Longitudinal MRI‐Driven Multi‐Modality Approach for Predicting Pathological Complete Response and B Cell Infiltration in Breast Cancer

Abstract Accurately predicting pathological complete response (pCR) to neoadjuvant treatment (NAT) in breast cancer remains challenging due to tumor heterogeneity. This study enrolled 2279 patients across 12 centers and develops a novel multi‐modality model integrating longitudinal magnetic resonanc...

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Detalles Bibliográficos

Principais autores:	Yu‐Hong Huang, Zhen‐Yi Shi, Teng Zhu, Tian‐Han Zhou, Yi Li, Wei Li, Han Qiu, Si‐Qi Wang, Li‐Fang He, Zhi‐Yong Wu, Ying Lin, Qian Wang, Wen‐Chao Gu, Chang‐Cong Gu, Xin‐Yang Song, Yang Zhou, Dao‐Gang Guan, Kun Wang
Formato:	Artigo
Idioma:	Inglês
Publicado:	Wiley 2025-03-01
Series:	Advanced Science
Assuntos:	artificial intelligence breast cancer medical imaging multi‐omics analysis neoadjuvant treatment
Acceso en liña:	https://doi.org/10.1002/advs.202413702
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