S Chung1, X Wang2, E Fieremans2, J F Rath3, P Amorapanth3, F-Y A Foo4, C J Morton2, D S Novikov2, S R Flanagan3, Y W Lui2. 1. From the Center for Advanced Imaging Innovation and Research & Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology (S.C., X.W., E.F., C.J.M., D.S.N., Y.W.L.) sohae.chung@nyulangone.org. 2. From the Center for Advanced Imaging Innovation and Research & Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology (S.C., X.W., E.F., C.J.M., D.S.N., Y.W.L.). 3. Department of Rehabilitation Medicine (J.F.R., P.A., S.R.F.), New York University School of Medicine, New York, New York. 4. Department of Neurology (F.-Y.A.F.), New York University Langone Health, New York, New York.
Abstract
BACKGROUND AND PURPOSE: Working memory impairment is one of the most troubling and persistent symptoms after mild traumatic brain injury (MTBI). Here we investigate how working memory deficits relate to detectable WM microstructural injuries to discover robust biomarkers that allow early identification of patients with MTBI at the highest risk of working memory impairment. MATERIALS AND METHODS: Multi-shell diffusion MR imaging was performed on a 3T scanner with 5 b-values. Diffusion metrics of fractional anisotropy, diffusivity and kurtosis (mean, radial, axial), and WM tract integrity were calculated. Auditory-verbal working memory was assessed using the Wechsler Adult Intelligence Scale, 4th ed, subtests: 1) Digit Span including Forward, Backward, and Sequencing; and 2) Letter-Number Sequencing. We studied 19 patients with MTBI within 4 weeks of injury and 20 healthy controls. Tract-Based Spatial Statistics and ROI analyses were performed to reveal possible correlations between diffusion metrics and working memory performance, with age and sex as covariates. RESULTS: ROI analysis found a significant positive correlation between axial kurtosis and Digit Span Backward in MTBI (Pearson r = 0.69, corrected P = .04), mainly present in the right superior longitudinal fasciculus, which was not observed in healthy controls. Patients with MTBI also appeared to lose the normal associations typically seen in fractional anisotropy and axonal water fraction with Letter-Number Sequencing. Tract-Based Spatial Statistics results also support our findings. CONCLUSIONS: Differences between patients with MTBI and healthy controls with regard to the relationship between microstructure measures and working memory performance may relate to known axonal perturbations occurring after injury.
BACKGROUND AND PURPOSE:Working memory impairment is one of the most troubling and persistent symptoms after mild traumatic brain injury (MTBI). Here we investigate how working memory deficits relate to detectable WM microstructural injuries to discover robust biomarkers that allow early identification of patients with MTBI at the highest risk of working memory impairment. MATERIALS AND METHODS: Multi-shell diffusion MR imaging was performed on a 3T scanner with 5 b-values. Diffusion metrics of fractional anisotropy, diffusivity and kurtosis (mean, radial, axial), and WM tract integrity were calculated. Auditory-verbal working memory was assessed using the Wechsler Adult Intelligence Scale, 4th ed, subtests: 1) Digit Span including Forward, Backward, and Sequencing; and 2) Letter-Number Sequencing. We studied 19 patients with MTBI within 4 weeks of injury and 20 healthy controls. Tract-Based Spatial Statistics and ROI analyses were performed to reveal possible correlations between diffusion metrics and working memory performance, with age and sex as covariates. RESULTS: ROI analysis found a significant positive correlation between axial kurtosis and Digit Span Backward in MTBI (Pearson r = 0.69, corrected P = .04), mainly present in the right superior longitudinal fasciculus, which was not observed in healthy controls. Patients with MTBI also appeared to lose the normal associations typically seen in fractional anisotropy and axonal water fraction with Letter-Number Sequencing. Tract-Based Spatial Statistics results also support our findings. CONCLUSIONS: Differences between patients with MTBI and healthy controls with regard to the relationship between microstructure measures and working memory performance may relate to known axonal perturbations occurring after injury.
Authors: Susumu Mori; Kenichi Oishi; Hangyi Jiang; Li Jiang; Xin Li; Kazi Akhter; Kegang Hua; Andreia V Faria; Asif Mahmood; Roger Woods; Arthur W Toga; G Bruce Pike; Pedro Rosa Neto; Alan Evans; Jiangyang Zhang; Hao Huang; Michael I Miller; Peter van Zijl; John Mazziotta Journal: Neuroimage Date: 2008-01-03 Impact factor: 6.556
Authors: E J Grossman; J H Jensen; J S Babb; Q Chen; A Tabesh; E Fieremans; D Xia; M Inglese; R I Grossman Journal: AJNR Am J Neuroradiol Date: 2012-11-22 Impact factor: 3.825
Authors: Sohae Chung; Els Fieremans; Xiuyuan Wang; Nuri E Kucukboyaci; Charles J Morton; James Babb; Prin Amorapanth; Farng-Yang A Foo; Dmitry S Novikov; Steven R Flanagan; Joseph F Rath; Yvonne W Lui Journal: J Neurotrauma Date: 2018-04-15 Impact factor: 5.269
Authors: Yicheng Long; Xuan Ouyang; Zhening Liu; Xudong Chen; Xinran Hu; Edwin Lee; Eric Y H Chen; Weidan Pu; Baoci Shan; Robert M Rohrbaugh Journal: Front Psychiatry Date: 2018-08-28 Impact factor: 4.157
Authors: S A Mohammad; N H Nashaat; A A M B Okba; A Kilany; A S Abdel-Rahman; A M Abd-Elhamed; E R Abdelraouf Journal: AJNR Am J Neuroradiol Date: 2022-06-09 Impact factor: 4.966