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

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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.

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Acknowledgments

The TRAIN-TBI project was generously supported by a gift from Dennis J. & Shannon Wong. Dr. Raji was supported by a training grant from the National Institute of Biomedical Imaging and Bioengineering (NIH T32 EB001631), administered by the UCSF Department of Radiology and Biomedical Imaging, and the American Society of Neuroradiology Boerger Research Grant. He is currently supported by additional grants from the Radiological Society of North America Research Scholar Award and WUSTL NIH KL2 Grant (KL2 TR000450 – ICTS Multidisciplinary Clinical Research Career Development Program). Dr. Mukherjee received support from the National Institute of Neurological Disorders and Stroke (NIH R01 NS060776).

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    Authors and Affiliations

    1. Neural Connectivity Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., Suite 350, San Francisco, CA, 94158, USA

      Cyrus A. Raji, Maxwell B. Wang, NhuNhu Nguyen, Julia P. Owen, Eva M. Palacios, Esther L. Yuh & Pratik Mukherjee

    2. Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA

      Cyrus A. Raji

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    1. Cyrus A. Raji
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    Raji, C.A., Wang, M.B., Nguyen, N. et al. Connectome mapping with edge density imaging differentiates pediatric mild traumatic brain injury from typically developing controls: proof of concept. Pediatr Radiol 50, 1594–1601 (2020). https://doi.org/10.1007/s00247-020-04743-9

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