Multi-parametric MRI prostate PIRAD scoring in a district general hospital: Correlating PIRADS 3 results with histological findings.

Prostate cancer is the most common male cancer in the UK. In many hospitals, patients are now being referred for a multi parametric (mp) MRI scan of their prostate as part of an evaluation for the presence of prostate cancer, prior to an ultrasound guided biopsy. PI-RADS score of 3 are defined as "equivocal" for the presence of prostate cancer. Thus, a PIRADS three lesion does not confidently determine whether there is significant prostate disease or not.Our aim is to determine the correlation of PIRADS three prostatic lesions with histology proven, clinically significant cancer.

We performed a retrospective review on a cohort of 143 consecutive patients. Each patient underwent a mp-MRI scan of their prostate given a PIRADS score. PIRADS three lesions were analysed further based on histology and categorised into malignant and non-malignant lesions. PSA results and prostatic volume of PIRADS three lesions were also analysed.

We identified forty five patients with PIRADS 3 lesions out of 143 patients. Thirty-two patients subsequently underwent trans-rectal/trans-perineal ultrasound guided biopsy. 43% of patients were found to have had a malignant prostatic adenocarcinoma on histology. The remaining 56% had non-malignant findings. Of those with malignant disease, there was a higher median PSA and lower mean prostatic volume.

The study confirms that a score of PIRADS three does not accurately differentiate between malignant and non-malignant lesions. Further investigations such as ultrasound-guided prostate biopsy and PSA parameters are required to accurately ascertain the nature of a prostate lesion with PIRADS score 3.

An ultrasound-guided prostate biopsy in patients with PIRADS 3 remains of paramount importance when distinguishing malignant versus non-malignant lesions. Multicentre data of MRI findings with PIRADS three scores is required to yield a sample size large enough to carry out statistical analysis.

The British journal of radiology. 2021 Dec 17 [Epub ahead of print]

Sarmad Aslam, Jeffrey Tsang, Ian Bickle, Ali Saiepour

Department of Radiology, Chesterfield Royal Hospital NHS Foundation Trust, Chesterfield, United Kingdom.