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• Clinical Article •
A clinical study on the prediction of Ki-67 expression status in breast cancer by quantitative parameters combined with apparent diffusion coefficient of synthetic MRI
HUANG Yue  LI Feng 

Cite this article as: HUANG Y, LI F. A clinical study on the prediction of Ki-67 expression status in breast cancer by quantitative parameters combined with apparent diffusion coefficient of synthetic MRI[J]. Chin J Magn Reson Imaging, 2025, 16(4): 41-47, 53. DOI:10.12015/issn.1674-8034.2025.04.007.


[Abstract] Objective To explore the relationship between quantitative parameters of synthetic MRI (SyMRI) before and after enhancement and the expression status of Ki-67 antigen in breast cancer, and to evaluate the predictive efficacy of these parameters combined with apparent diffusion coefficient (ADC) in the expression status of Ki-67.Materials and Methods The clinical and imaging data of 163 patients diagnosed with breast cancer at Xiangyang Central Hospital from March 2023 to October 2024 were retrospectively collected. All patients underwent complete MRI examinations and their tumor natures were confirmed by pathological examination. On the GE workstation, quantitative parameter values of SyMRI before and after enhancement were obtained and recorded, including pre-enhancement T1 value (T1-Pre), pre-enhancement T2 value (T2-Pre), pre-enhancement proton density value (PD-Pre), post-enhancement T1 value (T1-Gd), post-enhancement T2 value (T2-Gd), and post-enhancement PD value (PD-Gd). The relative change rates of relaxation time before and after enhancement were calculated and recorded as ΔT1%, ΔT2%, and ΔPD%. According to the expression status of Ki-67, the collected patients were divided into high expression group (≥ 30%) and low expression group (< 30%). Statistical analysis of the data was performed using SPSS 27 software, with P < 0.05 indicating statistical significance. Qualitative data were analyzed using the chi-square test, and quantitative data were analyzed using the Kolmogorov-Smirnov (K-S) test for normal distribution. Independent sample t-test or non-parametric Mann-Whitney U test was used to compare the differences in MRI parameters between the high and low expression groups of Ki-67. Significant variables were included in binary logistic regression analysis, and the DeLong test was used to evaluate the predictive efficacy of the model for the expression status of Ki-67.Results There were statistically significant differences between the two groups in terms of maximum lesion diameter, ADC value, estrogen receptor, progesterone receptor, time-signal intensity curve (TIC), and treatment plan selection (P < 0.05); However, there were no significant differences in age, human epidermal growth factor receptor (HER-2) expression status, lesion margin and shape, enhancement characteristics, breast gland type, and lymph node metastasis. Regarding SyMRI quantitative parameters, there were statistically significant differences between the high and low expression groups in T1-Pre, T2-Pre, T1-Gd, T2-Gd, and ΔT1% (P < 0.05); While PD-Pre, PD-Gd, ΔT2%, and ΔPD% showed no statistically significant differences between the two groups. Further multivariate logistic regression analysis showed that TIC, T1-Gd, and ADC value had significant statistical significance, with AUCs of 0.608, 0.837, and 0.701, respectively; sensitivities of 52%, 89%, and 85%, respectively; and specificities of 68%, 68%, and 46%, respectively. Additionally, a logistic regression prediction model was established by combining T1-Gd, ADC value, and TIC, which achieved an AUC of 0.881 for predicting the expression status of Ki-67, with a sensitivity of 89% and a specificity of 76%.Conclusions This study demonstrates that T1-Gd, as a non-invasive imaging biomarker, can effectively predict the expression level of Ki-67 in breast cancer in SyMRI quantitative analysis. By integrating ADC values and TIC, the constructed combined prediction model significantly improves the accuracy and efficacy of predicting Ki-67 expression levels in breast cancer. This finding provides a new approach and method for non-invasive assessment of breast cancer cell proliferation activity and treatment response.
[Keywords] magnetic resonance imaging；breast cancer；integrated magnetic resonance imaging；cell proliferation nuclear antigen；apparent diffusion coefficient

HUANG Yue1, 2   LI Feng3*  

1 Xiangyang Central Hospital of Wuhan University of Science and Technology, Xiangyang 441021, China

2 School of Medicine, Wuhan University of Science and Technology, Wuhan 430081, China

3 Department of Radiology, Xiangyang Central Hospital, Hubei University of Arts and Sciences, Xiangyang 441021, China

Corresponding author: LI F, E-mail: xfkite@163.com

Conflicts of interest   None.

Received  2025-01-13
Accepted  2025-04-10
DOI: 10.12015/issn.1674-8034.2025.04.007
Cite this article as: HUANG Y, LI F. A clinical study on the prediction of Ki-67 expression status in breast cancer by quantitative parameters combined with apparent diffusion coefficient of synthetic MRI[J]. Chin J Magn Reson Imaging, 2025, 16(4): 41-47, 53. DOI:10.12015/issn.1674-8034.2025.04.007.

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