Alterations of White Matter Integrity in Subcortical Ischemic Vascular Disease with and Without Cognitive Impairment: a TBSS Study
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Patients with subcortical ischemic vascular disease (SIVD) may exhibit a high risk of cognitive impairment (CI) by disruption of white matter (WM) integrity. Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore whole brain WM alterations at an asymptomatic stage of the disease, which might be correlated with underlying cognitive disorders. We aim to investigate alterations in WM microstructures and evaluate the relationships between the mean values of diffusion metrics (FA, MD, AD, and RD) and cognitive assessments in SIVD patients. Fifty SIVD patients with (SVCI, N = 25) and without (pre-SVCI, N = 25) cognitive impairments and normal controls (NC, N = 23) underwent DTI and neuropsychological examinations. DTI data were analyzed via TBSS to detect significant changes in WM tracts. Spearman correlation analysis was performed to evaluate relationships between the mean values of diffusion indices and the cognitive assessments. In general, extensive symmetrically altered areas that involved approximately the entire cerebral WM were noted in the pre-SVCI group but were less distinct than that noted in the SVCI group compared with NCs. The genu of corpus callosum exhibited the most damaged WM fiber. Throughout WM, FA was decreased, whereas MD, AD, and RD were increased. Some specific WM tracts in patient groups were significantly correlated with the severity of white matter hyperintensity (WMH), cognitive assessments about executive functions and processing speed. WM integrity has already been damaged at the pre-SVCI stage, which would be associate with future cognitive dysfunction. DTI could potentially establish early biomarkers to detect underlying mechanisms of SIVD.
KeywordsDiffusion tensor imaging White matter Cognitive dysfunction Cerebrovascular disorder
Our team thank all patients and healthy volunteers for their participation.
This work was supported by the National Science Foundation of China (NO.81671666), the Doctoral Scientific Funds of North Sichuan Medical College (CBY16-QD04), and the Key Project Sichuan Provincial Department of Education (18ZA0211).
- Alves GS, Knöchel VO, Knöchel C, Carvalho AF, Pantel J, Engelhardt E, Laks J (2015) Integrating retrogenesis theory to Alzheimer’s disease pathology: insight from DTI-TBSS investigation of the white matter microstructural integrity Biomed Research International 2015Google Scholar
- Benjamin P, Zeestraten E, Lambert C, Chis Ster I, Williams OA, Lawrence AJ, Patel B, MacKinnon AD, Barrick TR, Markus HS (2016) Progression of MRI markers in cerebral small vessel disease: sample size considerations for clinical trials. J Cereb Blood Flow Metab 36:228–240. https://doi.org/10.1038/jcbfm.2015.113 CrossRefPubMedPubMedCentralGoogle Scholar
- Ciulli S, Citi L, Salvadori E, Valenti R, Poggesi A, Inzitari D, Mascalchi M, Toschi N, Pantoni L, Diciotti S (2016) Prediction of impaired performance in trail making test in MCI patients with small vessel disease using DTI data. IEEE J Biomed Health Inform 20:1026–1033. https://doi.org/10.1109/JBHI.2016.2537808 CrossRefPubMedGoogle Scholar
- Duering M, Gonik M, Malik R, Zieren N, Reyes S, Jouvent E, Hervé D, Gschwendtner A, Opherk C, Chabriat H, Dichgans M (2013) Identification of a strategic brain network underlying processing speed deficits in vascular cognitive impairment. Neuroimage 66:177–183. https://doi.org/10.1016/j.neuroimage.2012.10.084 CrossRefPubMedGoogle Scholar
- Huang J et al (2018) White matter microstructural alterations in clinically isolated syndrome and multiple sclerosis. J Clin Neurosci. https://doi.org/10.1016/j.jocn.2018.01.007
