Percentage Of Intracranial Volume Research Articles

Brain White Matter Hyperintensities, Executive Dysfunction, Instability, and Falls in Older People: A Prospective Cohort Study

White matter hyperintensities (WMHs) are associated with fall risk factors in older people including reduced cognitive functioning and impaired balance and gait. This prospective study investigated relationships between WMHs, sensorimotor performance, executive functioning, and falls in a large sample of community-living older people. Two hundred and eighty-seven community-dwelling people aged 70-90 years, underwent structural magnetic resonance imaging and assessments of executive function (Trail-Making Tests), sensorimotor performance (Physiological Profile Assessment), and prospective monitoring of falls. Total WMH volume was quantified using an automated method. Fallers were defined as people who had at least one injurious or two noninjurious falls during the 12-month follow-up period. Participants with severe WMH burden (WMH volumes as a percentage of intracranial volume in the fourth quartile) performed poorly in the Trail-Making Test and Physiological Profile Assessment (p < .05) and had an increased risk of falls during the 12-month follow-up (relative risk = 1.63, 95% confidence interval 1.11-2.40). The association between WMHs and falls was little changed after adjusting for Trail-Making Test and Physiological Profile Assessment scores, age, sex, education, and a range of cardiovascular risk factors (relative risk = 1.55, 95% confidence interval 1.06-2.26). Greater WMH burden predicts falls over 12 months, and the association between greater burden of WMHs and falls appears to be independent of reduced executive function and sensorimotor performance. Strategies to reduce the development and progression of WMHs may contribute to future falls prevention in older people.

Progression of Cerebral Atrophy and White Matter Hyperintensities in Patients With Type 2 Diabetes

OBJECTIVEType 2 diabetes is associated with a moderate degree of cerebral atrophy and a higher white matter hyperintensity (WMH) volume. How these brain-imaging abnormalities evolve over time is unknown. The present study aims to quantify cerebral atrophy and WMH progression over 4 years in type 2 diabetes.RESEARCH DESIGN AND METHODSA total of 55 patients with type 2 diabetes and 28 age-, sex-, and IQ-matched control participants had two 1.5T magnetic resonance imaging scans with a 4-year interval. Volumetric measurements of total brain, peripheral cerebrospinal fluid (CSF), lateral ventricles, and WMH were performed with k-nearest neighbor–based probabilistic segmentation. All volumes were expressed as percentage of intracranial volume. Linear regression analyses, adjusted for age and sex, were performed to compare brain volumes between the groups and to identify determinants of volumetric change within the type 2 diabetic group.RESULTSAt baseline, patients with type 2 diabetes had a significantly smaller total brain volume and larger peripheral CSF volume than control participants. In both groups, all volumes showed a significant change over time. Patients with type 2 diabetes had a greater increase in lateral ventricular volume than control participants (mean adjusted between-group difference in change over time [95% CI]: 0.11% in 4 years [0.00 to 0.22], P = 0.047).CONCLUSIONSThe greater increase in lateral ventricular volume over time in patients with type 2 diabetes compared with control participants shows that type 2 diabetes is associated with a slow increase of cerebral atrophy over the course of years.

Accuracy and reproducibility study of automatic MRI brain tissue segmentation methods

