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Objective: To determine the independent and synergistic effects of amyloid and small vessel disease (SVD) burden on longitudinal cognitive decline in patients with subcortical vascular dementia (SVaD). Methods: A longitudinal cohort study was conducted involving patients from outpatient clinics of 2 tertiary referral centers. Sixty-one patients with SVaD were prospectively recruited and underwent MRI, 11C–Pittsburgh compound B (PiB) PET at baseline, and a 3-year annual neuropsychological follow-up. Effects of PiB positivity and SVD markers (white matter hyperintensities [WMH], lacunes, and microbleeds) on longitudinal cognitive decline were evaluated using generalized estimation equation after controlling for age, sex, education, APOE4 allele, and follow-up interval. Results: When individual neuropsychological tests were used as outcome measures, PiB positivity was associated with faster cognitive decline in attention, visuospatial, visual memory, and global cognition function. Higher WMH burden was associated with faster cognitive decline in attention, visuospatial, visual recognition memory, and semantic/phonemic fluency function, whereas lacunes and microbleeds had no significant effects. When global dementia rating (Clinical Dementia Rating sum of boxes) was considered as an outcome measure, however, only PiB positivity was associated with faster cognitive decline. Significant interactions between PiB positivity and higher SVD burden were found to affect cognitive decline in semantic word fluency (from WMH burden) and global dementia rating (from microbleed burden). Conclusions: In SVaD patients, amyloid burden, independently or interactively with SVD, contributed to longitudinal cognitive decline. Amyloid deposition was the strongest poor prognostic factor.

Objectives: We aimed to investigate the relationship between education and cortical thickness in cognitively normal individuals to determine whether education attenuated the association of advanced aging and cortical thinning. Methods: A total of 1,959 participants, in whom education levels were available, were included in the final analysis. Cortical thickness was measured on high-resolution MRIs using a surface-based method. Multiple linear regression analysis was performed for education level and cortical thickness, after controlling for possible confounders. Results: High levels of education were correlated with increased mean cortical thickness throughout the entire cortex ( p = 0.003). This association persisted after controlling for vascular risk factors. Statistical maps of cortical thickness showed that the high levels of education were correlated with increased cortical thickness in the bilateral premotor areas, anterior cingulate cortices, perisylvian areas, right superior parietal lobule, left lingual gyrus, and occipital pole. There were also interactive effects of age and education on the mean cortical thickness ( p = 0.019). Conclusions: Our findings suggest the protective effect of education on cortical thinning in cognitively normal older individuals, regardless of vascular risk factors. This effect was found only in the older participants, suggesting that the protective effects of education on cortical thickness might be achieved by increased resistance to structural loss from aging rather than by simply providing a fixed advantage in the brain.

Background: We tested our hypothesis that the white matter network might mediate the effect of amyloid and small vessel disease (SVD) on cortical thickness and/or cognition. Methods: We prospectively recruited 232 patients with cognitive impairment. Amyloid was assessed using Pittsburgh compound B–PET. SVD was quantified as white matter hyperintensity volume and lacune number. The regional white matter network connectivity was measured as regional nodal efficiency by applying graph theoretical analysis to diffusion tensor imaging data. We measured cortical thickness and performed neuropsychological tests. Results: SVD burden was associated with decreased nodal efficiency in the bilateral frontal, lateral temporal, lateral parietal, and occipital regions. Path analyses showed that the frontal nodal efficiency mediated the effect of SVD on the frontal atrophy and frontal-executive dysfunction. The temporoparietal nodal efficiency mediated the effect of SVD on the temporoparietal atrophy and memory dysfunction. However, Pittsburgh compound B retention ratio affected cortical atrophy and cognitive impairment without being mediated by nodal efficiency. Conclusions: We suggest that a disrupted white matter network mediates the effect of SVD, but not amyloid, on specific patterns of cortical atrophy and/or cognitive impairment. Therefore, our findings provide insight to better understand how amyloid and SVD burden can give rise to brain atrophy or cognitive impairment in specific patterns.

