The brain health index: Towards a combined measure of neurovascular and neurodegenerative structural brain injury

Abstract

Background A structural magnetic resonance imaging measure of combined neurovascular and neurodegenerative burden may be useful as these features often coexist in older people, stroke and dementia. Aim We aimed to develop a new automated approach for quantifying visible brain injury from small vessel disease and brain atrophy in a single measure, the brain health index. Materials and methods We computed brain health index in N = 288 participants using voxel-based Gaussian mixture model cluster analysis of T1, T2, T2*, and FLAIR magnetic resonance imaging. We tested brain health index against a validated total small vessel disease visual score and white matter hyperintensity volumes in two patient groups (minor stroke, N = 157; lupus, N = 51) and against measures of brain atrophy in healthy participants (N = 80) using multiple regression. We evaluated associations with Addenbrooke's Cognitive Exam Revised in patients and with reaction time in healthy participants. Results The brain health index (standard beta = 0.20-0.59, P < 0.05) was significantly and more strongly associated with Addenbrooke's Cognitive Exam Revised, including at one year follow-up, than white matter hyperintensity volume (standard beta = 0.04-0.08, P > 0.05) and small vessel disease score (standard beta = 0.02-0.27, P > 0.05) alone in both patient groups. Further, the brain health index (standard beta = 0.57-0.59, P < 0.05) was more strongly associated with reaction time than measures of brain atrophy alone (standard beta = 0.04-0.13, P > 0.05) in healthy participants. Conclusions The brain health index is a new image analysis approach that may usefully capture combined visible brain damage in large-scale studies of ageing, neurovascular and neurodegenerative disease.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

“…There is consensus that cavities resulting from infarction should be excluded from brain tissue estimates [5] , depending on the question being asked; clearly, they do not represent spaces such as subarachnoid space or ventricles, nor do they represent normal brain tissue. They can be considered as part of the “total burden of brain injury” [39] in some analyses. Quantitative methods that can estimate perivascular space volume are emerging; when such measurements are made, we recommend that perivascular space volume be reported as a separate tissue class and not included in the total brain volume.…”

Cortical thickness, white matter hyperintensities, and cognition after stroke

“…Brain atrophy and white matter hyperintensities (WMH) are common in people with ischemic stroke and both are independently associated with worse outcome. [1][2][3] Methods for measuring brain atrophy from magnetic resonance imaging (MRI) include assessment of grey and white matter volumes, cerebrospinal fluid volume, and more recently, cortical thickness. 4,5 Cortical thickness is the distance between grey and white matter surfaces and measurement allows for voxel-or vertex-wise analyses across the cortex, potentially increasing sensitivity to detect associations with cognitive impairment.…”

Automated quantification of small vessel disease brain changes on MRI predicts cognitive and functional decline

“…Recently, an automated global measure of whole brain atrophy and vascular disease has been proposed and shown to have a stronger relationship with cognition as compared to WMH volume alone and visual total SVD score. 25 Another study has also reported that a combination of SVD features contributed more to cognitive performance after stroke than the individual measures. 26 These studies have been limited by relatively small sample sizes and brief cognitive measures.…”