An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma

Journal of Translational Medicine

Research

Xinxin Xu¹  Weiquan Shu²  Feng Tang²  Renling Mao²  Xuhao Fang²  Yao Deng²  Yao Ye³  Ningfang Du⁴  Shihong Li⁴  Guangwu Lin⁴  Kefeng Li⁵ 

[1] Clinical Research Center for Gerontology, Huadong Hospital, Fudan University, Shanghai, China;Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China;Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China;Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China;School of Medicine, University of California, San Diego, CA, USA;Faculty of Health Sciences and Sports, Macao Polytechnic University, Macao SAR, China;

关键词: Glioma;    Magnetic resonance imaging;    Ki-67 labeling index;    Diffusion-weighted magnetic resonance imaging;    Apparent diffusion coefficient;    Peritumoral edema;   

DOI  :  10.1186/s12967-023-03950-w

 received in 2022-08-01, accepted in 2023-02-01,  发布年份 2023

来源: Springer

【 摘 要 】

Background and purposeKi-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics.MethodsPreoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis.ResultsADCmin, ADCmean, rADCmin, rADCmean and Ki-67 LI showed a negative correlation (r = − 0.478, r = − 0.369, r = − 0.488, r = − 0.388, all P < 0.001). The Ki-67 LI of low-grade gliomas (LGGs) was different from that of high-grade gliomas (HGGs), and the cut-off point of Ki-67 LI for distinguishing LGGs from HGGs was 9.5%, with an area under the ROC curve (AUROC) of 0.962 (95%CI 0.933–0.990). The ADC parameters in the high Ki-67 group were significantly lower than those in the low Ki-67 group (all P < 0.05). The peritumoral edema (PTE) of gliomas in the high Ki-67 LI group was higher than that in the low Ki-67 LI group (P < 0.05). The AUROC of Ki-67 LI level assessed by the multivariate logistic regression model was 0.800 (95%CI 0.721–0.879).ConclusionsThere was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI.

【 授权许可】

CC BY   
© The Author(s) 2023

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