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Pediatric radiology
10, 2020;50 (11): 1594-1601.

Connectome mapping with edge density imaging differentiates pediatric mild traumatic brain injury from typically developing controls: proof of concept.

Cyrus A Raji, Maxwell B Wang, NhuNhu Nguyen, Julia P Owen, Eva M Palacios, Esther L Yuh, Pratik Mukherjee
Author Information
  1. Cyrus A Raji: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA. cyrusraji@gmail.com. ORCID
  2. Maxwell B Wang: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
  3. NhuNhu Nguyen: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
  4. Julia P Owen: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
  5. Eva M Palacios: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
  6. Esther L Yuh: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
  7. Pratik Mukherjee: Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA.
PMID: 32607611 DOI: 10.1007/s00247-020-04743-9

Abstract

BACKGROUND: Although acute neurologic impairment might be transient, other long-term effects can be observed with mild traumatic brain injury. However, when pediatric patients with mild traumatic brain injury present for medical care, conventional imaging with CT and MR imaging often does not reveal abnormalities.
OBJECTIVE: To determine whether edge density imaging can separate pediatric mild traumatic brain injury from typically developing controls.
MATERIALS AND METHODS: Subjects were recruited as part of the "Therapeutic Resources for Attention Improvement using Neuroimaging in Traumatic Brain Injury" (TRAIN-TBI) study. We included 24 adolescents (χ=14.1 years of age, σ=1.6 years, range 10-16 years), 14 with mild traumatic brain injury (TBI) and 10 typically developing controls. Neurocognitive assessments included the pediatric version of the California Verbal Learning Test (CVLT) and the Attention Network Task (ANT). Diffusion MR imaging was acquired on a 3-tesla (T) scanner. Edge density images were computed utilizing fiber tractography. Principal component analysis (PCA) and support vector machines (SVM) were used in an exploratory analysis to separate mild TBI and control groups. The diagnostic accuracy of edge density imaging, neurocognitive tests, and fractional anisotropy (FA) from diffusion tensor imaging (DTI) was computed with two-sample t-tests and receiver operating characteristic (ROC) metrics.
RESULTS: Support vector machine-principal component analysis of edge density imaging maps identified three white matter regions distinguishing pediatric mild TBI from controls. The bilateral tapetum, sagittal stratum, and callosal splenium identified mild TBI subjects with sensitivity of 79% and specificity of 100%. Accuracy from the area under the ROC curve (AUC) was 94%. Neurocognitive testing provided an AUC of 61% (CVLT) and 71% (ANT). Fractional anisotropy yielded an AUC of 48%.
CONCLUSION: In this proof-of-concept study, we show that edge density imaging is a new form of connectome mapping that provides better diagnostic delineation between pediatric mild TBI and healthy controls than DTI or neurocognitive assessments of memory or attention.

Keywords

Brain Children Concussion Diffusion tensor imaging Edge density imaging Magnetic resonance imaging Traumatic brain injury

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Grants

  1. KL2 TR002346/NCATS NIH HHS
  2. R01 NS060776/NINDS NIH HHS
  3. T32 EB001631/NIBIB NIH HHS
  4. KL2 TR000450/NIH HHS
  5. KL2 TR000450/NCATS NIH HHS
  6. R01 NS060776/NIH HHS
  7. T32 EB001631/NIH HHS

MeSH Term

Adolescent
Anisotropy
Brain Injuries, Traumatic
Case-Control Studies
Child
Connectome
Diffusion Magnetic Resonance Imaging
Female
Humans
Male
Mental Status and Dementia Tests
Neuroimaging
Principal Component Analysis
Proof of Concept Study
Prospective Studies
Severity of Illness Index
Support Vector Machine
Tomography, X-Ray Computed
Journal Article
Article has an altmetric score of 3

Word Cloud

Created with Highcharts 10.0.0imagingmilddensitybraininjurypediatrictraumaticedgeTBIcontrolstypicallydevelopinganalysisAUCcanMRseparateAttentionTraumaticBrainstudyincludedNeurocognitiveassessmentsCVLTANTDiffusionEdgecomputedcomponentvectordiagnosticneurocognitiveanisotropytensorDTIROCidentifiedmappingBACKGROUND:Althoughacuteneurologicimpairmentmighttransientlong-termeffectsobservedHoweverpatientspresentmedicalcareconventionalCToftenrevealabnormalitiesOBJECTIVE:determinewhetherMATERIALSANDMETHODS:Subjectsrecruitedpart"TherapeuticResourcesImprovementusingNeuroimagingInjury"TRAIN-TBI24adolescentsχ=141 yearsageσ=16 yearsrange10-16 years1410versionCaliforniaVerbalLearningTestNetworkTaskacquired3-teslaTscannerimagesutilizingfibertractographyPrincipalPCAsupportmachinesSVMusedexploratorycontrolgroupsaccuracytestsfractionalFAdiffusiontwo-samplet-testsreceiveroperatingcharacteristicmetricsRESULTS:Supportmachine-principalmapsthreewhitematterregionsdistinguishingbilateraltapetumsagittalstratumcallosalspleniumsubjectssensitivity79%specificity100%Accuracyareacurve94%testingprovided61%71%Fractionalyielded48%CONCLUSION:proof-of-conceptshownewformconnectomeprovidesbetterdelineationhealthymemoryattentionConnectomedifferentiatescontrols:proofconceptChildrenConcussionMagneticresonance

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