Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer

• Published in: American journal of clinical and experimental urology 2024-01, Vol.12 (4), p.200-215
• Main Authors: Zhu, Min, Sali, Rasoul, Baba, Firas, Khasawneh, Hamdi, Ryndin, Michelle, Leveillee, Raymond J, Hurwitz, Mark D, Lui, Kin, Dixon, Christopher, Zhang, David Y
• Format: Article
• Language: English
• Subjects: Review
• ISSN: 2330-1910; 2330-1910
• DOI: 10.62347/JSAE9732

Histopathology, which is the gold-standard for prostate cancer diagnosis, faces significant challenges. With prostate cancer ranking among the most common cancers in the United States and worldwide, pathologists experience an increased number for prostate biopsies. At the same time, precise pathological assessment and classification are necessary for risk stratification and treatment decisions in prostate cancer care, adding to the challenge to pathologists. Recent advancement in digital pathology makes artificial intelligence and learning tools adopted in histopathology feasible. In this review, we introduce the concept of AI and its various techniques in the field of histopathology. We summarize the clinical applications of AI pathology for prostate cancer, including pathological diagnosis, grading, prognosis evaluation, and treatment options. We also discuss how AI applications can be integrated into the routine pathology workflow. With these rapid advancements, it is evident that AI applications in prostate cancer go beyond the initial goal of being tools for diagnosis and grading. Instead, pathologists can provide additional information to improve long-term patient outcomes by assessing detailed histopathologic features at pixel level using digital pathology and AI. Our review not only provides a comprehensive summary of the existing research but also offers insights for future advancements.