TY - JOUR
T1 - Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children
AU - Mcinnis, Carter
AU - Garcia, María José Solana
AU - Widjaja, Elysa
AU - Frndova, Helena
AU - Huyse, Judith Van
AU - Guerguerian, Anne Marie
AU - Oyefiade, Adeoye
AU - Laughlin, Suzanne
AU - Raybaud, Charles
AU - Miller, Elka
AU - Tay, Keng
AU - Bigler, Erin D.
AU - Dennis, Maureen
AU - Fraser, Douglas D.
AU - Campbell, Craig
AU - Choong, Karen
AU - Dhanani, Sonny
AU - Lacroix, Jacques
AU - Farrell, Catherine
AU - Beauchamp, Miriam H.
AU - Schachar, Russell
AU - Hutchison, James S.
AU - Wheeler, Anne L.
N1 - Funding Information:
This study was funded by a peer reviewed grant (2006-ABI-COMOR-440) from the Ontario Neurotrauma Foundation. ALW is supported by a Catalyst Scholarship for TBI Research funded by FedEx and the SickKids Foundation. CM was supported by the Ruth Taylor Studentship Fund at Queen’s University School of Medicine.
Publisher Copyright:
© Copyright 2021, Mary Ann Liebert, Inc.
PY - 2021/9/1
Y1 - 2021/9/1
N2 - The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.
AB - The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.
KW - functional outcomes
KW - magnetic resonance imaging
KW - pediatrics
KW - prediction models
KW - traumatic brain injury
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U2 - 10.1089/neu.2020.7514
DO - 10.1089/neu.2020.7514
M3 - Article
C2 - 33787327
AN - SCOPUS:85114321887
SN - 0897-7151
VL - 38
SP - 2407
EP - 2418
JO - Central Nervous System Trauma
JF - Central Nervous System Trauma
IS - 17
ER -