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基于组织病理学评估的 MRI 海马亚区自动分割技术在颞叶癫痫患者中的验证。

Validation of automatic MRI hippocampal subfield segmentation by histopathological evaluation in patients with temporal lobe epilepsy.

机构信息

Epilepsy Center Hessen, Philipps-University Marburg, Department of Neurology, Baldingerstrasse, 35043, Marburg, Germany.

Epilepsy Center, University Hospital Erlangen, Erlangen, Germany.

出版信息

Seizure. 2021 Apr;87:94-102. doi: 10.1016/j.seizure.2021.03.007. Epub 2021 Mar 12.

DOI:10.1016/j.seizure.2021.03.007
PMID:33752160
Abstract

OBJECTIVE

The present study validates the results of automated hippocampal subfield segmentation with histopathology in epilepsy patients undergoing epilepsy surgery.

METHODS

We performed an automated hippocampal subfield segmentation on presurgical three-dimensional, T1-weighted magnetization Prepared Rapid Acquisition of Gradient Echoes Magnetic Resonance Imaging (MRI) data of 25 patients with unilateral mesial temporal lobe epilepsy due to hippocampal sclerosis (HS), using Freesurfer Version 6.0. The resulting volumes of cornu ammonis (CA) subfields CA1, CA2/3, CA4 and the dentate gyrus (DG) were compared to the histopathological cell count.

RESULTS

We found a significant correlation between histopathology in subregion CA2 and automated segmentation of subregion CA1 (p = 0.0062), CA2/3 (p = 0.004), CA4 (p = 0.0062) and the DG (p = 0.0054), between histopathology in CA3 and automated segmentation of CA1 (p = 0.0132), CA2/3 (p = 0.0004), CA4 (p = 0.0032) and the DG (p = 0.0037), as well as between histopathology in the DG and automated segmentation of CA1 (p = 0.0115), CA2/3 (p < 0.0001), CA4 (p < 0.0001) and the DG (p = 0.0001). The histopathological finding of HS type 1 could correctly be classified in all cases on MRI.

SIGNIFICANCE

The present study shows significant correlations between histopathological evaluation and results of the automated segmentation of the hippocampus, thereby validating the automated segmentation method. As the differential involvement of different hippocampal subfields may be associated with clinical parameters and the outcome after epilepsy surgery, the automated segmentation is also promising for prognostic purposes.

摘要

目的

本研究旨在验证对行癫痫手术的癫痫患者进行术前三维 T1 加权磁化准备快速获取梯度回波磁共振成像(MRI)数据的自动海马亚区分割结果与组织病理学结果的一致性。

方法

我们使用 Freesurfer Version 6.0 对 25 例因海马硬化(HS)导致单侧内侧颞叶癫痫的患者的术前三维、T1 加权、磁化准备快速获取梯度回波 MRI 数据进行了自动海马亚区分割。比较了Cornu ammonis(CA)亚区 CA1、CA2/3、CA4 和齿状回(DG)的体积与组织病理学细胞计数的关系。

结果

我们发现组织病理学亚区 CA2 与自动分割亚区 CA1(p=0.0062)、CA2/3(p=0.004)、CA4(p=0.0062)和 DG(p=0.0054)之间存在显著相关性,组织病理学亚区 CA3 与自动分割亚区 CA1(p=0.0132)、CA2/3(p=0.0004)、CA4(p=0.0032)和 DG(p=0.0037)之间存在显著相关性,组织病理学 DG 与自动分割亚区 CA1(p=0.0115)、CA2/3(p<0.0001)、CA4(p<0.0001)和 DG(p=0.0001)之间存在显著相关性。在所有病例中,MRI 均能正确分类 HS 1 型的组织病理学发现。

意义

本研究表明组织病理学评估与海马自动分割结果之间存在显著相关性,从而验证了自动分割方法的有效性。由于不同海马亚区的不同受累程度可能与临床参数和癫痫手术后的结果相关,因此自动分割在预后方面也具有广阔的应用前景。

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