Is there a correlation between signal intensity ratio of 3T MRI and molecular subtypes of breast cancer?

Authors

Yuanping Tao, Hongyan Chao, Yue Ren, Wanjun Zheng, Yuyou Chen, Liang Du, Huanguo Li, Feng Cui

Published in

Radiology and oncology. Jul 04, 2026. Epub Jul 04, 2026.

Abstract

The study aimed to test whether tumoral signal intensity ratio (SIR) and other indicators of 3T MRI provides information related to molecular subtypes of breast cancer.
Between January 2022 and August 2025, 256 patients with breast cancer underwent 3T MRI. MRI morphological features and quantitative parameters (T1 SIR, T2 SIR, mean apparent diffusion coefficient [ADC] from diffusion-weighted imaging [DWI] and tumor diameter) were compared and measured according to molecular subtypes. Logistic regression was performed to find the related MRI parameters and establish combined parameters. A receiver operating characteristic (ROC) analysis was finally performed to test the diagnostic power of multivariate logistic regression model.
263 lesions were considered. Triple-negative (TN) subtype exhibited the highest T2 SIR and lowest T1 SIR (p < 0.05). Mean ADC values in TN were the lowest and highest in human epidermal growth factor receptor 2 (HER2)-enriched type (p < 0.001). Tumor diameter of HER2-enriched was the smallest, and that of triple-negative subtype was the largest (p < 0.001). Independent influencing factors were higher T2 SIR (p = 0.017) and larger tumor diameter (p = 0.011) associated with triple-negative subtype, and T1 SIR (p = < 0.01) was the only quantitative parameter associated with HER2-enriched subtype. The combined parameter (mean ADC + tumor diameter) achieved a largest area under the ROC curve (AUC = 0.781) for separating luminal A subtype.
Quantitative MRI parameters are correlated with the molecular subtypes of breast cancer. Combined parameters incorporating T1 SIR and T2 SIR exhibit potential diagnostic utility for differentiating HER2-enriched and triple-negative subtypes, respectively. T1 SIR and T2 SIR can enrich quantitative descriptors from breast MRI.

PMID:
42400313
Bibliographic data and abstract were imported from PubMed on 04 Jul 2026.

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