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Updated: Jan 6, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Whole-lesion histogram analysis of multi-model diffusion-weighted imaging for characterization and molecular
Yuan Yuan1, Manhua Huang1, Jie Peng1
1Department of Radiology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Purpose:
To evaluate the value of whole-lesion histogram analysis derived from mono-exponential, bi-exponential, and stretched-exponential DWI models in differentiating benign from malignant breast lesions and exploring molecular subtypes.
Material And Methods:
This retrospective study included 112 patients with 90 malignant lesions (17 Luminal A, 39 Luminal B, 18 HER2-positive, 10 triple-negative, and 6 undetermined) and 22 benign lesions, all examined with 1.5 T MRI. Histogram parameters-apparent diffusion coefficient (ADC), true diffusion (Dt), pseudo-diffusion (Dp), perfusion fraction (f), distributed diffusion coefficient (DDC), and heterogeneity index (alpha)-were analyzed using the Mann-Whitney U test, Kruskal-Wallis test, logistic regression, ROC analysis, the DeLong test, and the chi-square test.
Results:
Histogram parameters from all models showed significant differences between benign and malignant lesions, with high diagnostic performance (AUC range: 0.898-0.938). However, combining the models did not significantly improve the AUC (p > 0.05). In molecular subtype analyses, DDC_75% differed significantly between Luminal A and triple-negative subtypes (p = 0.035); Dt_50%, Dt_75%, and DDC_75% distinguished Luminal B from triple-negative subtypes (p = 0.016, 0.021, and 0.041, respectively); and ADC_kurtosis and DDC_kurtosis showed significant differences between HER2-positive and triple-negative subtypes (p = 0.021 and 0.029, respectively). ROC analysis indicated variable diagnostic efficacy among parameters across molecular subtypes, and model combinations did not enhance AUC values.
Conclusion:
Whole-lesion histogram analysis based on multi-model DWI shows potential for characterizing breast lesions. These exploratory findings, derived from an imbalanced single-center cohort, require further validation in larger prospective studies before clinical application.
