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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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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. |
format | Online Article Text |
id | pubmed-9922464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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