Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury.

Autor: Osmanlıoğlu Y; Department of Computer Science, College of Computing and Informatics, Drexel University, Philadelphia, Pennsylvania, USA., Parker D; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Alappatt JA; Speech and hearing, bioscience and technology program, Harvard Medical School, Harvard University, Boston, MA, USA., Gugger JJ; Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Diaz-Arrastia RR; Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.; Center for Brain Injury and Repair, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Whyte J; Moss Rehabilitation Research Institute, TBI Rehabilitation Research LaboratoryEinstein Medical Center, Elkins Park, Pennsylvania, USA., Kim JJ; Department of Molecular, Cellular, and Biomedical Sciences, CUNY School of Medicine, The City College of New York, New York, New York, USA., Verma R; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.; Center for Brain Injury and Repair, University of Pennsylvania, Philadelphia, Pennsylvania, USA.; Department of Neurosurgery, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Jazyk: angličtina
Zdroj: Human brain mapping [Hum Brain Mapp] 2022 Sep; Vol. 43 (13), pp. 3944-3957. Date of Electronic Publication: 2022 Apr 29.
DOI: 10.1002/hbm.25894
Abstrakt: Traumatic brain injury (TBI) is a major public health problem. Caused by external mechanical forces, a major characteristic of TBI is the shearing of axons across the white matter, which causes structural connectivity disruptions between brain regions. This diffuse injury leads to cognitive deficits, frequently requiring rehabilitation. Heterogeneity is another characteristic of TBI as severity and cognitive sequelae of the disease have a wide variation across patients, posing a big challenge for treatment. Thus, measures assessing network-wide structural connectivity disruptions in TBI are necessary to quantify injury burden of individuals, which would help in achieving personalized treatment, patient monitoring, and rehabilitation planning. Despite TBI being a disconnectivity syndrome, connectomic assessment of structural disconnectivity has been relatively limited. In this study, we propose a novel connectomic measure that we call network normality score (NNS) to capture the integrity of structural connectivity in TBI patients by leveraging two major characteristics of the disease: diffuseness of axonal injury and heterogeneity of the disease. Over a longitudinal cohort of moderate-to-severe TBI patients, we demonstrate that structural network topology of patients is more heterogeneous and significantly different than that of healthy controls at 3 months postinjury, where dissimilarity further increases up to 12 months. We also show that NNS captures injury burden as quantified by posttraumatic amnesia and that alterations in the structural brain network is not related to cognitive recovery. Finally, we compare NNS to major graph theory measures used in TBI literature and demonstrate the superiority of NNS in characterizing the disease.
(© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Databáze: MEDLINE
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