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journal article·2025-03Open access

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

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

Advanced Science· Volume 12· Issue 12
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Abstract

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 resonance imaging (MRI) spatial habitat radiomics, transcriptomics, and single‐cell RNA sequencing for predicting pCR. By analyzing tumor subregions on multi‐timepoint MRI, the model captures dynamic intra‐tumoral heterogeneity during NAT. It shows superior performance over traditional radiomics, with areas under the curve of 0.863, 0.813, and 0.888 in the external validation, immunotherapy, and multi‐omics cohorts, respectively. Subgroup analysis shows its robustness across varying molecular subtypes and clinical stages. Transcriptomic and single‐cell RNA sequencing analysis reveals that high model scores correlate with increased immune activity, notably elevated B cell infiltration, indicating the biological basis of the imaging model. The integration of imaging and molecular data demonstrates promise in spatial habitat radiomics to monitor dynamic changes in tumor heterogeneity during NAT. In clinical practice, this study provides a noninvasive tool to accurately predict pCR, with the potential to guide treatment planning and improve breast‐conserving surgery rates. Despite promising results, the model requires prospective validation to confirm its utility across diverse patient populations and clinical settings.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Radiomics and Machine Learning in Medical Imaging · Colorectal Cancer Surgical Treatments · Medical Imaging Techniques and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Breast Cancer Cancer Center Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University No. 106 Zhongshan Second Road, Yuexiu District Guangzhou Guangdong Province 510080 China

Department of Biochemistry and Molecular Biology School of Basic Medical Sciences Southern Medical University Guangzhou Guangdong Province 510515 China

Guangdong Key Laboratory of Single Cell Technology and Application Southern Medical University, Guangzhou Guangdong Province 510515 China

The Department of General Surgery Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University Xihu District Hangzhou Zhejiang Province 310000 China

Galactophore Department Jingzhou Hospital Affiliated to Yangtze University Shashi District Jingzhou 434000 China

Department of Biostatistics Harvard T.H. Chan School of Public Health Boston MA 02115 USA

Breast Center Cancer Hospital of Shantou University Medical College Jinping District Shantou Guangdong Province 515000 China

Clinical research center & Breast disease diagnosis and treatment center Shantou Central Hospital No. 114 Waima Road, Jinping District Shantou Guangdong Province 515000 China

Breast Disease Center, The First Affiliated Hospital Sun Yat‐sen University No. 58 Zhongshan Second Road, Yuexiu District Guangzhou Guangdong Province 510080 China

Department of Radiology The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University Huaiyin District Huaian Jiangsu Province 223001 China

Department of Artificial Intelligence Medicine Graduate School of Medicine Chiba University Chiba 263‐8522 Japan

Department of Medical Imaging The First Hospital of Qinhuangdao Haigang District Qinhuangdao Hebei Province 066000 China

Department of Radiology The First Affiliated Hospital of Jinan University No. 613 Huangpu West Road, Tianhe District Guangzhou Guangdong 510627 China

Department of Pathology The Second People's Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University No. 29 Xinglong Lane Changzhou Jiangsu Province 213164 China

Funding

National Natural Science Foundation of China · High-level Hospital Construction Project of Guangdong Provincial People's Hospital · Basic and Applied Basic Research Foundation of Guangdong Province · Fundo para o Desenvolvimento das Ciências e da Tecnologia

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