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联合定量磁敏感图与灰质体积预测小血管闭塞患者的神经功能缺损。

Combining Quantitative Susceptibility Mapping With the Gray Matter Volume to Predict Neurological Deficits in Patients With Small Artery Occlusion.

机构信息

Department of Neurology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.

Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.

出版信息

Brain Behav. 2024 Oct;14(10):e70080. doi: 10.1002/brb3.70080.

Abstract

BACKGROUND

Currently, there is still a lack of valuable neuroimaging markers to assess the clinical severity of stroke patients with small artery occlusion (SAO). Quantitative susceptibility mapping (QSM) is a quantitative processing method for neuroradiological diagnostics. Gray matter (GM) volume changes in stroke patients are also proved to be associated with neurological deficits. This study aims to explore the predictive value of QSM and GM volume in neurological deficits of patients with SAO.

METHODS

As neurological deficits, the National Institutes of Health Stroke Scale (NIHSS) was used. Sixty-six SAO participants within 24 h of first onset were enrolled and divided into mild and moderate groups based on NIHSS. QSM values of infarct area and GM volume were calculated from magnetic resonance imaging (MRI) data. Two-sample t-tests were used to compare differences in QSM value and GM volume between the two groups, and the diagnostic efficacy of the combination of QSM value and GM volume was evaluated.

RESULTS

The results revealed both the QSM value and GM volume within the infarct area of the moderate group were lower compared to the mild group. Moderate group exhibited lower GM volume in some specific gyrus compared with mild group in the case of voxel-wise GM volume on whole-brain voxel level. The support vector machine (SVM) classifier's analysis showed a high power for the combination of QSM value, GM volume within the infarct area, and voxel-wise GM volume.

CONCLUSION

Our research first reported the combination of QSM value, GM volume within the infarct area, and voxel-wise GM volume could be used to predict neurological impairment of patients with SAO, which provides new insights for further understanding the SAO stroke.

摘要

背景

目前,仍然缺乏有价值的神经影像学标志物来评估小动脉闭塞(SAO)卒中患者的临床严重程度。定量磁化率映射(QSM)是一种神经影像学诊断的定量处理方法。卒中患者的灰质(GM)体积变化也被证明与神经功能缺损有关。本研究旨在探讨 QSM 和 GM 体积对 SAO 患者神经功能缺损的预测价值。

方法

以国立卫生研究院卒中量表(NIHSS)作为神经功能缺损的评估指标。共纳入 66 例发病 24 小时内的 SAO 患者,根据 NIHSS 将其分为轻度组和中度组。从磁共振成像(MRI)数据中计算梗死区的 QSM 值和 GM 体积。采用两样本 t 检验比较两组间 QSM 值和 GM 体积的差异,并评估 QSM 值与 GM 体积联合的诊断效能。

结果

结果显示,中度组的梗死区 QSM 值和 GM 体积均低于轻度组。与轻度组相比,中度组在某些特定脑回的 GM 体积也较低。在全脑体素水平上,基于体素的 GM 体积分析显示,中度组在某些特定脑区的 GM 体积也较低。支持向量机(SVM)分类器分析显示,QSM 值、梗死区 GM 体积和基于体素的 GM 体积联合的诊断效能较高。

结论

本研究首次报道 QSM 值、梗死区 GM 体积和基于体素的 GM 体积联合可用于预测 SAO 患者的神经功能缺损,为进一步了解 SAO 卒中提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b779/11450255/6f184a5bb884/BRB3-14-e70080-g002.jpg

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