Abstract
Prostate Imaging Reporting and Data System (PI-RADS) has brought a standardized framework for the acquisition and interpretation of prostate multiparametric magnetic resonance imaging. To date, the most of studies implementing PI-RADS v2.1 in clinical practice have been conducted in developed Western countries. Our real-life experience from a developing country within the Middle East revealed that implementing PI-RADS v2.1 in prebiopsy multiparametric magnetic resonance imaging among 88 biopsy-naïve patients who underwent 12-core standard systematic biopsy, combined with magnetic resonance cognitive targeted biopsy, resulted in relatively lower cancer detection rates compared to developed countries. Therefore, we have discussed the limitations and challenges that might have influenced our results, including factors such as our equipment and technological capabilities, the experience and expertise of experts, and our biopsy methodology. Our lower cancer detection rates could be attributed to several factors, including the magnetic field strength of our scanner (1.5T), the shortage of expert and trained magnetic resonance imaging technologists in developing countries, the level of experience of our radiologist, the location and size of our index lesions, and inherent limitations of magnetic resonance cognitive targeted biopsy, particularly for lesions located at the apex and base of the prostate, as well as the number of biopsy cores obtained. Considering the challenges faced by radiologists in developing countries, incorporating artificial intelligence into the acquisition and interpretation of prostate multiparametric magnetic resonance imaging, and combining the PI-RADS scoring system with parameters with predictive value for prostate cancer diagnosis, like prostate-specific antigen density, prostate health index, and apparent diffusion coefficient value, could result in a significant improvement in prostate cancer detection and risk stratifications.