Comparison of Continuous-Time Random Walk and Fractional Order Calculus Diffusion Models for Preoperative Breast Lesion Characterization: Diagnosis, Biomarker Prediction and Molecular Subtyping.

BACKGROUND: Accurate preoperative characterization of breast lesions is important for individualized management. The conventional monoexponential (Mono) model has limited ability to capture the complex microstructure of lesions. Non-Gaussian diffusion models, including continuous-time random walk (CTRW) and fractional-order calculus (FROC), may overcome this limitation, but their value in predicting biomarkers and molecular subtypes remains unclear. PURPOSE: To comprehensively evaluate the diagnostic utility of the Mono, CTRW, and FROC models and their derived parameters for preoperative breast lesion characterization. STUDY TYPE: Prospective. POPULATION: 189 women (mean age, 47.4 ± 11.2 years) with 238 histopathologically confirmed breast lesions (138 benign, 100 malignant). FIELD STRENGTH/SEQUENCE: 3.0-T MRI; single-shot spin-echo echo-planar imaging for multi-b-value diffusion-weighted imaging (10 b-values ranging from 0 to 3000 s/mm2). ASSESSMENT: Diffusion parameters were extracted from whole-lesion volumes generated from slice-wise segmentations by two independent, blinded breast radiologists. Multiparameter joint models were constructed using logistic regression. STATISTICAL TESTS: Model performance was evaluated using repeated 5-fold cross-validation and patient-level cluster bootstrap for AUC comparisons. A two-sided p < 0.05 was considered statistically significant, and Bonferroni-adjusted thresholds were applied for multiple comparisons. RESULTS: For benign-malignant differentiation, the CTRW and FROC models yielded higher cross-validated AUCs than the Mono model (0.928, 0.918, and 0.865, respectively). For prognostic biomarkers, the FROC model achieved optimal predictive performance for HER2 status (AUC = 0.836). For molecular subtyping, the CTRW model significantly outperformed the Mono model in distinguishing HER2-positive lesions (AUC = 0.848 vs. 0.674); however, all models showed limited performance for triple-negative lesions, with all AUCs ≤ 0.502. DATA CONCLUSION: Non-Gaussian diffusion models, particularly the CTRW model, provide additional value beyond the Mono model for preoperative breast lesion characterization. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.