Feretzakis Georgios, Juliebø-Jones Patrick, Tsaturyan Arman, Sener Tarik Emre, Verykios Vassilios S, Karapiperis Dimitrios, Bellos Themistoklis, Katsimperis Stamatios, Angelopoulos Panagiotis, Varkarakis Ioannis, Skolarikos Andreas, Somani Bhaskar, Tzelves Lazaros
School of Science and Technology, Hellenic Open University, 26335 Patras, Greece.
Department of Urology, Haukeland University Hospital, 5021 Bergen, Norway.
Cancers (Basel). 2024 Feb 16;16(4):810. doi: 10.3390/cancers16040810.
This comprehensive review critically examines the transformative impact of artificial intelligence (AI) and radiomics in the diagnosis, prognosis, and management of bladder, kidney, and prostate cancers. These cutting-edge technologies are revolutionizing the landscape of cancer care, enhancing both precision and personalization in medical treatments. Our review provides an in-depth analysis of the latest advancements in AI and radiomics, with a specific focus on their roles in urological oncology. We discuss how AI and radiomics have notably improved the accuracy of diagnosis and staging in bladder cancer, especially through advanced imaging techniques like multiparametric MRI (mpMRI) and CT scans. These tools are pivotal in assessing muscle invasiveness and pathological grades, critical elements in formulating treatment plans. In the realm of kidney cancer, AI and radiomics aid in distinguishing between renal cell carcinoma (RCC) subtypes and grades. The integration of radiogenomics offers a comprehensive view of disease biology, leading to tailored therapeutic approaches. Prostate cancer diagnosis and management have also seen substantial benefits from these technologies. AI-enhanced MRI has significantly improved tumor detection and localization, thereby aiding in more effective treatment planning. The review also addresses the challenges in integrating AI and radiomics into clinical practice, such as the need for standardization, ensuring data quality, and overcoming the "black box" nature of AI. We emphasize the importance of multicentric collaborations and extensive studies to enhance the applicability and generalizability of these technologies in diverse clinical settings. In conclusion, AI and radiomics represent a major paradigm shift in oncology, offering more precise, personalized, and patient-centric approaches to cancer care. While their potential to improve diagnostic accuracy, patient outcomes, and our understanding of cancer biology is profound, challenges in clinical integration and application persist. We advocate for continued research and development in AI and radiomics, underscoring the need to address existing limitations to fully leverage their capabilities in the field of oncology.
本综述全面审视了人工智能（AI）和放射组学在膀胱癌、肾癌和前列腺癌的诊断、预后及治疗管理方面的变革性影响。这些前沿技术正在彻底改变癌症护理的格局，提高医疗治疗的精准度和个性化程度。我们的综述深入分析了AI和放射组学的最新进展，特别关注它们在泌尿肿瘤学中的作用。我们讨论了AI和放射组学如何显著提高了膀胱癌诊断和分期的准确性，尤其是通过多参数MRI（mpMRI）和CT扫描等先进成像技术。这些工具对于评估肌肉浸润性和病理分级至关重要，而这是制定治疗方案的关键要素。在肾癌领域，AI和放射组学有助于区分肾细胞癌（RCC）的亚型和分级。放射基因组学的整合提供了疾病生物学的全面视图，从而带来量身定制的治疗方法。前列腺癌的诊断和治疗管理也从这些技术中受益匪浅。AI增强的MRI显著提高了肿瘤检测和定位能力，从而有助于制定更有效的治疗方案。该综述还探讨了将AI和放射组学整合到临床实践中所面临的挑战，例如标准化的必要性、确保数据质量以及克服AI的“黑箱”性质。我们强调多中心合作和广泛研究对于提高这些技术在不同临床环境中的适用性和普遍性的重要性。总之，AI和放射组学代表了肿瘤学的重大范式转变，为癌症护理提供了更精确、个性化和以患者为中心的方法。虽然它们在提高诊断准确性、患者预后以及我们对癌症生物学理解方面的潜力巨大，但临床整合和应用方面的挑战依然存在。我们主张继续开展AI和放射组学的研究与开发，强调需要解决现有局限性，以充分发挥它们在肿瘤学领域的能力。