Objective: The purpose of this study was to propose new criteria for differentiating Pittsburgh compound B (PiB)-negative from PiB-positive subcortical vascular dementia (SVaD) using clinical and MRI variables. Methods: We measured brain amyloid deposition using PiB-PET in 77 patients with SVaD. All patients met DSM-IV criteria for vascular dementia and had severe white matter hyperintensities on MRI, defined as a cap or band ≥10 mm as well as a deep white matter lesion ≥25 mm. Eleven models were considered to differentiate PiB(−) from PiB(+) SVaD using 4 variables, including age, number of lacunes, medial temporal atrophy (MTA), and APOE e4. The ideal cutoff values in each of the 11 models were selected using the highest Youden index. Results: A total of 49 of 77 patients (63.6%) tested negative for PiB retention, while 28 (36.4%) tested positive for PiB retention. The ideal model for differentiating PiB(−) from PiB(+) SVaD was as follows: age ≤75 years, ≥5 lacunes, and MTA ≤3, which together yielded an accuracy of 67.5%. Conclusion: When patients meet the DSM-IV criteria for vascular dementia and also have severe white matter hyperintensities, younger age, greater number of lacunes, and lesser MTA, these are predictive of a PiB(−) scan in patients with SVaD. Classification of evidence: This study provides Class II evidence that the combination of younger age, greater number of lacunes, and lesser MTA identifies patients with SVaD at lower risk of Alzheimer disease pathology.

To evaluate the differences between early-onset subcortical vascular cognitive impairment (EO-SVCI) and late-onset subcortical vascular cognitive impairment (LO-SVCI) with regard to pathologic burden, structural changes, and cognitive function.We prospectively recruited 142 patients from a single referral center. Patients were divided into EO-SVCI (n = 30, age at onset65 years) and LO-SVCI (n = 112, age at onset ≥ 65 years) groups. All patients underwent neuropsychological tests, 3T brain MRI, and [(11)C] Pittsburgh compound B (PiB)-PET. We compared pathologic burden such as small vessel disease and amyloid burden; structural changes such as structural network, cortical thickness, and hippocampal volume; and cognitive function between EO-SVCI and LO-SVCI.EO-SVCI patients had more lacunes, while LO-SVCI patients had higher PiB standardized uptake value ratios. EO-SVCI patients exhibited more severe structural network disruptions in the frontal area, while LO-SVCI patients exhibited more severe cortical and hippocampal atrophy. Although disease severity did not differ between the 2 groups, frontal-executive dysfunction was more severe in EO-SVCI patients.EO-SVCI patients showed more vascular related factors, while LO-SVCI patients exhibited more Alzheimer disease-related characteristics. The greater number of lacunes in EO-SVCI might account for the more severe frontal network disruption and frontal-executive dysfunction, while the greater amyloid burden in LO-SVCI might account for the more severe cortical and hippocampal atrophy. Our findings suggest that the age at onset is a crucial factor that determines distinct features in SVCI patients, such as pathologic burden, structural changes, and cognitive function.

Objective: To investigate the topographic changes of white matter (WM) integrity and cortical thickness related to gait disturbances and determine whether these neural correlates mediate the association between cerebral small vessel disease (CSVD) and gait disturbances. Methods: A total of 129 patients with subcortical vascular cognitive impairment were included. CSVD severity was quantified as global and regional WM hyperintensities (WMH) volume and lacune and microbleed numbers. Amyloid burdens were assessed using Pittsburgh compound B (PiB)–PET scanning. Gait score was measured using a standardized scale. WM integrity was assessed by applying tract-based spatial statistics. Cortical thickness was measured using surface-based methods. Path analysis for gait score was performed using regional CSVD markers as predictors and fractional anisotropy (FA) and cortical thickness as mediators. Results: Periventricular WMH (PWMH) volume was associated with gait score, regardless of other CSVD. PiB retention ratio was not associated with gait score. Gait score was correlated with FA in the frontal and parietal WM and bilateral corpus callosum and with cortical thinning in the bilateral frontal and lateral temporo-parieto-occipital regions. Path analysis for gait score showed that PWMH contributed to gait disturbances with the mediation of mean FA or cortical thickness. Conclusions: Our findings suggest that WMH-related cortical thinning as well as disrupted integrity of periventricular WM is linked to gait disturbances.