Marra A, Morganti S, Pareja F, Campanella G, Bibeau F, Fuchs T, Loda M, Parwani A, Scarpa A, Reis-Filho J S, Curigliano G, Marchiò C, Kather J N
Division of Early Drug Development for Innovative Therapies, European Institute of Oncology IRCCS, Milan, Italy.
Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA; Gerstner Center for Cancer Diagnostics, Broad Institute of MIT and Harvard, Boston, USA.
Ann Oncol. 2025 Apr 28. doi: 10.1016/j.annonc.2025.03.006.
Artificial intelligence (AI) is rapidly transforming the fields of pathology and oncology, offering novel opportunities for advancing diagnosis, prognosis, and treatment of cancer.
Through a systematic review-based approach, the representatives from the European Society for Medical Oncology (ESMO) Precision Oncology Working Group (POWG) and international experts identified studies in pathology and oncology that applied AI-based algorithms for tumour diagnosis, molecular biomarker detection, and cancer prognosis assessment. These findings were synthesised to provide a comprehensive overview of current AI applications and future directions in cancer pathology.
The integration of AI tools in digital pathology is markedly improving the accuracy and efficiency of image analysis, allowing for automated tumour detection and classification, identification of prognostic molecular biomarkers, and prediction of treatment response and patient outcomes. Several barriers for the adoption of AI in clinical workflows, such as data availability, explainability, and regulatory considerations, still persist. There are currently no prognostic or predictive AI-based biomarkers supported by level IA or IB evidence. The ongoing advancements in AI algorithms, particularly foundation models, generalist models and transformer-based deep learning, offer immense promise for the future of cancer research and care. AI is also facilitating the integration of multi-omics data, leading to more precise patient stratification and personalised treatment strategies.
The application of AI in pathology is poised to not only enhance the accuracy and efficiency of cancer diagnosis and prognosis but also facilitate the development of personalised treatment strategies. Although barriers to implementation remain, ongoing research and development in this field coupled with addressing ethical and regulatory considerations will likely lead to a future where AI plays an integral role in cancer management and precision medicine. The continued evolution and adoption of AI in pathology and oncology are anticipated to reshape the landscape of cancer care, heralding a new era of precision medicine and improved patient outcomes.
人工智能（AI）正在迅速改变病理学和肿瘤学领域，为推进癌症的诊断、预后和治疗提供了新的机遇。
欧洲医学肿瘤学会（ESMO）精准肿瘤学工作组（POWG）的代表和国际专家通过基于系统评价的方法，确定了病理学和肿瘤学中应用基于人工智能算法进行肿瘤诊断、分子生物标志物检测和癌症预后评估的研究。综合这些发现，以全面概述当前人工智能在癌症病理学中的应用及未来方向。
人工智能工具与数字病理学的整合显著提高了图像分析的准确性和效率，实现了肿瘤的自动检测和分类、预后分子生物标志物的识别以及治疗反应和患者预后的预测。在临床工作流程中采用人工智能仍存在一些障碍，如数据可用性、可解释性和监管考量等。目前尚无IA级或IB级证据支持的基于人工智能的预后或预测生物标志物。人工智能算法的不断进步，特别是基础模型、通用模型和基于Transformer的深度学习，为癌症研究和治疗的未来带来了巨大希望。人工智能还促进了多组学数据的整合，从而实现更精确的患者分层和个性化治疗策略。
人工智能在病理学中的应用不仅有望提高癌症诊断和预后的准确性和效率，还将促进个性化治疗策略的发展。尽管实施障碍仍然存在，但该领域正在进行的研发以及对伦理和监管考量的解决，可能会带来一个人工智能在癌症管理和精准医学中发挥不可或缺作用的未来。预计人工智能在病理学和肿瘤学中的持续发展和应用将重塑癌症护理的格局，开创精准医学和改善患者预后的新时代。
