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Updated: Sep 23, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
The combination of cyclin D1 and MRI radiomics parameters improves breast cancer diagnosis and NACT efficacy
Yufei Fu1, Yizhi Shi1, Zhen Wang1
1Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Department of Radiology, Hubei, China.
Background:
The purpose of this study is to evaluate the combined diagnostic performance of Cyclin D1 and magnetic resonance imaging (MRI) parameters in breast cancer (BC), while also assessing their ability to forecast treatment response to neoadjuvant chemotherapy (NACT), so as to provide evidence for individualized treatment strategies.
Methods:
A total of 154 BC patients and 148 healthy women matched with BC patients in age and BMI were enrolled in this study. Peripheral blood Cyclin D1 quantification utilized enzyme-linked immunosorbent assay (ELISA), and CA15-3 and CA27.29 (both tumor markers) measurements were made using automated electrochemiluminescence immunoassay. Magnetic resonance imaging (MRI) was conducted to obtain dynamic contrast-enhanced scans, from which radiomics parameters (PSIER, TSICS, ADC) were derived. Diagnostic accuracy for BC and predictive value for chemotherapy response were evaluated through correlation analysis (Pearson), receiver operating characteristic (ROC) curves, and multivariate regression modeling.
Results:
Cyclin D1 levels were elevated in BC patients compared to healthy controls and showed a positive connection with CA15-3 and CA27.29 (P< 0.05). The diagnostic performance of Cyclin D1 alone yielded an AUC of 0.830, whereas a combined model incorporating MRI parameters (PSIER, TSICS, and ADC) significantly improved discrimination (AUC = 0.935, sensitivity 86.36%, specificity 87.84%). During NACT, Cyclin D1 levels declined dynamically. A predictive model integrating Cyclin D1 and imaging biomarkers achieved an AUC of 0.775 for identifying poor NACT responders (sensitivity 88.37%, specificity 56.76%).
Conclusions:
The combination of Cyclin D1 and MRI parameters enhances both BC diagnostic accuracy and NACT efficacy prediction.
