The Role of mpMRI in the Assessment of Prostate Cancer Recurrence Using the PI-RR System: Diagnostic Accuracy and Interobserver Agreement in Readers with Different Expertise

Abstract

Background: treated prostate cancer (PCa) patients develop biochemical recurrence (BCR) in 27–53% of cases; the role of MRI in this setting is still controversial. In 2021 a panel of experts proposed a “Prostate Imaging-Recurrence Reporting” (PI-RR) score, aiming to standardize the reporting. The aim of our study is to evaluate the reproducibility of the PI-RR scoring system among readers with different expertise. Methods: in this monocentric, retrospective observational study, the images of patients who underwent MRI with BCR from January 2017 to January 2022 were analyzed by two radiologists and a radiology resident. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were obtained. Interobserver agreement was calculated. The percentage of the PI-RR score of 3 was estimated to find out the proportion of uncertain exams reported among the readers. Results: a total of seventy-six patients were included in our study: eight previously treated with RT and sixty-eight who underwent surgery. The accuracy range was 75–80%, the sensitivity 68.4–71.1%, the specificity 81.6–89.5%, PPV 78.8–87.1%, and NPV 72.1–75.6%. The inter-reader agreement using a binary evaluation (PI-RR ≥ 3 as positive mpMRI) demonstrated a correlation coefficient (k) of 0.74 (95% CI: 0.62–0.87). The percentage for the PI-RR score of 3 was 6.6% for reader one, 14.5% for reader two, and 2.6% for reader three. Conclusion: this study confirmed the good accuracy of mpMRI in the detection of local recurrence of PCa and the good reproducibility of PI-RR score among all readers, confirming it to be a promising tool for the standardization of the assessment of patients with BCR.

Research progress on deep learning in magnetic resonance imaging–based diagnosis and treatment of prostate cancer: a review on the current status and perspectives

“…This is particularly crucial since PSA levels can fluctuate and be influenced by various factors (165,166). Furthermore, the role of mpMRI in assessing PCa recurrence has gained importance (167), underscoring the need for comprehensive investigation into MRI-based PCa recurrence prediction. Yan et al (168) conducted a multicenter study using a DL technique and a novel model called deep radiomic signature for BCR prediction.…”

Multiparametric magnetic resonance imaging in diagnosis of local prostate cancer recurrence after radiation therapy and radical prostatectomy: a unified PI-RR reporting system

“…По результатам опубликованных исследований система PI-RR имеет высокие показатели диагностической эффективности в выявлении локального рецидива у пациентов, получивших хирургическое лечение РПЖ в объеме РПЭ либо ЛТ. Общая точность мпМРТ в диагностике локальных рецидивов с использованием PI-RR у пациентов после РПЭ и ЛТ варьировала в диапазоне 75-85 и 77-88 % соответственно [52,53].…”

T2-Weighted MRI Radiomic Features Predict Prostate Cancer Presence and Eventual Biochemical Recurrence

“…PI-RADS has aided in the detection of cancerous lesions and has improved the consistency of clinical radiology reads [ 8 , 9 , 10 , 11 ]. While PI-RADS has improved cancer detection and is frequently used for biopsy guidance, it has not improved the stratification of patients at risk of BCR; therefore, there has been an increase in studies attempting to detect PCa with high metastatic potential [ 12 , 13 , 14 ].…”

“…Radiomics is a multi-step process where quantitative features or textures from MR images are extracted using data-characterization algorithms to decode underlying tissue characteristics [ 7 , 8 ]. Radiomic features contain first-, second-, and higher-order statistics that are combined with other patient data to develop models that may detect and characterize a clinically relevant outcome [ 9 , 10 , 11 , 12 ]. They are thought to capture distinct phenotypic differences in tumors and quantitatively assess intra- and intertumoral heterogeneity [ 18 , 19 ].…”