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基于病灶和间接结构与功能连接缺失预测卒中后缺损。

Post-stroke deficit prediction from lesion and indirect structural and functional disconnection.

机构信息

Clinica Neurologica, Department of Neuroscience, and Padova Neuroscience Center (PNC), University of Padova, Italy.

IRCCS San Camillo Hospital, Venice, Italy.

出版信息

Brain. 2020 Jul 1;143(7):2173-2188. doi: 10.1093/brain/awaa156.

Abstract

Behavioural deficits in stroke reflect both structural damage at the site of injury, and widespread network dysfunction caused by structural, functional, and metabolic disconnection. Two recent methods allow for the estimation of structural and functional disconnection from clinical structural imaging. This is achieved by embedding a patient's lesion into an atlas of functional and structural connections in healthy subjects, and deriving the ensemble of structural and functional connections that pass through the lesion, thus indirectly estimating its impact on the whole brain connectome. This indirect assessment of network dysfunction is more readily available than direct measures of functional and structural connectivity obtained with functional and diffusion MRI, respectively, and it is in theory applicable to a wide variety of disorders. To validate the clinical relevance of these methods, we quantified the prediction of behavioural deficits in a prospective cohort of 132 first-time stroke patients studied at 2 weeks post-injury (mean age 52.8 years, range 22-77; 63 females; 64 right hemispheres). Specifically, we used multivariate ridge regression to relate deficits in multiple functional domains (left and right visual, left and right motor, language, spatial attention, spatial and verbal memory) with the pattern of lesion and indirect structural or functional disconnection. In a subgroup of patients, we also measured direct alterations of functional connectivity with resting-state functional MRI. Both lesion and indirect structural disconnection maps were predictive of behavioural impairment in all domains (0.16 < R2 < 0.58) except for verbal memory (0.05 < R2 < 0.06). Prediction from indirect functional disconnection was scarce or negligible (0.01 < R2 < 0.18) except for the right visual field deficits (R2 = 0.38), even though multivariate maps were anatomically plausible in all domains. Prediction from direct measures of functional MRI functional connectivity in a subset of patients was clearly superior to indirect functional disconnection. In conclusion, the indirect estimation of structural connectivity damage successfully predicted behavioural deficits post-stroke to a level comparable to lesion information. However, indirect estimation of functional disconnection did not predict behavioural deficits, nor was a substitute for direct functional connectivity measurements, especially for cognitive disorders.

摘要

中风后的行为缺陷不仅反映了损伤部位的结构损伤,还反映了由于结构、功能和代谢连接中断而导致的广泛网络功能障碍。最近有两种方法可以从临床结构成像中估计结构和功能连接的中断。这是通过将患者的病变嵌入健康受试者的功能和结构连接图谱中,并得出穿过病变的结构和功能连接的整体,从而间接估计其对整个大脑连接组的影响来实现的。与使用功能 MRI 和扩散 MRI 分别获得的功能和结构连接的直接测量相比,这种网络功能障碍的间接评估更容易获得,并且从理论上讲,它适用于各种疾病。为了验证这些方法的临床相关性,我们在 132 名首次中风患者的前瞻性队列中进行了量化,这些患者在受伤后 2 周(平均年龄 52.8 岁,范围 22-77;63 名女性;64 名右侧半球)进行了研究。具体来说,我们使用多元岭回归将多个功能领域(左侧和右侧视觉、左侧和右侧运动、语言、空间注意力、空间和言语记忆)的缺陷与病变模式和间接结构或功能连接联系起来。在患者的亚组中,我们还使用静息状态功能 MRI 测量了功能连接的直接改变。病变和间接结构连接图均可以预测所有领域的行为障碍(0.16<R2<0.58),除言语记忆(0.05<R2<0.06)外。间接功能连接的预测很少或可以忽略不计(0.01<R2<0.18),除了右侧视野缺陷(R2=0.38)外,尽管所有领域的多元图谱在解剖学上都是合理的。在一组患者中,直接测量功能 MRI 功能连接的预测明显优于间接功能连接。总之,结构连接损伤的间接估计成功地预测了中风后的行为缺陷,其水平可与病变信息相媲美。然而,间接估计功能连接并不能预测行为缺陷,也不能替代直接功能连接测量,尤其是对于认知障碍。

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