Nutta-on Promjunyakul

Characterizing the white matter hyperintensity penumbra with cerebral blood flow measures.

Objective White matter hyperintensities (WMHs) are common with age, grow over time, and are associated with cognitive and motor impairments. Mechanisms underlying WMH growth are unclear. We aimed to determine the presence and extent of decreased normal appearing white matter (NAWM) cerebral blood flow (CBF) surrounding WMHs to identify ‘WM at risk’, or the WMH CBF penumbra. We aimed to further validate cross-sectional finding by determining whether the baseline WMH penumbra CBF predicts the development of new WMHs at follow-up. Methods Sixty-one cognitively intact elderly subjects received 3 T MPRAGE, FLAIR, and pulsed arterial spin labeling (PASL). Twenty-four subjects returned for follow-up MRI. The inter-scan interval was 18 months. A NAWM layer mask, comprised of fifteen layers, 1 mm thick each surrounding WMHs, was generated for periventricular (PVWMH) and deep (DWMH) WMHs. Mean CBF for each layer was computed. New WMH and persistent NAWM voxels for each penumbra layer were defined from follow-up MRI. Results CBF in the area surrounding WMHs was significantly lower than the total brain NAWM, extending approximately 12 mm from both the established PVWMH and DWMH. Voxels with new WMH at follow-up had significantly lower baseline CBF than voxels that maintained NAWM, suggesting that baseline CBF can predict the development of new WMHs over time. Conclusions A CBF penumbra exists surrounding WMHs, which is associated with future WMH expansion. ASL MRI can be used to monitor interventions to increase white matter blood flow for the prevention of further WM damage and its cognitive and motor consequences.

Less daily computer use is related to smaller hippocampal volumes in dementia-free elderly

(VAN), default mode network, and dorsal attention network) was assessed using template based rotation, an approach designed for use with existing network parcellations. A linear regression model with backward elimination (p<0.1 cut-off) was utilized with the FAQ as the dependent variable and the 4 networks as the predictors of interest. Covariates included age, sex, American National Adult Reading Test intelligence quotient (AMNART IQ, a proxy of premorbid IQ), processing speed, episodic memory, and fMRI confounders (signal-to-noise ratio, movement, and bad volumes). Results:There was a significant association between greater IADL impairment and reduced FPCN connectivity (b1⁄4-29.76, partial r(pr)1⁄4-0.36, p1⁄40.03) and increased VAN connectivity (b1⁄437.44, pr1⁄40.40, p1⁄40.02). Covariates retained in the model included premorbid IQ (b1⁄40.26, pr1⁄40.42, p1⁄40.01), processing speed (b1⁄40.12, pr1⁄4-0.37, p1⁄40.03), episodic memory (b1⁄4-0.11, pr1⁄4-0.29, p1⁄40.09), and movement (b1⁄427.61, pr1⁄40.33, p1⁄40.05). The overall model was significant (p1⁄40.005) and accounted for 41% of the variance. There was no significant association with the other networks. Conclusions:These results suggest that IADL impairment inMCI relates to a complex pattern of both reduced and increased connectivity in networks spanning frontal and parietal regions. Similar findings have been reported in a study using a global functioning measure, which consists of both IADL and cognition. Furthermore, reduced FPCNconnectivity has been associatedwith greater apathy, which has been associated with IADL impairment, and increased VAN connectivity has been associated with greater executive dysfunction, which has been associated with IADL impairment.

Baseline NAWM structural integrity and CBF predict periventricular WMH expansion over time

Objective We aimed to describe and compare baseline cerebral blood flow (CBF) and microstructural characteristics of normal-appearing white matter (NAWM) within the vulnerable periventricular white matter hyperintensity (PVWMH) penumbra region in predicting white matter hyperintensity (WMH) growth over time. Methods Fifty-two patients, aged 82.8 years, underwent serial brain MRI, including pulsed arterial spin labeling and diffusion tensor imaging (DTI). New WMH and persistent NAWM voxels in relation to WMH penumbra at follow-up were identified. Mean baseline CBF and DTI variables of the new WMH and persistent NAWM voxels were computed. Univariate analyses with paired t tests were performed. Generalized estimating equation analyses were used to compare the relationships of baseline CBF, and structural penumbras with WMH growth, controlling for confounders. Results Low baseline CBF and fractional anisotropy, and high mean diffusivity (MD), were independently associated with new PVWMH voxels, with MD being the best predictor of WMH growth. A separate model demonstrated that radial diffusivity had the strongest relationship with WMH growth compared with CBF and axial diffusivity. Conclusion CBF and DTI measures independently predict WMH growth over time. DTI is a more sensitive predictor of WMH growth than CBF, with WMH progression likely due to demyelinating injury secondary to low perfusion. Findings support the use of MD as a sensitive marker of NAWM vulnerability in future trials aimed at preserving WM integrity.