Bridging the experience gap in prostate multiparametric magnetic resonance imaging using artificial intelligence: A prospective multi-reader comparison study on inter-reader agreement in PI-RADS v2.1

The aim of the study was to determine the impact of using a semi-automatic commercially available AI-assisted software (Quantib® Prostate) on inter-reader agreement in PI-RADS scoring at different PI-QUAL ratings and grades of reader confidence and on reporting times among novice readers in multiparametric prostate MRI.

A prospective observational study, with a final cohort of 200 patients undergoing mpMRI scans, was performed at our institution. An expert fellowship-trained urogenital radiologist interpreted all 200 scans based on PI-RADS v2.1. The scans were divided into four equal batches of 50 patients. Four independent readers evaluated each batch with and without the use of AI-assisted software, blinded to expert and individual reports. Dedicated training sessions were held before and after each batch. Image quality rated according to PI-QUAL and reporting times were recorded. Readers' confidence was also evaluated. A final evaluation of the first batch was conducted at the end of the study to assess for any changes in performance.

The overall kappa coefficient differences in PI-RADS scoring agreement without and with Quantib® were 0.673 to 0.736 for Reader 1, 0.628 to 0.483 for Reader 2, 0.603 to 0.292 for Reader 3 and 0.586 to 0.613 for Reader 4. Using PI-RADS ≥ 4 as cut-off for biopsy, the AUCs with AI ranged from 0.799 (95 % CI: 0.743, 0.856) to 0.820 (95 % CI: 0.765, 0.874). Inter-reader agreements at different PI-QUAL scores were higher with the use of Quantib, particularly for readers 1 and 4, with Kappa coefficient values showing moderate to slight agreement.

Quantib® Prostate could potentially be useful in improving inter-reader agreement among less experienced to completely novice readers if used as a supplement to PACS.

European journal of radiology. 2023 Feb 19 [Epub ahead of print]

Ali Forookhi, Ludovica Laschena, Martina Pecoraro, Antonella Borrelli, Michele Massaro, Ailin Dehghanpour, Stefano Cipollari, Carlo Catalano, Valeria Panebianco

Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy., Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy. Electronic address: .

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