BACKGROUND AND PURPOSE: Diffuse axonal injury (DAI) after traumatic brain injury (TBI) is important in patient assessment and prognosis, yet they are underestimated with conventional imaging techniques. We used MR spectroscopic imaging (MRSI) to detect DAI and determine whether metabolite ratios are accurate in predicting long-term outcomes and to examine regional differences in injury between children with TBI and control subjects. METHODS: Forty children with TBI underwent transverse proton MRSI through the level of the corpus callosum within 1-16 days after injury. T2-weighted, fluid-attenuated inversion recovery, and susceptibility-weighted MR imaging was used to identify voxels as normal-appearing or as nonhemorrhagic or hemorrhagic injury. Neurologic outcome was evaluated at 6-12 months after injury. Metabolite ratios for total (all voxels), normal-appearing, and hemorrhagic brain were compared and used in a logistic regression model to predict long-term outcome. Total and regional metabolite ratios were compared with control data. RESULTS: A significant decrease in N-acetylaspartate (NAA)/creatine (Cr) and increase in choline (Cho)/Cr (evidence of DAI) was observed in normal-appearing (P < .05) and visibly injured (hemorrhagic) brain (P < .001) compared with controls. In normal-appearing brain NAA/Cr decreased more in patients with poor outcomes (1.32 +/- 0.54) than in those with good outcomes (1.61 +/- 0.50, P = .01) or control subjects (1.86 +/- 0.1, P = .00). In visibly injured brains, ratios were similarly altered in all patients. In predicting outcomes, ratios from normal-appearing and visibly-injured brain were 85% and 67% accurate, respectively. CONCLUSION: MRSI can depict injury in brain that appears normal on imaging and is useful for predicting long-term outcomes.
BACKGROUND AND PURPOSE: Diffuse axonal injury (DAI) after traumatic brain injury (TBI) is important in patient assessment and prognosis, yet they are underestimated with conventional imaging techniques. We used MR spectroscopic imaging (MRSI) to detect DAI and determine whether metabolite ratios are accurate in predicting long-term outcomes and to examine regional differences in injury between children with TBI and control subjects. METHODS: Forty children with TBI underwent transverse proton MRSI through the level of the corpus callosum within 1-16 days after injury. T2-weighted, fluid-attenuated inversion recovery, and susceptibility-weighted MR imaging was used to identify voxels as normal-appearing or as nonhemorrhagic or hemorrhagic injury. Neurologic outcome was evaluated at 6-12 months after injury. Metabolite ratios for total (all voxels), normal-appearing, and hemorrhagic brain were compared and used in a logistic regression model to predict long-term outcome. Total and regional metabolite ratios were compared with control data. RESULTS: A significant decrease in N-acetylaspartate (NAA)/creatine (Cr) and increase in choline (Cho)/Cr (evidence of DAI) was observed in normal-appearing (P < .05) and visibly injured (hemorrhagic) brain (P < .001) compared with controls. In normal-appearing brain NAA/Cr decreased more in patients with poor outcomes (1.32 +/- 0.54) than in those with good outcomes (1.61 +/- 0.50, P = .01) or control subjects (1.86 +/- 0.1, P = .00). In visibly injured brains, ratios were similarly altered in all patients. In predicting outcomes, ratios from normal-appearing and visibly-injured brain were 85% and 67% accurate, respectively. CONCLUSION:MRSI can depict injury in brain that appears normal on imaging and is useful for predicting long-term outcomes.
Authors: G Sinson; L J Bagley; K M Cecil; M Torchia; J C McGowan; R E Lenkinski; T K McIntosh; R I Grossman Journal: AJNR Am J Neuroradiol Date: 2001-01 Impact factor: 3.825
Authors: C S A Macmillan; J M Wild; J M Wardlaw; P J D Andrews; I Marshall; V J Easton Journal: Acta Neurochir (Wien) Date: 2002-09 Impact factor: 2.216
Authors: Karen A Tong; Stephen Ashwal; Barbara A Holshouser; Lori A Shutter; Gwenael Herigault; E Mark Haacke; Daniel K Kido Journal: Radiology Date: 2003-05 Impact factor: 11.105
Authors: Elisabeth A Wilde; Sylvain Bouix; David F Tate; Alexander P Lin; Mary R Newsome; Brian A Taylor; James R Stone; James Montier; Samuel E Gandy; Brian Biekman; Martha E Shenton; Gerald York Journal: Brain Imaging Behav Date: 2015-09 Impact factor: 3.978
Authors: Robert W Van Boven; Greg S Harrington; David B Hackney; Andreas Ebel; Grant Gauger; J Douglas Bremner; Mark D'Esposito; John A Detre; E Mark Haacke; Clifford R Jack; William J Jagust; Denis Le Bihan; Chester A Mathis; Susanne Mueller; Pratik Mukherjee; Norbert Schuff; Anthony Chen; Michael W Weiner Journal: J Rehabil Res Dev Date: 2009
Authors: Stephen Ashwal; Karen A Tong; Nirmalya Ghosh; Brenda Bartnik-Olson; Barbara A Holshouser Journal: J Child Neurol Date: 2014-06-22 Impact factor: 1.987
Authors: Su Xu; Jiachen Zhuo; Jennifer Racz; Da Shi; Steven Roys; Gary Fiskum; Rao Gullapalli Journal: J Neurotrauma Date: 2011-09-29 Impact factor: 5.269
Authors: M E Shenton; H M Hamoda; J S Schneiderman; S Bouix; O Pasternak; Y Rathi; M-A Vu; M P Purohit; K Helmer; I Koerte; A P Lin; C-F Westin; R Kikinis; M Kubicki; R A Stern; R Zafonte Journal: Brain Imaging Behav Date: 2012-06 Impact factor: 3.978
Authors: Talin Babikian; Sarah Deboard Marion; Sarah Copeland; Jeffry R Alger; Joseph O'Neill; Fabienne Cazalis; Richard Mink; Christopher C Giza; Jennifer A Vu; Suzanne M Hilleary; Claudia L Kernan; Nina Newman; Robert F Asarnow Journal: J Neurotrauma Date: 2010-03 Impact factor: 5.269