A multiparametric magnetic resonance imaging model incorporating the relative apparent diffusion coefficient for preoperative discrimination of triple-negative breast cancer.
1/5 보강
[OBJECTIVES] 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 (
- Sensitivity 77.18%
- Specificity 84.6%
APA
Fan H, Shao W, et al. (2026). A multiparametric magnetic resonance imaging model incorporating the relative apparent diffusion coefficient for preoperative discrimination of triple-negative breast cancer.. American journal of translational research, 18(3), 1910-1922. https://doi.org/10.62347/SGZO1989
MLA
Fan H, et al.. "A multiparametric magnetic resonance imaging model incorporating the relative apparent diffusion coefficient for preoperative discrimination of triple-negative breast cancer.." American journal of translational research, vol. 18, no. 3, 2026, pp. 1910-1922.
PMID
42007109 ↗
Abstract 한글 요약
[OBJECTIVES] 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).
[METHODS] 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).
[RESULTS] 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 < 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 < 0.01). The model showed good calibration and high clinical utility in DCA.
[CONCLUSIONS] 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.
[METHODS] 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).
[RESULTS] 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 < 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 < 0.01). The model showed good calibration and high clinical utility in DCA.
[CONCLUSIONS] 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.
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