Changes in gray matter volume and their correlation with cognitive impairment in patients with subcortical vascular cognitive impairment / 中华神经科杂志

ABSTRACT

Objective:To analyze the changes of total gray matter volume in patients with subcortical vascular cognitive impairment (SVCI) and their correlation with cognitive impairment.Methods:Data of fifty patients with subcortical ischemic vascular disease (SIVD) who admitted to the outpatient department or ward of the Department of Neurology, the First Affiliated Hospital of Anhui Medical University from November 2017 to March 2019, were collected for the study, including 23 patients with SVCI and 27 patients with subcortical ischemic vascular disease without cognitive impairment (SIVD-NCI). All subjects were assessed using the Minimal Mental State Examination (MMSE), the Montreal Cognitive Assessment scale (MoCA), the Cambridge Cognitive Assessment scale for the elderly-Chinese version (CAMCOG-C), the Stroop test, the Geriatric Depression Scale, and the Activity of Daily Living scale (ADL). All subjects underwent 3.0 T magnetic resonance imaging scans to obtain T 1WI, T 2WI, fluid attenuated inversion recovery (FLAIR) images and 3D-T 1 structural image data. Voxel-based morphometry (VBM) was used to analyze and compare the differences in gray matter volume between SVCI group and SIVD-NCI group. Results:Compared with the SIVD-NCI group, the MMSE score (22.00 (20.00, 24.00) vs 28.00 (27.00, 29.00), Z=-6.073, P<0.001), MoCA score (15.00 (13.00,19.00) vs 24.00 (23.00, 26.00), Z=-5.233, P<0.001), total score of CAMCOG-C (67.65±13.35 vs 88.41±10.98, t=-6.032, P<0.001) and the directional (8.00 (5.00, 9.00) vs 10.00 (9.00, 10.00), Z=-4.133, P<0.001), language (24.00 (21.00, 26.00) vs 27.00 (24.00, 28.00), Z=-3.171, P=0.002), memory (11.00 (9.00, 15.00) vs 19.00 (17.00, 21.00), Z=-4.648, P<0.001), attention (4.00 (2.00, 6.00) vs 7.00 (6.00, 7.00), Z=-3.929, P<0.001), executive (8.00 (6.00, 10.00) vs 11.00 (9.00, 12.00), Z=-3.696, P<0.001), calculation (2.00 (2.00, 2.00) vs 2.00 (2.00, 2.00), Z=-2.528, P=0.011), thinking (6.00 (3.00, 6.00) vs 6.00 (6.00, 8.00), Z=-4.029, P<0.001), perception (6.00 (6.00, 7.00) vs 8.00 (7.00, 9.00), Z=-4.221, P<0.001) in the SVCI group were obviously decreased. ADL score (21.00 (20.00, 26.00) vs 20.00 (20.00, 20.00), Z=-2.634, P=0.008) and Stroop test score (28.61±4.53 vs 20.04±6.07, t=5.704, P<0.001) were significantly higher in the SVCI group than in the SIVD-NCI group. The total gray matter volume ((556.86±49.19) mm 3vs (618.13±51.73) mm 3, t=-3.572, P=0.001) and white matter volume ((479.35±48.17) mm 3vs (507.22±43.84) mm 3, t=-2.141, P=0.037) in the SVCI group were smaller than that in the SIVD-NCI group. VBM analysis showed that the SVCI group had significantly smaller gray matter volume in the left inferior temporal gyrus ( t=5.17, P<0.001, family wise error (FWE) correction), right middle temporal gyrus ( t=4.99, P<0.001, FWE correction), right orbital superior frontal gyrus ( t=5.02, P<0.001, FWE correction), left middle occipital gyrus ( t=5.67, P<0.001, FWE correction), right middle occipital gyrus ( t=5.77, P<0.001, FWE correction). MoCA score was positively correlated with the volume of gray matter in the left inferior temporal gyrus of patients with SIVD ( r=0.292, P<0.05), language function score was positively correlated with the volume of gray matter in the left inferior temporal gyrus ( r=0.322, P<0.05), and Stroop test score was negatively correlated with gray matter volume in the left inferior temporal gyrus ( r=-0.329, P<0.05). Conclusion:Gray matter atrophy exists in multiple brain regions in patients with SVCI, and these atrophic brain regions are associated with cognitive impairment of SIVD.