Keywords: fMRI Analysis, Breast, Breast cancer;HER2;IVIM
Motivation: This study aimed to predict HER2 expression states in breast cancer patients using IVIM imaging, offering valuable guidance for anti-HER2 treatment.
Goal(s): To categorize patients into HER2-positive, HER2-low, and HER2-zero groups, analyze IVIM parameters, and assess their relationship with clinicopathological features.
Approach: 67 breast cancer patients were retrospectively analyzed, with IVIM imaging and data collection. Statistical tests were employed to compare the groups.
Results: While no significant differences emerged in clinicopathological features, ADCfast values differed significantly. Both HER2-positive and HER2-low subgroups exhibited higher ADCfast values than HER2-zero cases. ADC, ADCslow, and f showed no significant variations.
Impact: This study demonstrates that ADCfast can predict HER2 expression noninvasively, assisting in personalized treatment planning and prognosis assessment for breast cancer patients pre-surgery, providing valuable insights for clinical decision-making.
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