Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
366-06-001 ISMRM Abstract

Predicting Neoadjuvant Chemotherapy Response Pattern in Luminal B Breast Cancer Using DCE-MRI and IVIM

Primary: Analysis Methods - Classification and Prediction
Secondary: Analysis Methods - Data Processing
366-06-001 · Body Diffusion MRI Applications · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row G
Keywords: Data Analysis Diagnosis/Prediction Breast cancer
Accepted
Shuo Wang 1, Moyun Zhang1, Xinyue Yin1, Zhitian Guo1, Lina Zhang1, Haonan Guan2
1Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
2GE Healthcare, MR Research China, Beijing, 100176, P.R. China, China
Presenting Author: Shuo Wang

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Sun S, Zhou J, Bai Y, et al. Role of oedema and shrinkage patterns for prediction of response to neoadjuvant chemotherapy and survival outcomes in luminal breast cancer. Clin Radiol. 2024;79(8):e1010-e1020. Doi:10.1016/j.crad.2024.04.021 [doi]
2. Huang Y, Song X, Chen Y, et al. Intratumoral Microbiome-related MRI Model for Predicting Breast Cancer Shrinkage Pattern Following Neoadjuvant Therapy. Radiology. 2025;316(2):e243545. Doi:10.1148/radiol.243545 [doi]
3. Chen X, Luo Y, Xie Z, Wen Y, Mou F, Zeng W. Prediction of neoadjuvant chemotherapy efficacy in breast cancer: integrating multimodal imaging and clinical features. BMC Med Imaging. 2025;25(1):118. Published 2025 Apr 14. Doi:10.1186/s12880-025-01631-2 [doi]
4. Gong X, Wang X, Wang L, et al. Comparing Multi-b-Value Diffusion MRI Models for Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer. Radiology. 2025;316(1):e242969. Doi:10.1148/radiol.242969 [doi]
5. Huang YH, Shi ZY, Zhu T, et al. Longitudinal MRI-Driven Multi-Modality Approach for Predicting Pathological Complete Response and B Cell Infiltration in Breast Cancer. Adv Sci (Weinh). 2025;12(12):e2413702. Doi:10.1002/advs.202413702 [doi]
6. Liu C, Huang X, Chen X, et al. Use of Pretreatment Multiparametric MRI to Predict Tumor Regression Pattern to Neoadjuvant Chemotherapy in Breast Cancer. Acad Radiol. 2023;30 Suppl 2:S62-S70. Doi:10.1016/j.acra.2023.02.024 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/366-06-001