Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.
Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challenging, there is a risk for long-term psychiatric, neurologic, and psychosocial problems in some patients that motivates the search for new and better biomarkers. Recently, diffusion magnetic resonance imaging (dMRI) has shown promise in detecting mTBI, but its validity is still being investigated. Resting state functional network connectivity (rsFNC) is another approach that is emerging as a promising option for the diagnosis of mTBI. The present work investigated the use of rsFNC for mTBI detection compared with dMRI results on the same cohort. Fifty patients with mTBI (25 males) and age-sex matched healthy controls were recruited. Features from dMRI were obtained using all voxels, the enhanced Z-score microstructural assessment for pathology, and the distribution corrected Z-score. Features based on rsFNC were obtained through group independent component analysis and correlation between pairs of resting state networks. A linear support vector machine was used for classification and validated using leave-one-out cross validation. Classification achieved a maximum accuracy of 84.1% for rsFNC and 75.5% for dMRI and 74.5% for both combined. A t test analysis revealed significant increase in rsFNC between cerebellum versus sensorimotor networks and between left angular gyrus versus precuneus in subjects with mTBI. These outcomes suggest that inclusion of both common and unique information is important for classification of mTBI. Results also suggest that rsFNC can yield viable biomarkers that might outperform dMRI and points to connectivity to the cerebellum as an important region for the detection of mTBI.
1 The Mind Research Network and Lovelace Biomedical and Environmental Research Institute , Albuquerque, New Mexico .
Victor M
VM
Vergara
1 The Mind Research Network and Lovelace Biomedical and Environmental Research Institute , Albuquerque, New Mexico .|2 Department of Neurology, University of New Mexico School of Medicine , Albuquerque, New Mexico .
Andrew R
AR
Mayer
1 The Mind Research Network and Lovelace Biomedical and Environmental Research Institute , Albuquerque, New Mexico .|3 Department of ECE, University of New Mexico , Albuquerque, New Mexico .
Eswar
E
Damaraju
1 The Mind Research Network and Lovelace Biomedical and Environmental Research Institute , Albuquerque, New Mexico .|4 Department of Psychology, University of New Mexico , Albuquerque, New Mexico .
Kent A
KA
Kiehl
1 The Mind Research Network and Lovelace Biomedical and Environmental Research Institute , Albuquerque, New Mexico .|3 Department of ECE, University of New Mexico , Albuquerque, New Mexico .
Vince
V
Calhoun
D000328:Adult; D016880:Anisotropy; D001924:Brain Concussion / Q000000981:diagnostic imaging* / Q000503:physiopathology; D002531:Cerebellum / Q000000981:diagnostic imaging* / Q000503:physiopathology; D002540:Cerebral Cortex / Q000000981:diagnostic imaging* / Q000503:physiopathology; D063132:Connectome / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D060388:Support Vector Machine; D055815:Young Adult
diffusion tensor imaging; magnetic resonance imaging; traumatic brain injury
Brain Imaging Behav. 2012 Jun;6(2):293-318
22555821
Neuroimage. 2017 Jan 15;145(Pt B):365-376
27033684
Nature. 2014 Aug 14;512(7513):185-9
25043041
Neurology. 2010 Jul 13;75(2):168-76
20625170
Brain. 2012 Apr;135(Pt 4):1281-92
22505633
Brain Struct Funct. 2016 Apr;221(3):1427-42
25573247
J Magn Reson Imaging. 2014 Jun;39(6):1558-68
24014176
J Neurotrauma. 2014 Sep 1;31(17):1457-77
24742275
Brain Imaging Behav. 2012 Jun;6(2):329-42
22684769
Brain Connect. 2015 Mar;5(2):102-14
25222050
Radiology. 2011 Sep;260(3):831-40
21775670
IEEE Rev Biomed Eng. 2012;5:60-73
23231989
Neuroimage. 2011 Apr 15;55(4):1716-27
21255654
Neuroimage. 2002 May;16(1):241-50
11969331
Brain Res. 2013 Nov 6;1537:201-15
23994210
Front Hum Neurosci. 2015 Sep 22;9:513
26441610
Neuroimage. 2004 Jul;22(3):1214-22
15219593
Neuroimage. 2011 Aug 1;57(3):839-55
21640835
Neuroimage. 2012 Feb 1;59(3):2142-54
22019881
PLoS One. 2013;8(3):e59382
23555665
Brain. 2006 Feb;129(Pt 2):290-2
16434422
Arch Clin Neuropsychol. 2009 Feb;24(1):3-10
19395352
Neurosci Biobehav Rev. 2015 Feb;49:8-18
25434880
Brain. 2014 Jan;137(Pt 1):12-32
23869106
Hum Brain Mapp. 2001 Nov;14(3):140-51
11559959
N Engl J Med. 2010 Sep 30;363(14):1293-6
20879875
JAMA Psychiatry. 2015 Jan;72(1):68-74
25409415
AJNR Am J Neuroradiol. 2004 Mar;25(3):370-6
15037457
Brain Imaging Behav. 2012 Jun;6(2):137-92
22438191
Cerebellum. 2007;6(3):159-62
17786810
Front Syst Neurosci. 2011 Feb 04;5:2
21442040
Brain. 2011 Aug;134(Pt 8):2233-47
21841202
Hum Brain Mapp. 2011 Nov;32(11):1825-35
21259381
Hum Brain Mapp. 2009 Jan;30(1):241-55
18072279
Magn Reson Imaging Clin N Am. 2013 May;21(2):279-98
23642554
Acad Radiol. 2010 Sep;17(9):1096-102
20605490
Radiology. 2012 Dec;265(3):882-92
23175546
IEEE Trans Biomed Eng. 2011 Dec;58(12):3406-17
21900068
J Head Trauma Rehabil. 2014 Mar-Apr;29(2):E1-E10
23558829
Nat Rev Neurol. 2014 Mar;10(3):156-66
24514870
Neuroimage Clin. 2014 Jul 24;7:87-97
25610770
J Rehabil Med. 2004 Feb;(43 Suppl):61-75
15083871
Hum Brain Mapp. 2009 Oct;30(10):3127-41
19235882
Brain Inj. 2013;27(11):1304-10
24020442
Biol Psychiatry Cogn Neurosci Neuroimaging. 2016 May;1(3):230-244
27347565
Hum Brain Mapp. 2014 Nov;35(11):5457-70
24931496
PLoS One. 2014 Aug 14;9(8):e104021
25121760
Brain. 2011 Feb;134(Pt 2):449-63
21193486
J Neurotrauma. 2015 Jul 15;32(14):1046-55
25318005
Neurotherapeutics. 2013 Jul;10(3):511-9
23605556
Neuroimage. 2010 Feb 15;49(4):3110-21
19931396