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

Authors :
Ningfang Du
Weiquan Shu
Kefeng Li
Yao Deng
Xinxin Xu
Yao Ye
Feng Tang
Renling Mao
Guangwu Lin
Shihong Li
Xuhao Fang
Source :
Journal of Translational Medicine, Vol 21, Iss 1, Pp 1-11 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract Background and purpose Ki-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. Methods Preoperative 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. Results ADCmin, 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

Details

Language :
English
ISSN :
14795876 and 28775708
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Translational Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.467e2877570845d0be1811b86db8b2c0
Document Type :
article
Full Text :
https://doi.org/10.1186/s12967-023-03950-w