Prostate Imaging for Recurrence Reporting (PI-RR) was introduced in 2021 to standardize the interpretation and reporting of multiparametric magnetic resonance imaging (MRI) for prostate cancer following whole-gland treatment. The system scores image on a scale from 1 to 5 and has shown promising results in single-center studies. The aim of our systematic review and meta-analysis was to assess the diagnostic performance of the PI-RR system in predicting the likelihood of local recurrence after whole-gland treatment.
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for diagnostic test accuracy were followed. Relevant databases were searched up to December 2023. Primary studies met the eligibility criteria if they reported MRI diagnostic performance in prostate cancer recurrence using PI-RR. Diagnostic performance for MRI was assessed using two different cutoff points (≥3 or ≥4 for positivity according to the PI-RR system). A meta-analysis with a random-effects model was used to estimate pooled sensitivity and specificity values.
Sixteen articles were identified for full-text reading, of which six were considered eligible, involving a total of 467 patients. Using a cutoff of PI-RR ≥3 (4 studies) for recurrent disease, the sensitivity was 77.8% (95% confidence interval [CI] 69.9-84.1%) and the specificity was 80.2% (95% CI 58.2-92.2%). Using a cutoff of PI-RR ≥4 (4 studies), the sensitivity was 61.9% (95% CI 35.6-82.7%) and the specificity was 86.6% (95% CI 75.1-93.3%). Overall, the inter-rater agreement varied from fair to excellent.
PI-RR is accurate in detecting local recurrence after whole-gland treatment for prostate cancer and shows fair-to-good to excellent inter-reader agreement. Overall, a PI-RR cutoff of ≥3 showed high sensitivity and specificity.
We reviewed studies that reported on how good MRI scans using a scoring system called PI-RR were in detecting recurrence of prostate cancer. We found that this system shows good performance, with fair to excellent agreement between different radiologists.
European urology oncology. 2024 May 31 [Epub ahead of print]
Felipe A Mourato, Luiza G Schmitt, Miriana Mariussi, Giovanni Torri, Stephan Altmayer, Francesco Giganti, Jorge Abreu-Gomez, Nathan Perlis, Alejandro Berlin, Sangeet Ghai, Masoom A Haider, Adriano B Dias
Unidade de Diagnóstico por Imagem, Empresa Brasileira de Serviços Hospitalares, Hospital das Clínicas da Universidade Federal de Pernambuco, Recife, Brazil. Electronic address: ., Department of Radiation Oncology, UT Southwestern, Dallas, TX, USA., Department of Diagnostic Radiology, Hospital Universitario Austral, Buenos Aires, Argentina., Department of Radiology and Diagnostic Imaging, Hospital Universitário de Santa Maria, Universidade Federal de Santa Maria, Santa Maria, Brazil., Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA., Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery and Interventional Science, UCL, London, UK., University Medical Imaging Toronto; Joint Department of Medical Imaging; University Health Network-Sinai Health System-Women's College Hospital, University of Toronto, Toronto, ON, Canada., Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada., Department of Radiation Oncology, Princess Margaret Cancer Center, University Health Network and University of Toronto, Toronto, Canada.