The Evidence for Using Artificial Intelligence to Enhance Prostate Cancer MR Imaging

Abstract

Purpose of review: The purpose of this review is to summarize the current status of artificial intelligence applied to prostate cancer MR imaging.

Recent findings: Artificial intelligence has been applied to prostate cancer MR imaging to improve its diagnostic accuracy and reproducibility of interpretation. Multiple models have been tested for gland segmentation and volume calculation, automated lesion detection, localization, and characterization, as well as prediction of tumor aggressiveness and tumor recurrence. Studies show, for example, that very robust automated gland segmentation and volume calculations can be achieved and that lesions can be detected and accurately characterized. Although results are promising, we should view these with caution. Most studies included a small sample of patients from a single institution and most models did not undergo proper external validation. More research is needed with larger and well-design studies for the development of reliable artificial intelligence tools.

Keywords: Artificial intelligence; Deep learning; MRI; Prostate cancer; Radiomics.