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形态学脑网络可预测帕金森病患者对左旋多巴的反应性。

Morphologic brain network predicts levodopa responsiveness in Parkinson disease.

作者信息

Xie Yongsheng, Gao Chunyan, Wu Bin, Peng Liling, Wu Jianjun, Lang Liqin

机构信息

Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.

National Center for Neurological Disorders, Shanghai, China.

出版信息

Front Aging Neurosci. 2023 Jan 5;14:990913. doi: 10.3389/fnagi.2022.990913. eCollection 2022.

Abstract

BACKGROUND

The levodopa challenge test (LCT) has been routinely used in Parkinson disease (PD) evaluation and predicts the outcome of deep brain stimulation (DBS). Guidelines recommend that patients with an improvement in Unified Parkinson's Disease Rating Scale (UPDRS)-III score > 33% in the LCT receive DBS treatment. However, LCT results are affected by many factors, and only provide information on the immediate effectiveness of dopamine. The aim of the present study was to investigate the relationship between LCT outcome and brain imaging features of PD patients to determine whether the latter can be used to identify candidates for DBS.

METHODS

A total of 38 PD patients were enrolled in the study. Based on improvement in UPDRS-III score in the LCT, patients were divided into low improvement (PD-LCT-L) and high improvement (PD-LCT-H) groups. Each patient's neural network was reconstructed based on T1-weighted magnetic resonance imaging data using the Jensen-Shannon divergence similarity estimation method. The network was established with the multiple kernel support vector machine technique. We analyzed differences in individual morphologic brain networks and their global and local metrics to determine whether there were differences in the connectomes of PD-LCT-L and PD-LCT-H groups.

RESULTS

The 2 groups were similar in terms of demographic and clinical characteristics. Mean ± SD levodopa responsiveness was 26.52% ± 3.47% in the PD-LCT-L group (N = 13) and 58.66% ± 4.09% in the PD-LCT-H group ( = 25). There were no significant differences between groups in global and local metrics. There were 43 consensus connections that were affected in both groups; in PD-LCT-L patients, most of these connections were decreased whereas those related to the dorsolateral superior frontal gyrus and left cuneus were significantly increased.

CONCLUSION

Morphologic brain network assessment is a valuable method for predicting levodopa responsiveness in PD patients, which can facilitate the selection of candidates for DBS.

摘要

背景

左旋多巴激发试验(LCT)一直被常规用于帕金森病(PD)评估,并可预测深部脑刺激(DBS)的效果。指南建议,在LCT中统一帕金森病评定量表(UPDRS)-III评分改善>33%的患者接受DBS治疗。然而,LCT结果受多种因素影响,且仅提供多巴胺即时疗效的信息。本研究的目的是调查LCT结果与PD患者脑成像特征之间的关系,以确定后者是否可用于识别DBS候选者。

方法

共纳入38例PD患者。根据LCT中UPDRS-III评分的改善情况,将患者分为低改善组(PD-LCT-L)和高改善组(PD-LCT-H)。使用詹森-香农散度相似性估计方法,基于T1加权磁共振成像数据重建每位患者的神经网络。采用多核支持向量机技术建立网络。我们分析了个体形态学脑网络及其全局和局部指标的差异,以确定PD-LCT-L组和PD-LCT-H组的连接组是否存在差异。

结果

两组在人口统计学和临床特征方面相似。PD-LCT-L组(N = 13)左旋多巴反应性的均值±标准差为26.52%±3.47%,PD-LCT-H组(N = 25)为58.66%±4.09%。两组在全局和局部指标上无显著差异。两组共有43条一致性连接受到影响;在PD-LCT-L患者中,这些连接大多减少,而与背外侧额上回和左楔叶相关的连接显著增加。

结论

脑形态学网络评估是预测PD患者左旋多巴反应性的一种有价值的方法,有助于DBS候选者的选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33a8/9849367/66821050d013/fnagi-14-990913-g001.jpg

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