Preliminary study on DCE-MRI radiomics analysis for differentiation of HER2-low and HER2-zero breast cancer.

Autor:	Yin L; Department of Breast Surgery, Jiangsu University Affiliated People's Hospital, Zhenjiang, China.; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China., Zhang Y; School of Medical Imaging, Jiangsu University, Zhenjiang, China.; Department of Radiology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Wei X; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China.; Department of Pathology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Shaibu Z; School of Medicine, Jiangsu University, Zhenjiang, Jiangsu, China., Xiang L; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China.; Department of Radiology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Wu T; Department of Pathology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Zhang Q; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China.; Department of Ultrasound, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Qin R; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China.; Department of Medical Oncology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China., Shan X; Zhenjiang Clinical Medical College of Nanjing Medical University, Zhenjiang, China.; Department of Radiology, Jiangsu University Affiliated People's Hospital, Zhenjiang, China.
Jazyk:	angličtina
Zdroj:	Frontiers in oncology [Front Oncol] 2024 Aug 15; Vol. 14, pp. 1385352. Date of Electronic Publication: 2024 Aug 15 (Print Publication: 2024).
DOI:	10.3389/fonc.2024.1385352
Abstrakt:	Purpose: This study aims to evaluate the utility of radiomic features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in distinguishing HER2-low from HER2-zero breast cancer. Patients and Methods: We retrospectively analyzed 118 MRI cases, including 78 HER2-low and 40 HER2-zero patients confirmed by immunohistochemistry or fluorescence in situ hybridization. From each DCE-MRI case, 960 radiomic features were extracted. These features were screened and reduced using intraclass correlation coefficient, Mann-Whitney U test, and least absolute shrinkage to establish rad-scores. Logistic regression (LR) assessed the model's effectiveness in distinguishing HER2-low from HER2-zero. A clinicopathological MRI characteristic model was constructed using univariate and multivariate analysis, and a nomogram was developed combining rad-scores with significant MRI characteristics. Model performance was evaluated using the receiver operating characteristic (ROC) curve, and clinical benefit was assessed with decision curve analysis. Results: The radiomics model, clinical model, and nomogram successfully distinguished between HER2-low and HER2-zero. The radiomics model showed excellent performance, with area under the curve (AUC) values of 0.875 in the training set and 0.845 in the test set, outperforming the clinical model (AUC = 0.691 and 0.672, respectively). HER2 status correlated with increased rad-score and Time Intensity Curve (TIC). The nomogram outperformed both models, with AUC, sensitivity, and specificity values of 0.892, 79.6%, and 82.8% in the training set, and 0.886, 83.3%, and 90.9% in the test set. Conclusions: The DCE-MRI-based nomogram shows promising potential in differentiating HER2-low from HER2-zero status in breast cancer patients. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2024 Yin, Zhang, Wei, Shaibu, Xiang, Wu, Zhang, Qin and Shan.)
Databáze:	MEDLINE
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