Prostate MRI percentage tumor involvement or "PI‐RADS percent" as a predictor of adverse surgical pathology. Issue 9 (19th April 2022) - Ratnani, Parita; Dovey, Zach; Parekh, Sneha; Sobotka, Stanislaw; Shukla, Devki; Davis, Avery; Roshandel, Reza; Wagaskar, Vinayak; Jambor, Ivan; Lundon, Dara J.; Wiklund, Peter; Kyprianou, Natasha; et al.
Abstract: Background: This study assesses magnetic resonance imaging (MRI) prostate % tumor involvement or "PI‐RADs percent" as a predictor of adverse pathology (AP) after surgery for localized prostate cancer (PCa). Two separate variables, "All PI‐RADS percent" (APP) and "Highest PI‐RADS percent" (HPP), are defined as the volume of All PI‐RADS 3–5 score lesions on MRI and the volume of the Highest PI‐RADS 3‐5 score lesion each divided by TPV, respectively. Method: An analysis was done of an IRB approved prospective cohort of 557 patients with localized PCa who had targeted biopsy of MRI PIRADs 3–5 lesions followed by RARP from April 2015 to May 2020 performed by a single surgeon at a single center. AP was defined as ISUP GGG ≥3, pT stage ≥T3 and/or LNI. Univariate and multivariable analyses were used to evaluate APP and HPP at predicting AP with other clinical variables such as Age, PSA at surgery, Race, Biopsy GGG, mpMRI ECE and mpMRI SVI. Internal and External Validation demonstrated predicted probabilities versus observed probabilities. Results: AP was reported in 44.5% ( n = 248) of patients. Multivariable regression showed both APP (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04–1.14, p = 0.0007) and HPP (OR: 1.10; 95% CI: 1.04–1.16; p = 0.0007) were significantly associated with AP with individual area under the operating curves (AUCs) of 0.6142 and 0.6229, respectively, and AUCs of 0.8129 and 0.8124 when incorporated in models including preoperative PSA and highest biopsy GGG. Conclusions: Increasing PI‐RADS Percent was associated with a higher risk of AP, and both APP and HPP may have clinical utility as predictors of AP in GGG 1 and 2 patients being considered for AS. Patient Summary: Using PIRADs percent to predict AP for presurgical patients may help risk stratification, and for low and low volume intermediate risk patients, may influence treatment decisions.