MRI-based Histopathological Imaging Features Predict Molecular Subtypes of Breast Cancer

Introduction: This study aimed to investigate the correlation between magnetic resonance imaging (MRI) characteristics and molecular subtypes of breast carcinoma. Methods: A retrospective analysis was carried out on 194 breast cancer patients who underwent preoperative MRI. Pathological confirmation and molecular subtyping were performed on postoperative specimens. Preoperative MRI features of the lesions were evaluated. Univariate and multivariate logistic regression analyses were employed to identify MRI features associated with each molecular subtype. Results: A total of 194 breast cancer patients who underwent preoperative MRI and surgical treatment were included, with a mean age of 52.31 ± 12.08 years. Invasive ductal carcinoma was the predominant diagnosis (94.84%), and the expression rates of ER, PR, and HER2 were 58.76%, 55.67%, and 35.05%, respectively. The Ki-67 index was >20% in 70.62% of patients. Luminal B (HER2−) was the most common molecular subtype (33.51%). Significant differences were observed in lesion morphology, T2-weighted signal intensity, enhancement pattern, and type across the five molecular subtypes, though delayed-phase enhancement kinetics showed no significant variation. Logistic regression indicated that low T2WI signal and restricted diffusion were associated with Luminal A, while mass-like morphology and delayed-phase washout were predictors of Luminal B. Non-Mass Enhancement (NME) and rapid early enhancement were linked to HER2-enriched tumors, and unifocal, high T2WI signal, delayed-phase washout, and irregular margins were characteristic of triple-negative breast cancer. Conclusion: Distinct MRI features were found to be associated with specific molecular subtypes of breast cancer, providing valuable insights for subtypespecific diagnosis and therapeutic strategy formulation.

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Journal
Current Medical Imaging Formerly Current Medical Imaging Reviews
Published
2025-12-03
DOI
https://doi.org/10.2174/0115734056411259251028093038
Primary Topic
MRI in cancer diagnosis
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article
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article

MRI-based Histopathological Imaging Features Predict Molecular Subtypes of Breast Cancer

Heng Zhang, Yinfeng Qian
Current Medical Imaging Formerly Current Medical Imaging Reviews
MRI in cancer diagnosis
article

MRI-based Histopathological Imaging Features Predict Molecular Subtypes of Breast Cancer

Heng Zhang, Yinfeng Qian
article en

Abstract

Introduction: This study aimed to investigate the correlation between magnetic resonance imaging (MRI) characteristics and molecular subtypes of breast carcinoma. Methods: A retrospective analysis was carried out on 194 breast cancer patients who underwent preoperative MRI. Pathological confirmation and molecular subtyping were performed on postoperative specimens. Preoperative MRI features of the lesions were evaluated. Univariate and multivariate logistic regression analyses were employed to identify MRI features associated with each molecular subtype. Results: A total of 194 breast cancer patients who underwent preoperative MRI and surgical treatment were included, with a mean age of 52.31 ± 12.08 years. Invasive ductal carcinoma was the predominant diagnosis (94.84%), and the expression rates of ER, PR, and HER2 were 58.76%, 55.67%, and 35.05%, respectively. The Ki-67 index was >20% in 70.62% of patients. Luminal B (HER2−) was the most common molecular subtype (33.51%). Significant differences were observed in lesion morphology, T2-weighted signal intensity, enhancement pattern, and type across the five molecular subtypes, though delayed-phase enhancement kinetics showed no significant variation. Logistic regression indicated that low T2WI signal and restricted diffusion were associated with Luminal A, while mass-like morphology and delayed-phase washout were predictors of Luminal B. Non-Mass Enhancement (NME) and rapid early enhancement were linked to HER2-enriched tumors, and unifocal, high T2WI signal, delayed-phase washout, and irregular margins were characteristic of triple-negative breast cancer. Conclusion: Distinct MRI features were found to be associated with specific molecular subtypes of breast cancer, providing valuable insights for subtypespecific diagnosis and therapeutic strategy formulation.

Current Medical Imaging Formerly Current Medical Imaging ReviewsVol. 21
Anhui Medical University (CN), First Affiliated Hospital of Anhui Medical University (CN)
Good health and well-being
Openalex Percentile: Top 29%
MRI in cancer diagnosis
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