Multiregional MRI-based deep learning radiomics to predict axillary response after neoadjuvant chemotherapy in breast cancer patients

Combining intratumoral and 5-mm peritumoral region radiomics had the highest predictive efficiency for axillary pCR after NAC in breast cancer. The deep learning radiomics nomogram based on intra- and peritumoral regions outperformed the clinical model. The proposed model could provide a noninvasive and easy-to-use tool to offer decision support for optimizing treatments.

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Publication Details

Journal
Insights into Imaging
Published
2026-01-26
DOI
https://doi.org/10.1186/s13244-025-02193-1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Multiregional MRI-based deep learning radiomics to predict axillary response after neoadjuvant chemotherapy in breast cancer patients

Ting Zhao, Chenying Lu, Shuiwei Xia, Guihan Lin et al.
Insights into Imaging
Radiomics and Machine Learning in Medical Imaging
article

Multiregional MRI-based deep learning radiomics to predict axillary response after neoadjuvant chemotherapy in breast cancer patients

Ting Zhao, Chenying Lu, Shuiwei Xia, Guihan Lin, Changsheng Shi, Min Xu, Yongjun Chen, Yi Zhou, Zhiyi Peng, Weiyue Chen
article en

Abstract

Combining intratumoral and 5-mm peritumoral region radiomics had the highest predictive efficiency for axillary pCR after NAC in breast cancer. The deep learning radiomics nomogram based on intra- and peritumoral regions outperformed the clinical model. The proposed model could provide a noninvasive and easy-to-use tool to offer decision support for optimizing treatments.

Insights into ImagingVol. 17(1)
Wenzhou Medical University (CN), Ruian People's Hospital (CN), Lishui Central Hospital (CN), Wenzhou Institute of Technology Testing & Calibration (CN), First Affiliated Hospital Zhejiang University (CN)
Openalex Percentile: Top 79%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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Multiregional MRI-based deep learning radiomics to predict axillary response after neoadjuvant chemotherapy in breast cancer patients — Ting Zhao, Chenying Lu, et al. · Insights into Imaging (2026) | TGRS Research Map | TGRS