Literature DB >> 22549452

Embracing chaos: the scope and importance of clinical and pathological heterogeneity in mTBI.

Sara B Rosenbaum1, Michael L Lipton.   

Abstract

Mild traumatic brain injury (mTBI) manifests a wide array of clinical features, indicating great heterogeneity of its underlying pathologic features. mTBI diversity is related to pre-injury inter-individual differences and differences in the characteristics of each injury. This review summarizes key features of mTBI patients, their injuries and outcomes to give context to the scope of complexity inherent in this disorder. These differences are underscored by heterogeneity in postmortem pathology and in vivo imaging studies. Recognition, understanding and accounting for disease heterogeneity in mTBI are needed to enhance diagnosis and patient management, as approaches that do not account for inter-individual variation in pathology and patient characteristics relevant to real-life clinical trial participants, may entirely miss therapeutic targets. Refining our approach to TBI diagnosis, in light of inter-individual differences, can facilitate the development of effective prognostic tools and algorithms. New paradigms, which embrace heterogeneity of mTBI, in both preclinical and clinical investigation as well the appreciation of this variability in clinical care, offer much promise for enhancing outcomes and mitigating the burden of mTBI on its victims.

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Year:  2012        PMID: 22549452     DOI: 10.1007/s11682-012-9162-7

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  48 in total

Review 1.  Neuroimaging biomarkers in mild traumatic brain injury (mTBI).

Authors:  Erin D Bigler
Journal:  Neuropsychol Rev       Date:  2013-08-24       Impact factor: 7.444

2.  Investigating the effects of subconcussion on functional connectivity using mass-univariate and multivariate approaches.

Authors:  Bryson B Reynolds; Amanda N Stanton; Sauson Soldozy; Howard P Goodkin; Max Wintermark; T Jason Druzgal
Journal:  Brain Imaging Behav       Date:  2018-10       Impact factor: 3.978

3.  Phage display for identification of serum biomarkers of traumatic brain injury.

Authors:  Sarbani Ghoshal; Vimala Bondada; Kathryn E Saatman; Rodney P Guttmann; James W Geddes
Journal:  J Neurosci Methods       Date:  2016-05-07       Impact factor: 2.390

4.  Longitudinal MR Spectroscopy Shows Altered Metabolism in Traumatic Brain Injury.

Authors:  Andrew A Maudsley; Varan Govind; Gaurav Saigal; Stuart G Gold; Leo Harris; Sulaiman Sheriff
Journal:  J Neuroimaging       Date:  2017-07-23       Impact factor: 2.486

Review 5.  Current status of fluid biomarkers in mild traumatic brain injury.

Authors:  Jacqueline R Kulbe; James W Geddes
Journal:  Exp Neurol       Date:  2015-05-14       Impact factor: 5.330

Review 6.  A decade of DTI in traumatic brain injury: 10 years and 100 articles later.

Authors:  M B Hulkower; D B Poliak; S B Rosenbaum; M E Zimmerman; M L Lipton
Journal:  AJNR Am J Neuroradiol       Date:  2013-01-10       Impact factor: 3.825

7.  Potholes and molehills: bias in the diagnostic performance of diffusion-tensor imaging in concussion.

Authors:  Richard Watts; Alex Thomas; Christopher G Filippi; Joshua P Nickerson; Kalev Freeman
Journal:  Radiology       Date:  2014-03-14       Impact factor: 11.105

8.  Advanced biomarkers of pediatric mild traumatic brain injury: Progress and perils.

Authors:  Andrew R Mayer; Mayank Kaushal; Andrew B Dodd; Faith M Hanlon; Nicholas A Shaff; Rebekah Mannix; Christina L Master; John J Leddy; David Stephenson; Christopher J Wertz; Elizabeth M Suelzer; Kristy B Arbogast; Timothy B Meier
Journal:  Neurosci Biobehav Rev       Date:  2018-08-09       Impact factor: 8.989

9.  Unilateral parietal brain injury increases risk-taking on a rat gambling task.

Authors:  Jenny E Ozga-Hess; Cory Whirtley; Christopher O'Hearn; Kristen Pechacek; Cole Vonder Haar
Journal:  Exp Neurol       Date:  2020-01-31       Impact factor: 5.330

10.  Two step Gaussian mixture model approach to characterize white matter disease based on distributional changes.

Authors:  Namhee Kim; Moonseong Heo; Roman Fleysher; Craig A Branch; Michael L Lipton
Journal:  J Neurosci Methods       Date:  2016-04-29       Impact factor: 2.390

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