Copy the page URI to the clipboard
Keelan, Jonathan; Chung, Emma and Hague, James
(2019).
DOI: https://doi.org/10.1088/1361-6560/ab2479
Abstract
The cerebral arteries are difficult to reproduce from first principles, featuring interwoven territories, and intricate layers of grey and white matter with differing metabolic demand. The aim of this study was to identify the ideal configuration of arteries required to sustain an entire brain hemisphere based on minimisation of the energy required to supply the tissue. The 3D distribution of grey and white matter within a healthy human brain was first segmented from Magnetic Resonance Images. A novel simulated annealing algorithm was then applied to determine the optimal configuration of arteries required to supply brain tissue. The model is validated through comparison of this ideal, entirely optimised, brain vasculature with the known structure of real arteries. This establishes that the human cerebral vasculature is highly optimised; closely resembling the most energy efficient arrangement of vessels. In addition to local adherence to fluid dynamics optimisation principles, the optimised vasculature reproduces global brain perfusion territories with well defined boundaries between anterior, middle and posterior regions. This validated brain vascular model and algorithm can be used for patient-specific modelling of stroke and cerebral haemodynamics, identification of sub-optimal conditions associated with vascular disease, and optimising vascular structures for tissue engineering and artificial organ design.
Viewing alternatives
Download history
Metrics
Public Attention
Altmetrics from AltmetricNumber of Citations
Citations from DimensionsItem Actions
Export
About
- Item ORO ID
- 61821
- Item Type
- Journal Item
- ISSN
- 1361-6560
- Project Funding Details
-
Funded Project Name Project ID Funding Body DTA - Open University. DTA 2009-13. (n/a) EP/P505046/1 EPSRC (Engineering and Physical Sciences Research Council) Not Set EP/L025884/1 EPSRC - Keywords
- Cerebral vasculature; Computer simulation; Cardiovascular Systems; Mathematical Models; Optimisation; MRI
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Physical Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
-
Centre for Electronic Imaging (CEI)
Physics
Mathematical Biology - Copyright Holders
- © 2019 Institute of Physics and Engineering in Medicine
- Depositing User
- James Hague