Voxel-based analysis of the metabolic asymmetrical and network patterns in hypermetabolism-associated crossed cerebellar diaschisis.
Voxel-based analysis of the metabolic asymmetrical and network patterns in hypermetabolism-associated crossed cerebellar diaschisis.
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基于体素的代谢不对称和代谢亢进相关的交叉小脑机能联系不上的网络模式分析
DOI：
10.1016/j.nicl.2022.103032
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发表时间：
2022
影响因子：
4.2
通讯作者：
Zhu, Xiaohua
中科院分区：
文献类型：
--
作者：
Zhu, Yuankai;Ruan, Ge;Zou, Sijuan;Cheng, Zhaoting;Zhu, Xiaohua
关键词：
基于体素的分析可以用来评估CCD的不对称轮廓。在与CCD相关的异常脑网络中，高代谢的SMC和PRG是恒定的。高代谢和低代谢特征都与CCD的存在有关。位于纹状体和丘脑的AI最小的患者更容易出现CCD。小脑内纹状体、丘脑和小脑之间的联系发生改变。交叉性小脑错位在幕上低代谢患者中已被广泛研究，但有关对侧幕上高代谢患者的交叉小脑错位的代谢特征尚缺乏有效证据。本研究旨在通过基于体素的不对称指数(AI)和脑网络分析来评估高代谢相关的CCD的代谢不对称性、网络模式和易感因素。本文介绍了70例单侧幕上高代谢患者的临床资料，其中阳性组70例，阴性组99例。在AImax和Aimin的不同脑区中，纹状体和丘脑的CCD阳性率最高(分别为85.7%和70.1%)。Ccd+组AImax(中位数0.44-0.84)、幕上高代谢体积(1183.5[399.3-3026.8]比386.0[152.0-1193.0])和低代谢体积(37796.5[24741.8-53278.0]比3337.0[1020.0-17193.0])显著增加。Aimin(−0.85[-1.05-−0.73]vs−0.49[−0.68-−0.35])低于Ccd组(All P<；(0.001)。Logistic回归分析显示，位于纹状体和丘脑的Aimin患者发生脑出血的概率是额叶患者的16.4倍(OR=16.393；95%CI，4.463~60.207；P<0.001)，脑出血的发生与AImax(OR=49.594；95%CI，5.519~445.653；P<0.001)和Aimin(OR=3.133×10−4，95%CI，1.693×10−5~5.799×10−3，P<0.05)有关；(0.001)。脑网络分析表明，在与CCD相关的模式中，对侧辅助运动皮质(SMC)和楔前回的相对高代谢是恒定的。提示单侧幕上高代谢患者AImax较大，Aimin较低，Aimin较低，纹状体和丘脑Aimin较高，可能是Cd的易感因素。对侧SMC和楔前回的相对活动增加可能归因于与CCD相关的异常脑网络的代偿机制。
Voxel-based analysis could be applied for assessing the asymmetrical profile of CCD. Hypermetabolic SMC and PrG are constant in the abnormal brain network related to CCD. Both hyper- and hypo-metabolic features are associated with the presence of CCD. Patients with minimum of AI located at striatum & thalamus are prone to present CCD. Altered connectivities between striatum & thalamus and cerebellum exist in CCD. Crossed cerebellar diaschisis (CCD) has been widely investigated in patients with supratentorial hypometabolism, however, the available evidence about the metabolic feature of CCD in patients with contralateral supratentorial hypermetabolism is lacking. This study aimed to assess the metabolic asymmetrical profile, network pattern and predisposing factors for the hypermetabolism-associated CCD, by using voxel-based asymmetry index (AI) and brain network analyses. Seventy CCD positive (CCD+) and 99 CCD negative (CCD-) patients with unilateral supratentorial hypermetabolism were introduced. Among different brain regions with AImax or AImin, striatum & thalamus was accompanied by the highest positive rate of CCD (85.7% or 70.1%, respectively). CCD+ group had significantly greater AImax (median [IQR], 0.62 [0.44–0.84] vs. 0.47 [0.35–0.61]), supratentorial hypermetabolic volume (1183.5 [399.3–3026.8] vs. 386.0 [152.0–1193.0]) and hypometabolic volume (37796.5 [24741.8–53278.0] vs. 3337.0 [1020.0–17193.0]), and lower AImin (−0.85 [-1.05–−0.73] vs. −0.49 [−0.68–−0.35]) compared with CCD- group (all P < 0.001). Logistic regression analysis manifested that patients with AImin located at striatum & thalamus were 16.4 times more likely to present CCD than those at frontal lobe (OR = 16.393; 95% CI, 4.463–60.207; P < 0.001), and the occurrence of CCD was also associated with AImax (OR = 49.594; 95% CI, 5.519–445.653; P < 0.001) and AImin (OR = 3.133 × 10−4, 95% CI, 1.693 × 10−5–5.799 × 10−3, P < 0.001). Brain network analysis indicated that the relative hypermetabolism in the contralateral supplementary motor cortex (SMC) and precuneus gyrus were constant in the CCD related patterns. These results demonstrated that the greater AImax, lower AImin and AImin located at striatum & thalamus should be predisposing factors for CCD in patients with unilateral supratentorial hypermetabolism. Relative increased activities in the contralateral SMC and precuneus gyrus might be attributed to a compensatory mechanism for the abnormal brain network related to CCD.
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