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Abstract #3882

Quantitative Evaluation of Multi-dimensional Diffusion MRI in Breast Cancer Diagnosis and Molecular Subtypes Prediction

Yuxi Tao1, Jialu Zhang2, Junxiong Xie1, Zuwu Ai1, and Yaqin Zhang1
1the Fifth Affiliated Hospital of Sun Yat-sen University, zhuhai, China, 2MR Research, GE Healthcare, Beijing, China

Synopsis

Keywords: Microstructure, Cancer

Motivation: Breast cancer is a leading cause of cancer-related deaths and is highly heterogeneous, requiring precise subtype classification for personalized treatment.

Goal(s): To assess the capability of multi-dimensional diffusion MRI (MD-dMRI) in differentiating between benign and malignant breast lesions and identifying molecular subtypes of breast cancer.

Approach: A prospective study involving 76 patients with suspected breast lesions was conducted. MD-dMRI scans were performed, and quantitative parameters reflecting tissue heterogeneity were analyzed.

Results: MD-dMRI parameters showed significant differentiation between benign and malignant lesions. The CMD and MKI parameters provided valuable insights into molecular subtypes, supporting personalized therapeutic strategies.

Impact: MD-dMRI enhances breast cancer diagnosis and subtype identification, improving precision medicine. It offers non-invasive, accurate insights into tumor heterogeneity, guiding personalized treatment and potentially improving patient outcomes and survival rates.

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