The future of prostate cancer fusion biopsy: enhancing efficiency with artificial intelligence

Background: Prostate cancer is a leading cause of cancer-related morbidity and mortality among men worldwide. Fusion biopsy, combining magnetic resonance imaging (MRI) with transrectal ultrasound (TRUS) guidance, has enhanced the detection of clinically significant prostate cancer. However, challenges such as inter-operator variability and accurate lesion targeting persist. Artificial intelligence (AI) and machine learning (ML) offer potential improvements in diagnostic accuracy and efficiency. Objective: To systematically review the role and perspectives of AI and ML in improving the efficiency of fusion biopsy in men with prostate cancer. Materials and Methods: Following PRISMA guidelines, a comprehensive literature search was conducted in MEDLINE, Web of Science, and Scopus up to October 2023. Studies assessing the application of AI and ML in fusion biopsy for prostate cancer were included. Results: A total of 1,236 records were identified (MEDLINE: 432; Web of Science: 398; Scopus: 406), with 312 duplicates removed. Titles and abstracts of 924 articles were screened, and 68 qualified for full-text eligibility assessment. Twenty-seven articles met the inclusion criteria and were qualitatively synthesized. Conclusion: AI and ML hold promise in improving the efficiency and accuracy of fusion biopsies in prostate cancer. Large-scale, prospective studies and standardized protocols are necessary to validate these technologies and facilitate their integration into clinical practice.