Romeo Valeria, Accardo Giuseppe, Perillo Teresa, Basso Luca, Garbino Nunzia, Nicolai Emanuele, Maurea Simone, Salvatore Marco
Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Naples, Italy.
Department of Breast Surgery, Centro di Riferimento Oncologico della Basilicata (IRCCS-CROB), Rionero in Vulture, 85028 Potenza, Italy.
Cancers (Basel). 2021 Jul 14;13(14):3521. doi: 10.3390/cancers13143521.
Neoadjuvant chemotherapy (NAC) is becoming the standard of care for locally advanced breast cancer, aiming to reduce tumor size before surgery. Unfortunately, less than 30% of patients generally achieve a pathological complete response and approximately 5% of patients show disease progression while receiving NAC. Accurate assessment of the response to NAC is crucial for subsequent surgical planning. Furthermore, early prediction of tumor response could avoid patients being overtreated with useless chemotherapy sections, which are not free from side effects and psychological implications. In this review, we first analyze and compare the accuracy of conventional and advanced imaging techniques as well as discuss the application of artificial intelligence tools in the assessment of tumor response after NAC. Thereafter, the role of advanced imaging techniques, such as MRI, nuclear medicine, and new hybrid PET/MRI imaging in the prediction of the response to NAC is described in the second part of the review. Finally, future perspectives in NAC response prediction, represented by AI applications, are discussed.
新辅助化疗（NAC）正成为局部晚期乳腺癌的标准治疗方法，旨在在手术前缩小肿瘤大小。不幸的是，一般不到30%的患者能达到病理完全缓解，约5%的患者在接受NAC时出现疾病进展。准确评估NAC的反应对于后续的手术规划至关重要。此外，早期预测肿瘤反应可以避免患者接受无效化疗疗程的过度治疗，而这些化疗并非没有副作用和心理影响。在这篇综述中，我们首先分析和比较传统和先进成像技术的准确性，并讨论人工智能工具在评估NAC后肿瘤反应中的应用。此后，综述的第二部分描述了先进成像技术，如MRI、核医学和新型PET/MRI融合成像在预测NAC反应中的作用。最后，讨论了以人工智能应用为代表的NAC反应预测的未来前景。
