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Journal article
Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury
Human brain mapping, v 43(13), pp 3944-3957
29 Apr 2022
PMID: 35486024
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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.
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Details
- Title
- Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury
- Creators
- Yusuf Osmanlıoğlu - Department of Computer Science, College of Computing and Informatics, Drexel University, Philadelphia, Pennsylvania, USADrew Parker - University of PennsylvaniaJacob A Alappatt - Harvard UniversityJames J Gugger - University of PennsylvaniaRamon R Diaz-Arrastia - University of PennsylvaniaJohn Whyte - Moss Rehabilitation HospitalJunghoon J Kim - City College of New YorkRagini Verma - University of PennsylvaniaYusuf Osmanlioglu - Computer Science (Computing)
- Publication Details
- Human brain mapping, v 43(13), pp 3944-3957
- Publisher
- Wiley
- Grant note
- R01-NS065980 / NIH HHS W81XWH-19-2-0002 / U.S. Department of Defense RO1-NS096606 / NIH HHS W81XWH1910861 / U.S. Department of Defense T32NS091006 / NINDS NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000788648700001
- Scopus ID
- 2-s2.0-85128886552
- Other Identifier
- 991019167666804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neuroimaging
- Neurosciences
- Radiology, Nuclear Medicine & Medical Imaging