A multiparametric magnetic resonance imaging model incorporating the relative apparent diffusion coefficient for...

To explore the value of a multiparametric MRI combined model based on morphology, hemodynamics, and apparent diffusion coefficient (ADC) in differentiating triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (non-TNBC).

A retrospective study was conducted on 213 breast cancer patients (64 TNBC, 149 non-TNBC). Morphological, hemodynamic, mean apparent diffusion coefficient (ADC), and relative apparent diffusion coefficient (rADC) features were compared. Feature selection was performed using LASSO, and a multiparametric combined model was constructed using logistic regression. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and DeLong tests. Calibration and clinical utility were evaluated using the Hosmer-Lemeshow test, calibration curves, and decision curve analysis (DCA).

TNBC tended to present as unifocal lesions with hyperintensity on T2WI. They also frequently showed cystic necrosis, peritumoral edema, and Type II/III curve patterns (all P < 0.05). The diagnostic performance of rADC1 (AUC = 0.669) was better than that of mean ADC and rADC2. Multifocality/multicentricity, peritumoral edema, and rADC1 were independent predictors of TNBC. The combined model achieved an AUC of 0.772, 67.19% sensitivity, 77.18% specificity, and 84.6% negative predictive value, performing better than single-parameter models (all P < 0.01). The model showed good calibration and high clinical utility in DCA.

The combined model - constructed based on multifocality/multicentricity, peritumoral edema, and the rADC1 value - can effectively predict TNBC preoperatively, has good discrimination, calibration, and clinical utility, and provides an important imaging reference basis for accurately identifying TNBC and formulating individualized diagnosis and treatment plans.