Citation
Main, Keith L., et al. "DTI Measures Identify Mild and Moderate TBI Cases Among Patients With Complex Health Problems: a Receiver Operating Characteristic Analysis of U.S. Veterans." NeuroImage. Clinical, vol. 16, 2017, pp. 1-16.
Main KL, Soman S, Pestilli F, et al. DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans. Neuroimage Clin. 2017;16:1-16.
Main, K. L., Soman, S., Pestilli, F., Furst, A., Noda, A., Hernandez, B., Kong, J., Cheng, J., Fairchild, J. K., Taylor, J., Yesavage, J., Wesson Ashford, J., Kraemer, H., & Adamson, M. M. (2017). DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans. NeuroImage. Clinical, 16, 1-16. https://doi.org/10.1016/j.nicl.2017.06.031
Main KL, et al. DTI Measures Identify Mild and Moderate TBI Cases Among Patients With Complex Health Problems: a Receiver Operating Characteristic Analysis of U.S. Veterans. Neuroimage Clin. 2017;16:1-16. PubMed PMID: 28725550.
TY - JOUR
T1 - DTI measures identify mild and moderate TBI cases among patients with complex health problems: A receiver operating characteristic analysis of U.S. veterans.
AU - Main,Keith L,
AU - Soman,Salil,
AU - Pestilli,Franco,
AU - Furst,Ansgar,
AU - Noda,Art,
AU - Hernandez,Beatriz,
AU - Kong,Jennifer,
AU - Cheng,Jauhtai,
AU - Fairchild,Jennifer K,
AU - Taylor,Joy,
AU - Yesavage,Jerome,
AU - Wesson Ashford,J,
AU - Kraemer,Helena,
AU - Adamson,Maheen M,
Y1 - 2017/06/24/
PY - 2016/08/15/received
PY - 2017/06/10/revised
PY - 2017/06/23/accepted
PY - 2017/7/21/entrez
PY - 2017/7/21/pubmed
PY - 2018/4/24/medline
KW - AD, axial diffusivity
KW - Axon degeneration
KW - CC, corpus callosum
KW - Concussion
KW - DAI, diffuse axonal injury
KW - DTI, diffusion tensor imaging
KW - FA, fractional anisotropy
KW - GN, genu
KW - Imaging
KW - LAT, left anterior thalamic tract
KW - LCG, left cingulum
KW - LCH, left cingulum – hippocampus
KW - LCS, left cortico-spinal tract
KW - LIF, left inferior fronto-occipital fasciculus
KW - LIL, left inferior longitudinal fasciculus
KW - LSL, left superior longitudinal fasciculus
KW - LST, left superior longitudinal fasciculus – temporal
KW - LUN, left uncinate
KW - MD, mean diffusivity
KW - Neurodegeneration
KW - PTSD, post-traumatic stress disorder
KW - RAT, right anterior thalamic tract
KW - RCG, right cingulum
KW - RCH, right cingulum – Hippocampus
KW - RCS, right cortico-spinal tract
KW - RD, radial diffusivity
KW - RIF, right inferior fronto-occipital fasciculus
KW - RIL, right inferior longitudinal fasciculus
KW - ROC, receiver operating characteristic
KW - RSL, right superior longitudinal fasciculus
KW - RST, right superior longitudinal fasciculus – temporal
KW - RUN, right uncinate
KW - SP, splenium
KW - TBI, traumatic brain injury
KW - Traumatic brain injury
SP - 1
EP - 16
JF - NeuroImage. Clinical
JO - Neuroimage Clin
VL - 16
N2 - Standard MRI methods are often inadequate for identifying mild traumatic brain injury (TBI). Advances in diffusion tensor imaging now provide potential biomarkers of TBI among white matter fascicles (tracts). However, it is still unclear which tracts are most pertinent to TBI diagnosis. This study ranked fiber tracts on their ability to discriminate patients with and without TBI. We acquired diffusion tensor imaging data from military veterans admitted to a polytrauma clinic (Overall n = 109; Age: M = 47.2, SD = 11.3; Male: 88%; TBI: 67%). TBI diagnosis was based on self-report and neurological examination. Fiber tractography analysis produced 20 fiber tracts per patient. Each tract yielded four clinically relevant measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity). We applied receiver operating characteristic (ROC) analyses to identify the most diagnostic tract for each measure. The analyses produced an optimal cutpoint for each tract. We then used kappa coefficients to rate the agreement of each cutpoint with the neurologist's diagnosis. The tract with the highest kappa was most diagnostic. As a check on the ROC results, we performed a stepwise logistic regression on each measure using all 20 tracts as predictors. We also bootstrapped the ROC analyses to compute the 95% confidence intervals for sensitivity, specificity, and the highest kappa coefficients. The ROC analyses identified two fiber tracts as most diagnostic of TBI: the left cingulum (LCG) and the left inferior fronto-occipital fasciculus (LIF). Like ROC, logistic regression identified LCG as most predictive for the FA measure but identified the right anterior thalamic tract (RAT) for the MD, RD, and AD measures. These findings are potentially relevant to the development of TBI biomarkers. Our methods also demonstrate how ROC analysis may be used to identify clinically relevant variables in the TBI population.
SN - 2213-1582
UR - https://www.unboundmedicine.com/medline/citation/28725550/DTI_measures_identify_mild_and_moderate_TBI_cases_among_patients_with_complex_health_problems:_A_receiver_operating_characteristic_analysis_of_U_S__veterans_
L2 - https://linkinghub.elsevier.com/retrieve/pii/S2213-1582(17)30162-6
DB - PRIME
DP - Unbound Medicine
ER -