Multiple Parameters from Ultrafast Dynamic Contrast-enhanced MRI to Differentiate HER2-Zero, -Low, and -Positive Breast Cancer

Motivation: Accurate differentiation of human epidermal growth factor receptor 2 (HER2) expression status in breast cancer (BC) is essential for selecting appropriate targeted therapies. Current diagnostic methods have limitations in identifying low HER2 expression levels, necessitating more efficient, non-invasive techniques. Goal(s): To evaluate the feasibility of using ultrafast dynamic contrast-enhanced MRI (UF-DCE MRI) to distinguish HER2 expression statuses in BC. Approach: 398 histopathologically-confirmed BC patients underwent UF-DCE MRI. Five UF-DCE MRI-derived parameters were analyzed to assess their diagnostic performance. Results: UF-DCE MRI parameters showed significant differences between HER2-Zero, HER2-Low, and HER2-Positive subtypes, though diagnostic performance was moderate. Impact: This research demonstrates that UF-DCE MRI could provide a non-invasive method for distinguishing HER2 expression levels in BC, aiding in selecting appropriate therapies. It has the potential to improve personalized treatment approaches and influence future clinical practice in HER2-targeted therapies.

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/10.58530/2025/1682
Primary Topic
MRI in cancer diagnosis
Type
article
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article

Multiple Parameters from Ultrafast Dynamic Contrast-enhanced MRI to Differentiate HER2-Zero, -Low, and -Positive Breast Cancer

Jiuquan Zhang, Ying Cao, Huifang Chen, Xiaoxia Wang 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
MRI in cancer diagnosis
article

Multiple Parameters from Ultrafast Dynamic Contrast-enhanced MRI to Differentiate HER2-Zero, -Low, and -Positive Breast Cancer

Jiuquan Zhang, Ying Cao, Huifang Chen, Xiaoxia Wang, Ting Yin, Yao Huang
article en

Abstract

Motivation: Accurate differentiation of human epidermal growth factor receptor 2 (HER2) expression status in breast cancer (BC) is essential for selecting appropriate targeted therapies. Current diagnostic methods have limitations in identifying low HER2 expression levels, necessitating more efficient, non-invasive techniques. Goal(s): To evaluate the feasibility of using ultrafast dynamic contrast-enhanced MRI (UF-DCE MRI) to distinguish HER2 expression statuses in BC. Approach: 398 histopathologically-confirmed BC patients underwent UF-DCE MRI. Five UF-DCE MRI-derived parameters were analyzed to assess their diagnostic performance. Results: UF-DCE MRI parameters showed significant differences between HER2-Zero, HER2-Low, and HER2-Positive subtypes, though diagnostic performance was moderate. Impact: This research demonstrates that UF-DCE MRI could provide a non-invasive method for distinguishing HER2 expression levels in BC, aiding in selecting appropriate therapies. It has the potential to improve personalized treatment approaches and influence future clinical practice in HER2-targeted therapies.

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%
MRI in cancer diagnosis
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Multiple Parameters from Ultrafast Dynamic Contrast-enhanced MRI to Differentiate HER2-Zero, -Low, and -Positive Breast Cancer — Jiuquan Zhang, Ying Cao, 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