A multicenter study on preoperative prediction of TNBC based on multi-parameter MRI intratumoral combined with peritumoral radiomics

Motivation: Previous studies on triple-negative breast cancer(TNBC) have primarily focused on the characteristics of the tumor itself, with less emphasis on the surrounding tissue, and have mostly been conducted at a single center using a single sequence of analysis. Goal(s): Multi-sequence MRI intratumoral combined with peritumoral radiomics models can identify TNBC , providing individualized treatment plans for patients and improving their prognosis. Approach: Using image genomics methods, eight predictive models for TNAC were constructed, validated internally and externally, and the optimal model was finally selected. Results: The model constructed based on multiparametric MRI intratumor combined with peritumor radiomics features can better predict TNBC and non-TNBC. Impact: This model can predict TNBC in a non-invasive and early manner, which is of great significance to the treatment and prognosis of patients.

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/10.58530/2025/1407
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

A multicenter study on preoperative prediction of TNBC based on multi-parameter MRI intratumoral combined with peritumoral radiomics

Mingtai Cao, Airu Yang, Xin-Yi 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

A multicenter study on preoperative prediction of TNBC based on multi-parameter MRI intratumoral combined with peritumoral radiomics

Mingtai Cao, Airu Yang, Xin-Yi Liu, Yuntai Cao
article en

Abstract

Motivation: Previous studies on triple-negative breast cancer(TNBC) have primarily focused on the characteristics of the tumor itself, with less emphasis on the surrounding tissue, and have mostly been conducted at a single center using a single sequence of analysis. Goal(s): Multi-sequence MRI intratumoral combined with peritumoral radiomics models can identify TNBC , providing individualized treatment plans for patients and improving their prognosis. Approach: Using image genomics methods, eight predictive models for TNAC were constructed, validated internally and externally, and the optimal model was finally selected. Results: The model constructed based on multiparametric MRI intratumor combined with peritumor radiomics features can better predict TNBC and non-TNBC. Impact: This model can predict TNBC in a non-invasive and early manner, which is of great significance to the treatment and prognosis of patients.

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 63%
Radiomics and Machine Learning in Medical Imaging
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A multicenter study on preoperative prediction of TNBC based on multi-parameter MRI intratumoral combined with peritumoral radiomics — Mingtai Cao, Airu Yang, et al. · 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 (2025) | TGRS Research Map | TGRS