathologic analysis was conducted by a fellowship-trained genitourinary pathologist. All statistical analysis including predictive modeling were conducted by an expert biostatistician.
RESULTS: On multivariate analysis, zone (PZ as compared to TZ) was a predictor of csPCa (OR 2.58, 95% CI 1.50-4.44, P<.0005). A 700 µm2/s ADC value cutoff in isolation had an AUC of 0.56, but our combined model, bolstered by clinical and imaging data, including zone and prostate-specific antigen density, yielded an AUC of 0.78, at an ADC value cutoff of 947 µm2/s. In application, simulated scenarios yielded probabilities between 16% and 82%, therefore above a biopsy omission threshold of 10% or less.
CONCLUSION: Prostate zone and ADC value quantification each independently contribute to csPCa predictability, but no simulated use of the model yielded biopsy-omission thresholds for patients with MRI visible lesions.
METHODS: Data were retrospectively collected from a single cancer center, with institutional review board review and exemption waiver, on a lesion-level retrospective analysis of prostate multiparametric magnetic resonance imaging (mpMRI) of N = 429 men, harboring N = 546 lesions. MRIs were read and reviewed by a fellowship-trained genitourinary/abdominal imaging radiologist. Pathologic analysis was conducted by a fellowship-trained genitourinary pathologist. All statistical analysis including predictive modeling were conducted by an expert biostatistician.
RESULTS: On multivariate analysis, zone (PZ as compared to TZ) was a predictor of csPCa (OR 2.58, 95% CI 1.50-4.44, P<.0005). A 700 µm2/s ADC value cutoff in isolation had an AUC of 0.56, but our combined model, bolstered by clinical and imaging data, including zone and prostate-specific antigen density, yielded an AUC of 0.78, at an ADC value cutoff of 947 µm2/s. In application, simulated scenarios yielded probabilities between 16% and 82%, therefore above a biopsy omission threshold of 10% or less.
CONCLUSION: Prostate zone and ADC value quantification each independently contribute to csPCa predictability, but no simulated use of the model yielded biopsy-omission thresholds for patients with MRI visible lesions.