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Clinical Article
Histogram features of quantitative parameters from synthetic MRI and ADC map in predicting the expression of Ki-67 in breast cancer
LI Fangzheng  LI Qin  WU Shasha  SUN Shengjun  YU Haitong  CHEN Yongsheng  NIU Qingliang 

Cite this article as: Li FZ, Li Q, Wu SS, et al. Histogram features of quantitative parameters from synthetic MRI and ADC map in predicting the expression of Ki-67 in breast cancer[J]. Chin J Magn Reson Imaging, 2022, 13(7): 29-34, 67. DOI:10.12015/issn.1674-8034.2022.07.006.

[Abstract] Objective To evaluate the value of the histogram features of quantitative parameters from synthetic MRI and apparent diffusion coefficient (ADC) in predicting the expression of Ki-67 in breast cancer.Materials and Methods The clinical and imaging data of 146 patients with breast cancer confirmed by pathology in our hospital from December 2019 to March 2021 were retrospectively analyzed. All patients underwent MRI routine sequence imaging, dynamic contrast-enhanced MRI (DCE-MRI) and synthetic MRI sequence scan imaging before biopsy or surgery. The histogram features of the quantitative parameters T1、T2、proton density (PD) of synthetic MRI and ADC values were extracted by PyRadiomics software. According to the expression of Ki-67, breast cancer patients were divided into high expression group (≥30%) and low expression group (<30%). The χ2 test, independent sample t-test or Mann-Whitney U test were used to compare the differences of clinical and pathological characteristics, the histogram features of synthetic MRI quantitative parameter maps (T1-mapping, T2-mapping, PD-mapping) and ADC map between the two groups. Logistic regression analysis was used to analyze the relationship between the expression status of Ki-67 in breast cancer and quantitative parameters of MRI, and drawn the receiver operating characteristic (ROC) curve, calculated the area under curve (AUC) to compare the predictive efficacy of each histogram feature in predicting the expression status of Ki-67.Results Univariate logistic analysis showed that there were no significant differences in the histogram characteristics of ADC map, clinical and pathological characteristics between the high and low expression groups of Ki-67 (age, P=0.13; maximum diameter, P=0.09; shape, P=0.94; border, P=0.23; reinforcement mode, P=0.13; fibrous gland type, P=0.26). There was statistically significant difference in T1- mean, T1-10th percentile, T2- mean, T2-10th percentile, PD-entropy, and PD-kurtosis between the high and low expression groups Ki-67 in breast cancer (P<0.01). Multivariate logistic analysis showed that T1-10th percentile and T2-10th percentile were independent predictors for Ki-67 expression states. The AUC of predicting Ki-67 expression by the model constructed by the two parameters was 0.809, with the sensitivity of 64.8%, the specificity of 87.5% and the accuracy of 72.8%.Conclusions The quantitative parameters of synthetic MRI can help predict the expression of Ki-67 in breast cancer and provide an effective auxiliary diagnosis method for preoperative non-invasive evaluation of tumor proliferation.
[Keywords] breast cancer;magnetic resonance imaging;quantitative;synthetic magnetic resonance imaging;Ki-67

LI Fangzheng1   LI Qin2   WU Shasha2   SUN Shengjun1   YU Haitong1   CHEN Yongsheng2   NIU Qingliang2*  

1 School of Medical Imaging, Weifang Medical College, Weifang 261053, China

2 Center of Medical Imaging, Weifang Traditional Chinese Medicine Hospital, Weifang 261041, China

NIU QL, E-mail:

Conflicts of interest   None.

Received  2022-03-28
Accepted  2022-07-01
DOI: 10.12015/issn.1674-8034.2022.07.006
Cite this article as: Li FZ, Li Q, Wu SS, et al. Histogram features of quantitative parameters from synthetic MRI and ADC map in predicting the expression of Ki-67 in breast cancer[J]. Chin J Magn Reson Imaging, 2022, 13(7): 29-34, 67.DOI:10.12015/issn.1674-8034.2022.07.006

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