An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma
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 a...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-02-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-023-03950-w |
| _version_ | 1811165763941171200 |
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| author | Ningfang Du Weiquan Shu Kefeng Li Yao Deng Xinxin Xu Yao Ye Feng Tang Renling Mao Guangwu Lin Shihong Li Xuhao Fang |
| author_facet | Ningfang Du Weiquan Shu Kefeng Li Yao Deng Xinxin Xu Yao Ye Feng Tang Renling Mao Guangwu Lin Shihong Li Xuhao Fang |
| author_sort | Ningfang Du |
| collection | DOAJ |
| description | 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 < 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. |
| first_indexed | 2024-04-10T15:41:53Z |
| format | Article |
| id | doaj.art-467e2877570845d0be1811b86db8b2c0 |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-04-10T15:41:53Z |
| publishDate | 2023-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-467e2877570845d0be1811b86db8b2c02023-02-12T12:21:02ZengBMCJournal of Translational Medicine1479-58762023-02-0121111110.1186/s12967-023-03950-wAn initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in gliomaNingfang Du0Weiquan Shu1Kefeng Li2Yao Deng3Xinxin Xu4Yao Ye5Feng Tang6Renling Mao7Guangwu Lin8Shihong Li9Xuhao Fang10Department of Radiology, Huadong Hospital, Fudan UniversityDepartment of Neurosurgery, Huadong Hospital, Fudan UniversitySchool of Medicine, University of CaliforniaDepartment of Neurosurgery, Huadong Hospital, Fudan UniversityClinical Research Center for Gerontology, Huadong Hospital, Fudan UniversityDepartment of Pathology, Huadong Hospital, Fudan UniversityDepartment of Neurosurgery, Huadong Hospital, Fudan UniversityDepartment of Neurosurgery, Huadong Hospital, Fudan UniversityDepartment of Radiology, Huadong Hospital, Fudan UniversityDepartment of Radiology, Huadong Hospital, Fudan UniversityDepartment of Neurosurgery, Huadong Hospital, Fudan UniversityAbstract 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 < 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.https://doi.org/10.1186/s12967-023-03950-wGliomaMagnetic resonance imagingKi-67 labeling indexDiffusion-weighted magnetic resonance imagingApparent diffusion coefficientPeritumoral edema |
| spellingShingle | Ningfang Du Weiquan Shu Kefeng Li Yao Deng Xinxin Xu Yao Ye Feng Tang Renling Mao Guangwu Lin Shihong Li Xuhao Fang An initial study on the predictive value using multiple MRI characteristics for Ki-67 labeling index in glioma Journal of Translational Medicine Glioma Magnetic resonance imaging Ki-67 labeling index Diffusion-weighted magnetic resonance imaging Apparent diffusion coefficient Peritumoral edema |
| 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 | Glioma Magnetic resonance imaging Ki-67 labeling index Diffusion-weighted magnetic resonance imaging Apparent diffusion coefficient Peritumoral edema |
| url | https://doi.org/10.1186/s12967-023-03950-w |
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