2023
DOI: 10.21037/qims-22-450
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Functional-structural large-scale brain networks are correlated with neurocognitive impairment in acute mild traumatic brain injury

Abstract: Background: This study was conducted to investigate topological changes in large-scale functional connectivity (FC) and structural connectivity (SC) networks in acute mild traumatic brain injury (mTBI) and determine their potential relevance to cognitive impairment.Methods: Seventy-one patients with acute mTBI (29 males, 42 females, mean age 43.54 years) from Nanjing First Hospital and 57 matched healthy controls (HC) (33 males, 24 females, mean age 46.16 years) from the local community were recruited in this … Show more

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Cited by 4 publications
(2 citation statements)
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“…In contrast, studies of acute mTBI have certain advantages in identifying the changes in brain structure and function during the onset, thus providing important information on the pathogenesis of mTBI. Abnormal changes in CBF in the insula are consistent with previous studies based on functional MRI (fMRI), 27 , 28 suggesting that this may be one of the core regions for the onset of acute mTBI. In addition, acute mTBI also had abnormal CBF in frontal regions, especially the medial prefrontal gyrus, and increased CBF in the bilateral temporal lobes.…”
Section: Discussionsupporting
confidence: 89%
“…In contrast, studies of acute mTBI have certain advantages in identifying the changes in brain structure and function during the onset, thus providing important information on the pathogenesis of mTBI. Abnormal changes in CBF in the insula are consistent with previous studies based on functional MRI (fMRI), 27 , 28 suggesting that this may be one of the core regions for the onset of acute mTBI. In addition, acute mTBI also had abnormal CBF in frontal regions, especially the medial prefrontal gyrus, and increased CBF in the bilateral temporal lobes.…”
Section: Discussionsupporting
confidence: 89%
“…Previous articles have provided a comprehensive and detailed description of these global and nodal metrics [19]. In this study, we used a sparsity threshold ranging from 0.05 to 0.5 with a step of 0.01 to analyze topological network properties to reduce the effect of bias caused by a single threshold [20]. The metrics of the structural network were calculated as the area under the curve (AUC).…”
Section: Network Constructionmentioning
confidence: 99%