Vigdorovits Alon, Köteles Maria Magdalena, Olteanu Gheorghe-Emilian, Pop Ovidiu
Department of Pathology, County Clinical Emergency Hospital, Faculty of Medicine and Pharmacy, University of Oradea, 1 December Sq. No. 10, 410087 Oradea, Romania.
Center for Research and Innovation in Personalized Medicine of Respiratory Diseases, "Victor Babes" University of Medicine and Pharmacy, 300041 Timisoara, Romania.
Cancers (Basel). 2023 Dec 2;15(23):5692. doi: 10.3390/cancers15235692.
The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.
应用人工智能改善癌症患者获得高质量医疗服务的机会是现代医学的目标之一。病理学是现代肿瘤治疗的基础,其作用已远远超出诊断范畴,扩展到预测治疗反应和总体生存期。然而,在资源稀缺的医疗系统中,病理学的资金投入往往是事后才考虑的事情。病理学数字化程度的提高为潜在使用人工智能工具提高病理学家的效率以及从组织中提取更多信息铺平了道路。在这篇综述中,我们概述了与人工智能和肿瘤学病理学相关的主要研究方向,如肿瘤分类、分子改变预测和生物标志物定量。然后,我们讨论已成熟为临床产品并获得临床使用监管批准的工具实例。最后,我们强调病理学数字化和人工智能在病理学中应用所面临的主要障碍,同时也讨论可能的解决方案。