Clinical applications of artificial intelligence in Radiology: prostate magnetic resonance imaging

Abstract

This review provides an overview of how artificial intelligence (AI) can assist radiologists in evaluating prostate magnetic resonance imaging (MRI). Main tasks include image quality assessment, gland outlining, lesion detection and classification, lesion delineation, and structured reporting. Although the implementation of AI-based systems is still in its early stages, they have demonstrated promising results in improving the accuracy and efficiency of prostate MRI and reducing variability in diagnostic performance. Specifically, AI-based tools have proven effective in image quality evaluation, gland segmentation, and lesion detection and classification. However, improvements are still necessary, particularly for lesion delineation and automatic structured reporting. Indeed, AI-assisted lesion delineation requires larger, uniformly labeled datasets, and automatic structured reporting requires higher-quality linguistic expression generation. Taken as a whole, while AI-based models hold significant potential to support radiologists in various prostate MRI-related tasks, validation through human-driven clinical trials is required before implementing them in clinical practice. High-quality research is warranted to demonstrate the added value of AI compared to radiologists alone to bridge the gap between the current role of supporting tool and the futuristic role of decision-making tool.

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