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Structural features of brain regions in temporal lobe epilepsy with dual pathology: An analysis based on MRI postprocessing technology

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Title: Structural features of brain regions in temporal lobe epilepsy with dual pathology: An analysis based on MRI postprocessing technology
Authors: KONG Yu, LIU Ruihan, YAO Lei, WANG Shuzhen, LIU Chunzhao, KONG Qingxia
Source: 精准医学杂志, Vol 39, Iss 6, Pp 500-504 (2024)
Publisher Information: Editorial Office of Journal of Precision Medicine, 2024.
Publication Year: 2024
Collection: LCC:Medicine
Subject Terms: epilepsy, temporal lobe, image processing, computer-assisted, magnetic resonance imaging, malformations of cortical development, hippocampus, sclerosis, Medicine
More Details: Objective To perform automatic fine brain segmentation and brain region quantitative analysis based on magnetic resonance imaging (MRI) postprocessing technology, and to investigate the structural features of brain regions in drug-resis-tant temporal lobe epilepsy (TLE) with dual pathology (DP). Methods Thirty-five TLE patients with DP treated at our hospital from January 2017 to December 2023 were selected as TLE-DP group, and 32 healthy adults from the same period were selected as control group. The MRI images of the two groups were collected for automatic fine brain segmentation and brain region quantitative analysis. The volume, volume fraction, cortical thickness, cortical surface area, and cortical curvature of each brain region were compared between the two groups. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the above parameters for the efficacy of diagnosis of TLE with DP. Results Automatic fine brain segmentation and brain region quantitative analysis indicated that the volume of 30 brain regions, volume fraction of 12 brain regions, cortical thickness of 2 brain regions, cortical surface area of 11 brain regions, cortical curvature of 3 brain regions, volume of 21 hippocampal subregions, and volume fraction of 1 hippocampal subregion were significantly different between the two groups (t=-2.151-3.882,P0.7). Conclusion Automatic fine brain segmentation and brain region quantitative analysis based on MRI postprocessing technology are of high diagnostic value in TLE patients with DP.
Document Type: article
File Description: electronic resource
Language: Chinese
ISSN: 2096-529X
20240600
Relation: https://jpmed.qdu.edu.cn/fileup/2096-529X/PDF/1732259604090-599105829.pdf; https://doaj.org/toc/2096-529X
DOI: 10.13362/j.jpmed.202406007
Access URL: https://doaj.org/article/dcaa30e6712342ec8e753926048e2cd9
Accession Number: edsdoj.30e6712342ec8e753926048e2cd9
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  Data: 精准医学杂志, Vol 39, Iss 6, Pp 500-504 (2024)
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  Data: Editorial Office of Journal of Precision Medicine, 2024.
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  Data: <searchLink fieldCode="DE" term="%22epilepsy%2C+temporal+lobe%22">epilepsy, temporal lobe</searchLink><br /><searchLink fieldCode="DE" term="%22image+processing%2C+computer-assisted%22">image processing, computer-assisted</searchLink><br /><searchLink fieldCode="DE" term="%22magnetic+resonance+imaging%22">magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22malformations+of+cortical+development%22">malformations of cortical development</searchLink><br /><searchLink fieldCode="DE" term="%22hippocampus%22">hippocampus</searchLink><br /><searchLink fieldCode="DE" term="%22sclerosis%22">sclerosis</searchLink><br /><searchLink fieldCode="DE" term="%22Medicine%22">Medicine</searchLink>
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  Data: Objective To perform automatic fine brain segmentation and brain region quantitative analysis based on magnetic resonance imaging (MRI) postprocessing technology, and to investigate the structural features of brain regions in drug-resis-tant temporal lobe epilepsy (TLE) with dual pathology (DP). Methods Thirty-five TLE patients with DP treated at our hospital from January 2017 to December 2023 were selected as TLE-DP group, and 32 healthy adults from the same period were selected as control group. The MRI images of the two groups were collected for automatic fine brain segmentation and brain region quantitative analysis. The volume, volume fraction, cortical thickness, cortical surface area, and cortical curvature of each brain region were compared between the two groups. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the above parameters for the efficacy of diagnosis of TLE with DP. Results Automatic fine brain segmentation and brain region quantitative analysis indicated that the volume of 30 brain regions, volume fraction of 12 brain regions, cortical thickness of 2 brain regions, cortical surface area of 11 brain regions, cortical curvature of 3 brain regions, volume of 21 hippocampal subregions, and volume fraction of 1 hippocampal subregion were significantly different between the two groups (t=-2.151-3.882,P0.7). Conclusion Automatic fine brain segmentation and brain region quantitative analysis based on MRI postprocessing technology are of high diagnostic value in TLE patients with DP.
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      – SubjectFull: image processing, computer-assisted
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      – SubjectFull: magnetic resonance imaging
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