Research on Predicting the Efficacy of NAC in Breast Cancer Based on a Multisequence MRI Intratumoral Combined Peritumoral Radiomics Model

Motivation: Currently, studies on the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer primarily focus on the internal regions of the lesion. There are fewer studies on the surrounding regions of the tumor, and most of them use single sequences for analysis. Goal(s): This study aims to assess the efficacy of NAC for breast cancer before treatment, providing personalized treatment plans for patients. Approach: Extract radiomics features from the intratumoral and peritumoral regions of breast cancer patients from three centers, construct radiomics models, and select the optimal model. Results: This study can effectively predict the efficacy of NAC in breast cancer. Impact: This study contributes to improving the level of breast cancer diagnosis and treatment.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/1550
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Predicting the Efficacy of NAC in Breast Cancer Based on a Multisequence MRI Intratumoral Combined Peritumoral Radiomics Model

Mingtai Cao, Airu Yang, Xinyi Liu, Yuntai Cao
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Research on Predicting the Efficacy of NAC in Breast Cancer Based on a Multisequence MRI Intratumoral Combined Peritumoral Radiomics Model

Mingtai Cao, Airu Yang, Xinyi Liu, Yuntai Cao
article en

Abstract

Motivation: Currently, studies on the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer primarily focus on the internal regions of the lesion. There are fewer studies on the surrounding regions of the tumor, and most of them use single sequences for analysis. Goal(s): This study aims to assess the efficacy of NAC for breast cancer before treatment, providing personalized treatment plans for patients. Approach: Extract radiomics features from the intratumoral and peritumoral regions of breast cancer patients from three centers, construct radiomics models, and select the optimal model. Results: This study can effectively predict the efficacy of NAC in breast cancer. Impact: This study contributes to improving the level of breast cancer diagnosis and treatment.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 65%
Radiomics and Machine Learning in Medical Imaging
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