Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician
Issue title: Thematic Issue: The Science and Practice of Neuropsychological Assessment in Neurorehabilitation
Guest editors: Daniel Klyce, Ana Mills and Paul Dukarm
Affiliations: [a] Department of Neurology and Psychiatry, University of Utah, Salt Lake City, UT, USA
| [b] Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, USA
| [c] Department of Neurology, University of California-Davis, Sacramento, CA, USA
| [d] Re:Cognition Health, London, United Kingdom
Correspondence:
[*]
Address for correspondence: Erin D. Bigler, Ph.D., P.O. Box 979, Somerset, CA 95684, USA. E-mail: [email protected].
Abstract: BACKGROUND:Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician. OBJECTIVE:Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained. METHODS:Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach. RESULTS:Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI. CONCLUSIONS:Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.
Keywords: Traumatic brain injury (TBI), white matter (WM), gray matter (GM), volumetrics, ‘cone of vulnerability’, neural networks, computed tomography (CT), magnetic resonance imaging (MRI)
