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

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 pr...

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Autores principales: Du, Ningfang, Shu, Weiquan, Li, Kefeng, Deng, Yao, Xu, Xinxin, Ye, Yao, Tang, Feng, Mao, Renling, Lin, Guangwu, Li, Shihong, Fang, Xuhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922464/
https://www.ncbi.nlm.nih.gov/pubmed/36774480
http://dx.doi.org/10.1186/s12967-023-03950-w
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author Du, Ningfang
Shu, Weiquan
Li, Kefeng
Deng, Yao
Xu, Xinxin
Ye, Yao
Tang, Feng
Mao, Renling
Lin, Guangwu
Li, Shihong
Fang, Xuhao
author_facet Du, Ningfang
Shu, Weiquan
Li, Kefeng
Deng, Yao
Xu, Xinxin
Ye, Yao
Tang, Feng
Mao, Renling
Lin, Guangwu
Li, Shihong
Fang, Xuhao
author_sort Du, Ningfang
collection PubMed
description 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: ADC(min), ADC(mean), rADC(min), rADC(mean) 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). CONCLUSIONS: There 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03950-w.
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spelling pubmed-99224642023-02-13 An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma Du, Ningfang Shu, Weiquan Li, Kefeng Deng, Yao Xu, Xinxin Ye, Yao Tang, Feng Mao, Renling Lin, Guangwu Li, Shihong Fang, Xuhao J Transl Med Research 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: ADC(min), ADC(mean), rADC(min), rADC(mean) 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). CONCLUSIONS: There 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03950-w. BioMed Central 2023-02-11 /pmc/articles/PMC9922464/ /pubmed/36774480 http://dx.doi.org/10.1186/s12967-023-03950-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Du, Ningfang
Shu, Weiquan
Li, Kefeng
Deng, Yao
Xu, Xinxin
Ye, Yao
Tang, Feng
Mao, Renling
Lin, Guangwu
Li, Shihong
Fang, Xuhao
An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title_full An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title_fullStr An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title_full_unstemmed An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title_short An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
title_sort initial study on the predictive value using multiple mri characteristics for ki-67 labeling index in glioma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922464/
https://www.ncbi.nlm.nih.gov/pubmed/36774480
http://dx.doi.org/10.1186/s12967-023-03950-w
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