Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.

Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes.

Déclaration de conflit d'intérêts

M.I. received honoraria from Agilent Technologies Denmark ApS and Diaceutics PLC. C.S. received honoraria for consulting, advisory roles, speaker bureaus, and/or research grants from Bristol Myers Squibb, Astra Zeneca, Daiichi-Sankyo, Gilead, Roche SPA, Novartis, Menarini, Veracyte Inc. G.d.A. received honoraria for consulting, advisory roles, and speaker bureaus from Merck Sharp & Dohme (MSD), Novartis, AstraZeneca, Roche, and Daiichi Sankyo. G.C. received honoraria from Roche and others from Novartis, Lilly, Pfizer, Astra Zeneca, Daichii Sankyo, Ellipsis, Veracyte, Exact Science, Celcuity, Merck, BMS, Gilead, Sanofi, Menarini. N.F. received honoraria for consulting, advisory roles, speaker bureaus, travel, and/or research grants from Merck Sharp & Dohme (MSD), Merck, Novartis, AstraZeneca, Roche, Menarini, Daiichi Sankyo, GlaxoSmithKline (GSK), Gilead, Adicet Bio, Sermonix, Reply, Veracyte Inc., Leica Biosystems, and Lilly. These companies had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. All other authors have no relevant financial or non-financial interests to disclose.