The ability to study changes in brain morphometry in longitudinal studies majorly depends on the accuracy and reproducibility of the brain tissue quantification. We evaluate the accuracy and reproducibility of four previously proposed automatic brain tissue segmentation methods: FAST, SPM5, an automatically trained k-nearest neighbor (kNN) classifier, and a conventional kNN classifier based on a prior training set. The intensity nonuniformity correction and skull-stripping mask were the same for all methods. Evaluations were performed on MRI scans of elderly subjects derived from the general population. Accuracy was evaluated by comparison to two manual segmentations of MRI scans of six subjects (mean age 65.9±4.4years). Reproducibility was assessed by comparing the automatic segmentations of 30 subjects (mean age 57.0±3.7years) who were scanned twice within a short time interval. All methods showed good accuracy and reproducibility, with only small differences between methods. The conventional kNN classifier was the most accurate method with similarity indices of 0.82/0.90/0.94 for cerebrospinal fluid/gray matter/white matter, but it showed the lowest reproducibility. FAST yielded the most reproducible segmentation volumes with volume difference standard deviations of 0.55/0.49/0.38 (percentage of intracranial volume) respectively. The results of the reproducibility experiment can be used to calculate the required number of subjects in the design of a longitudinal study with sufficient power to detect changes over time in brain (tissue) volume. Example sample size calculations demonstrate a rather large effect of the choice of segmentation method on the required number of subjects.

Magnetic Resonance Imaging White Matter Hyperintensities and Brain Volume in the Prediction of Mild Cognitive Impairment and Dementia

To determine whether magnetic resonance imaging (MRI) white matter hyperintensities (WMH), whole-brain atrophy, and cardiovascular risk factors predict the development of cognitive decline and dementia. Subjects were recruited into this prospective cohort study and followed for incident cognitive decline for mean (SD) 6.0 (4.1) years. Magnetic resonance imaging dual-echo sequences, obtained at baseline, were used to determine the volume of WMH and the brain parenchymal fraction (BPF), the proportion of the intracranial cavity occupied by brain. White matter hyperintensity volume was analyzed as the percentage of intracranial volume (WMHr); "high WMH" was defined as a WMHr more than 1 SD above the mean. General community. Volunteer sample consisting of 67 subjects with normal cognition and 156 subjects with mild cognitive impairment (MCI). Time to diagnosis of MCI (among those with normal cognition at baseline) or time to diagnosis of dementia, either all-cause or probable Alzheimer disease (AD) (among those with MCI at baseline). Cox proportional hazards models were used for multivariable analysis. High WMH was a predictor of progression from normal to MCI (adjusted hazard ratio [HR], 3.30; 95% confidence interval [CI], 1.33-8.17; P= .01) but not conversion from MCI to all-cause dementia. Conversely, BPF did not predict progression from normal to MCI but did predict conversion to dementia (adjusted HR, 1.10 for each 1% decrease in BPF; 95% CI, 1.02-1.19; P= .02). When conversion to AD dementia was considered as the outcome, BPF was likewise a predictor (adjusted HR, 1.16 for each 1% decrease in BPF; 95% CI, 1.08-1.24; P< .001), but high WMH was not. Past tobacco smoking was associated with both progression from normal to MCI (adjusted HR, 2.71; 95% CI, 1.12-6.55; P= .03) and conversion to all-cause dementia (adjusted HR, 2.08; 95% CI, 1.13-3.82; P= .02), but not AD dementia. These findings suggest that WMH are associated with the risk of progressing from normal to MCI. In persons whose cognitive abilities are already impaired, BPF predicts the conversion to dementia.

Brain tissue volumes in the general elderly population: The Rotterdam Scan Study

We investigated how volumes of cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) varied with age, sex, small vessel disease and cardiovascular risk factors in the Rotterdam Scan Study. Participants ( n = 490; 60–90 years) were non-demented and 51.0% had hypertension, 4.9% had diabetes mellitus, 17.8% were current smoker and 54.0% were former smoker. We segmented brain MR-images into GM, normal WM, white matter lesion (WML) and CSF. Brain infarcts were rated visually. Volumes were expressed as percentage of intra-cranial volume. With increasing age, volumes of total brain, normal WM and total WM decreased; that of GM remained unchanged; and that of WML increased, in both men and women. Excluding persons with infarcts did not alter these results. Persons with larger load of small vessel disease had smaller brain volume, especially normal WM volume. Diastolic blood pressure, diabetes mellitus and current smoking were also related to smaller brain volume. In the elderly, higher age, small vessel disease and cardiovascular risk factors are associated with smaller brain volume, especially WM volume.