Time-Dependent Diffusion MRI-Based Microstructural Mapping for Characterizing HER2-Zero, -Low, -Ultra-Low, and -Positive Breast Cancer.

BACKGROUND

With breast cancer treatment advances, accurate non-invasive methods are needed to distinguish its human epidermal growth factor receptor 2 (HER2) subtypes. Recently developed time-dependent diffusion MRI (t-dMRI) has potential in characterizing cellular tissue microstructures in breast cancer. However, its role in identifying HER2 subtypes is unknown.

PURPOSE

To investigate the feasibility of t-dMRI-based microstructural histogram parameters for characterizing properties of four HER2 subtypes in breast cancer.

STUDY TYPE

Prospective.

POPULATION

Four hundred ninety-five participants with invasive breast cancer (18 HER2-zero, 49 -ultralow, 243 -low and 185 -positive).

FIELD STRENGTH/SEQUENCE: 3-T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences for t-dMRI.

ASSESSMENT

The HER2 status was categorized as HER2-zero, -ultralow, -low, or -positive by immunohistochemistry and fluorescence in situ hybridization. The t-dMRI data were fitted using the IMPULSED method. Tumors were identified on dynamic contrast-enhanced MRI and delineated on the PGSE image (b = 0 s/mm). Forty-nine histogram parameters were extracted from the tumor, including four microstructural maps (diameter, intracellular fraction, extracellular diffusivity, cellularity) and three apparent diffusion coefficient maps.

STATISTICAL TESTS

Histogram parameters were analyzed via one-way analysis of variance followed by pairwise t tests with Bonferroni correction. The Boruta method selected the significant parameters for each HER2 subtype. The predictive performance was assessed through area under the curve (AUC). A p value < 0.05 was considered statistically significant.

RESULTS

Thirty-two histogram parameters showed significant differences among the four HER2 subgroups. Four models were constructed, which achieved high performance for distinguishing HER2-positive versus negative (AUC of 0.85), HER2-positive versus low (AUC of 0.87), and HER2-low versus immunohistochemistry 0 (AUC of 0.81), along with moderate performance for distinguishing HER2-zero versus -ultralow (AUC of 0.77).

DATA CONCLUSION

Selected t-dMRI-derived histogram parameters may be applicable for identifying HER2 subtypes in breast cancer.

TECHNICAL EFFICACY STAGE