- Lawrence AJ, Patel B, Morris RG, Mackinnon AD, Rich PM, Barrick TR, Markus HS (2013) Correction: mechanisms of cognitive impairment in cerebral small vessel disease: multimodal MRI results from the St George’s cognition and neuroimaging in stroke (SCANS) study. PLoS One 8:e61014CrossRefPubMedPubMedCentralGoogle Scholar
- Palta P, Snitz B, Carlson MC (2016) Neuropsychologic assessment. In: Neuroepidemiology. Handb Clin Neurol:107–119. https://doi.org/10.1016/b978-0-12-802973-2.00007-0
- Sachdev P, Kalaria R, O'Brien J, Skoog I, Alladi S, Black SE, Blacker D, Blazer DG, Chen C, Chui H, Ganguli M, Jellinger K, Jeste DV, Pasquier F, Paulsen J, Prins N, Rockwood K, Roman G, Scheltens P, Internationlal Society for Vascular Behavioral and Cognitive Disorders (2014) Diagnostic criteria for vascular cognitive disorders: a VASCOG statement. Alzheimer Dis Assoc Disord 28:206–218. https://doi.org/10.1097/wad.0000000000000034 CrossRefPubMedPubMedCentralGoogle Scholar
- Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TEJ (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487–1505. https://doi.org/10.1016/j.neuroimage.2006.02.024 CrossRefGoogle Scholar
- Sun Y, Cao W, Ding W, Wang Y, Han X, Zhou Y, Xu Q, Zhang Y, Xu J (2016) Cerebral blood flow alterations as assessed by 3D ASL in cognitive impairment in patients with subcortical vascular cognitive impairment: a marker for disease severity. Front Aging Neurosci 8:211. https://doi.org/10.3389/fnagi.2016.00211 CrossRefPubMedPubMedCentralGoogle Scholar
- Sun Q, Chen GQ, Wang XB, Yu Y, Hu YC, Yan LF, Zhang X, Yang Y, Zhang J, Liu B, Wang CC, Ma Y, Wang W, Han Y, Cui GB (2018) Alterations of white matter integrity and hippocampal functional connectivity in type 2 diabetes without mild cognitive impairment. Front Neuroanat 12:21. https://doi.org/10.3389/fnana.2018.00021 CrossRefPubMedPubMedCentralGoogle Scholar
- van der Holst HM, Tuladhar AM, Zerbi V, van Uden IWM, de Laat KF, van Leijsen EMC, Ghafoorian M, Platel B, Bergkamp MI, van Norden AGW, Norris DG, van Dijk EJ, Kiliaan AJ, de Leeuw FE (2018) White matter changes and gait decline in cerebral small vessel disease. Neuroimage Clin 17:731–738. https://doi.org/10.1016/j.nicl.2017.12.007 CrossRefPubMedGoogle Scholar
- Wardlaw JM, Smith EE, Biessels GJ, Cordonnier C, Fazekas F, Frayne R, Lindley RI, O’Brien JT, Barkhof F, Benavente OR, Black SE, Brayne C, Breteler M, Chabriat H, Decarli C, de Leeuw FE, Doubal F, Duering M, Fox NC, Greenberg S, Hachinski V, Kilimann I, Mok V, Oostenbrugge Rv, Pantoni L, Speck O, Stephan BC, Teipel S, Viswanathan A, Werring D, Chen C, Smith C, van Buchem M, Norrving B, Gorelick PB, Dichgans M, STandards for ReportIng Vascular changes on nEuroimaging (STRIVE v1) (2013) Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 12:822–838CrossRefPubMedPubMedCentralGoogle Scholar
- Yuan JL, Wang SK, Guo XJ, Teng LL, Jiang H, Gu H, Hu WL (2017) Disconnections of cortico-subcortical pathways related to cognitive impairment in patients with Leukoaraiosis: a preliminary diffusion tensor imaging study. Eur Neurol 78:41–47. https://doi.org/10.1159/000477899 CrossRefPubMedGoogle Scholar
- Zeestraten EA, Lawrence AJ, Lambert C, Benjamin P, Brookes RL, Mackinnon AD, Morris RG, Barrick TR, Markus HS (2017) Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease. Neurology 89:1869–1876. https://doi.org/10.1212/wnl.0000000000004594 CrossRefPubMedPubMedCentralGoogle Scholar
- Zhou X, Hu X, Zhang C, Wang H, Zhu X, Xu L, Sun Z, Yu Y (2016) Aberrant functional connectivity and structural atrophy in subcortical vascular cognitive impairment: relationship with cognitive impairments. Front Aging Neurosci 8:14. https://doi.org/10.3389/fnagi.2016.00014 CrossRefPubMedPubMedCentralGoogle Scholar