The matter of white and gray matter in cognitive impairment

Cognitive impairment spans from minor subjective cognitive impairment to disabling dementia. Many biomarkers have been developed to monitor different aspects of cognitive impairment. Magnetic resonance imaging is the most used neuroimaging biomarker in research and can measure gray matter (GM) and white matter (WM) changes. Although there is a consensus that atrophy in GM is a marker for neuronal loss, there is little evidence assessing the role of WM changes. The aim of this thesis is to first develop a tool to reliably measure the changes in WM in the form of white matter hyperintensities (WMH) and second to evaluate the role of WM and GM changes in the early stages of cognitive decline. In Study I and Study II, a fully automated method for segmentation of WMH has been developed and validated. Validation results indicated that the WMH segmentation was performed with high similarity to manual delineation and with superb reproducibility. In Study III, coronary heart disease (CHD) and hypertension, which are known to contribute to WM damage, were examined and their effect on GM and WM changes was investigated on a group of 69 individuals with 30-year follow-up. We showed that CHD and hypertension indeed affect the GM volume and thickness and the effect of CHD is partially independent of hypertension. However, the results indicate no significant effect on WMH, which we believe is due to the fact that WMH were measured as a crude total volume. In Study IV, a pipeline was developed to isolate the WM tract connecting each GM region to the rest of the brain and to measure the burden of WMH on each tract, hereinafter tractbased WMH. We used a cohort of 257 cognitively normal (CTL), 87 subjective cognitive impairment (SCI) and 124 mild cognitive impairment (MCI) subjects and examined their GM volume, tract-based WMH and cognitive performance. Our results indicated that the fraction of variance in GM volume that can be explained by tract-based WMH in SCI subjects is significantly higher than in both CTL and MCI subjects. The results also showed that in subjects with high and low cognitive performance, tract-based WMH can barely explain any GM volume change. However, in subjects with slight cognitive impairment tract-based WMH can explain the changes in GM volume. In summary, we investigated different ways of measuring the damage of WMH and showed that the role of WMH is more pronounced when measuring them in relation to the WM tract they affect. The effect of WMH on GM has been shown to be mainly in the earlier stages of cognitive impairment

Can measuring hippocampal atrophy with a fully automatic method be substantially less noisy than manual segmentation over both 1 and 3 years?

To quantify the "segmentation noise" of several widely used fully automatic methods for measuring longitudinal hippocampal atrophy in Alzheimer's disease and compare the results to the segmentation noise of manual segmentation over both 1 and 3 years. The segmentation noise of 5 longitudinal hippocampal atrophy measurement methods was quantified, including checking its Gaussianity, using 264 subjects from the ADNI1 back-to-back (BTB) data set over both 1 year and 3 year intervals. The segmentation methods were FreeSurfer 5.3.0 both cross sectional and longitudinal, FreeSurfer 6.0.0 longitudinal, MAPS-HBSI and FSL/FIRST 5.0.8. The BTB manual segmentation of 75 ADNI subjects from a previous study provided the manual distributions for comparison. All methods, including the manual segmentation, violated the Gaussianity assumption. Two methods, FreeSurfer 6.0.0 and MAPS-HBSI, had a segmentation noise substantially less than a surrogate for manual segmentation. FreeSurfer 5.3.0 longitudinal was confirmed as a surrogate for manual segmentation. The violation of the Gaussian assumption by the segmentation methods assessed, including manual, suggests results of previous studies that assumed Gaussian statistics without confirmation may need review. Fully automatic FreeSurfer 6.0.0 and MAPS-HBSI both have lower segmentation noise than manual requiring less than two thirds of the subjects to detect the same treatment effect

Coronary heart disease and cortical thickness, gray matter and white matter lesion volumes on MRI.

Coronary heart disease (CHD) has been linked with cognitive decline and dementia in several studies. CHD is strongly associated with blood pressure, but it is not clear how blood pressure levels or changes in blood pressure over time affect the relation between CHD and dementia-related pathology. The aim of this study was to investigate relations between CHD and cortical thickness, gray matter volume and white matter lesion (WML) volume on MRI, considering CHD duration and blood pressure levels from midlife to three decades later. The study population included 69 elderly at risk of dementia who participated in the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study. CAIDE participants were examined in midlife, re-examined 21 years later, and then after additionally 7 years (in total up to 30 years follow-up). MRIs from the second re-examination were used to calculate cortical thickness, gray matter and WML volume. CHD diagnoses were obtained from the Finnish Hospital Discharge Register. Linear regression analyses were adjusted for age, sex, follow-up time and scanner type, and additionally total intracranial volume in GM volume analyses. Adding diabetes, cholesterol or smoking to the models did not influence the results. CHD was associated with lower thickness in multiple regions, and lower total gray matter volume, particularly in people with longer disease duration (>10 years). Associations between CHD, cortical thickness and gray matter volume were strongest in people with CHD and hypertension in midlife, and those with CHD and declining blood pressure after midlife. No association was found between CHD and WML volumes. Based on these results, long-term CHD seems to have detrimental effects on brain gray matter tissue, and these effects are influenced by blood pressure levels and their changes over time

Eye and hand motor interactions with the Symbol Digit Modalities Test in early multiple sclerosis

Purpose Eye and hand motor dysfunction may be present early in the disease course of relapsing-remitting multiple sclerosis (RRMS), and can affect the results on visual and written cognitive tests. We aimed to test for differences in saccadic initiation time (SI time) between RRMS patients and healthy controls, and whether SI time and hand motor speed interacted with the written version of the Symbol Digit Modalities Test (wSDMT). Methods Patients with RRMS (N=44, age 35.1±7.3 years), time since diagnosis <3 years and matched controls (N=41, age 33.2±6.8 years) were examined with ophthalmological, neurological and neuropsychological tests, as well as structural MRI (white matter lesion load (WMLL) and brainstem lesions), visual evoked potentials (VEP) and eye-tracker examinations of saccades. Results SI time was longer in RRMS than controls (p<0.05). SI time was not related to the Paced Auditory Serial Addition Test (PASAT), WMLL or to the presence of brainstem lesions. 9 hole peg test (9HP) correlated significantly with WMLL (r=0.58, p<0.01). Both SI time and 9HP correlated negatively with the results of wSDMT (r=−0.32, p<0.05, r=−0.47, p<0.01), but none correlated with the results of PASAT. Conclusions RRMS patients have an increased SI time compared to controls. Cognitive tests results, exemplified by the wSDMT, may be confounded by eye and hand motor function

CAIDE study and formation of the MRI population.

<p>CAIDE study and formation of the MRI population.</p

Statistical difference (t-value) maps of cortical thickness between CHD and control groups.

<p>Significant and FDR corrected (p<0.05) differences in cortical thickness between groups are displayed as color-labeled t-values on the surface of a standardized brain (warmer colors indicate thinner cortex). Analyses are adjusted for age, sex, follow-up time and scanner type.</p

Associations between CHD and cortical thickness, GM volume and WML volume according to the duration of CHD.

<p>Values are standardized β-coefficients (p-values) from linear regression analyses. All analyses are adjusted for age, sex, follow-up time and scanner type. GM volume analyses are additionally adjusted for TIV. P-values <0.05 are bold.</p><p>Associations between CHD and cortical thickness, GM volume and WML volume according to the duration of CHD.</p