4.5 Article

Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions

期刊

NEUROIMAGE-CLINICAL
卷 30, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2021.102639

关键词

Structural disconnection; White matter disconnection; Lesion mapping; Lesion methods; Disconnectome

资金

  1. NIH Institutes and Centers support the NIH Blueprint for Neuroscience Research [1U54MH091657]
  2. McDonnell Center for Systems Neuroscience at Washington University
  3. [R01 NS095741]
  4. [R01 HD061117]

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Lesion studies are crucial for cognitive neuroscientists and neurologists, but new evidence suggests neurological diseases like stroke are brain network disorders. The Lesion Quantification Toolkit is a MATLAB software package that provides tools for quantifying the structural impacts of focal brain lesions, aiding researchers in understanding the effects of white matter disconnections on cognitive and physiological consequences.
Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.

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