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Brain SPECT imaging and left hemispatial neglect covaried using partial least squares: The sunnybrook stroke study

机译:使用局部最小二乘法对脑SPECT成像和左半乳ne漏进行协变量:Sunnybrook脑卒中研究

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摘要

Hemispatial neglect, characterized as failure to attend to contralesional space, is hypothesized by current neuroanatomical models to result from damage to a network involving the frontal, parietal, and cingulate cortices, basal ganglia, and thalamus. This study investigated this model of neglect in 81 right hemisphere‐damaged acute stroke patients using 99 Tc‐HMPAO single photon emission‐computed tomography (SPECT). In order to exploit the inherent collinearity of SPECT regional brain ratios, a novel statistical technique, partial least squares (PLS), was utilized. It makes use of high correlations to identify biologically relevant patterns of brain activity. Averaged ipsilesional cerebellar ratios from 152 brain segments were covaried with performance on subtests of the Sunnybrook Neglect Battery. In this patient sample, the most influential region identified by PLS corresponded to the area surrounding the right temporal‐parietal‐occipital (TPO) junction that included the right lateral occipital, temporal, and inferior parietal lobes. Hypoperfusion in the medial frontal cortex, including the anterior cingulate, also emerged as significantly associated with more severe neglect. Thus, hypoperfusion in only two of the five hypothesized network regions emerged as significantly associated with hemispatial neglect on SPECT imaging. This work converges with structural imaging studies to suggest that damage to the TPO junction, not just the parietal lobe, may be the critical region for hemispatial neglect. Our study demonstrated the utility of PLS for analyzing functional imaging and behavioral data sets in a clinical population in relation to current neuroanatomical models of neglect. Hum. Brain Mapping 7:244–253, 1999. © 1999 Wiley‐Liss, Inc.
机译:目前的神经解剖模型假设半侧pat漏被认为是对额叶皮层,基底节和丘脑的损害。本研究使用99 Tc-HMPAO单光子发射计算机断层扫描(SPECT)研究了81位右半球受损的急性中风患者的这种忽视模型。为了利用SPECT区域脑部比率的固有共线性,采用了一种新颖的统计技术,偏最小二乘(PLS)。它利用高度相关性来识别大脑活动的生物学相关模式。来自152个脑节的同侧小脑平均比率与Sunnybrook Neglect Battery子测试的表现相关。在该患者样本中,PLS识别出的最有影响力的区域对应于右侧颞顶叶枕(TPO)交界处的区域,其中包括右侧枕叶,颞顶叶和下顶叶。内侧额叶皮层的灌注不足,包括前扣带回也明显与更严重的忽视有关。因此,五个假设的网络区域中只有两个区域的灌注不足与SPECT成像上的半pat漏明显相关。这项工作与结构成像研究相吻合,表明对TPO连接的损害(不仅仅是顶叶)可能是半pat漏的关键区域。我们的研究证明了PLS在分析与当前忽视的神经解剖模型相关的临床人群中的功能成像和行为数据集方面的实用性。哼。 Brain Mapping 7:244–253,1999。©1999 Wiley-Liss,Inc.。

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