Key result
Physiologic supply-demand model estimates cerebrovascular flow more robustly against segmentation uncertainties than Murray's law.
Why the study?
Current boundary conditions for cerebrovascular image-based modeling rely on in-vivo measurements or geometry-based models, which are constrained by image resolution or high sensitivity to segmented geometry.
Does a physiologic model based on supply and demand accurately estimate cerebrovascular blood flow and perfusion territory compared to Murray's law and literature data?
Observational (n=42)
Yes
Does a physiologic model based on supply and demand accurately estimate cerebrovascular blood flow and perfusion territory compared to Murray's law and literature data?
The proposed physiologic model based on supply and demand accurately estimates cerebrovascular blood flow and perfusion territories, offering a robust alternative to Murray's law for image-based modeling.
May improve boundary conditions for cerebrovascular image-based modeling; leaves open prospective in-vivo validation before clinical use.
Image-based modeling heavily relies on boundary conditions to obtain realistic blood flow and pressure. For the cerebrovascular system, boundary conditions are derived using in-vivo measurements or geometry-based models such as Murray's law, but these are constrained by the image resolution or high sensitivity to the segmented geometry. We propose a physiologic model of the cerebrovascular system based on a supply and demand relationship between arteries and tissues. Blood flow and perfusion territory are determined by associating brain tissues with nearby vessels using Voronoi tessellation. The model was evaluated for 40 healthy young individuals and two diseased patients, and was validated by comparing the estimated blood flows and perfusion territories against literature data and perfusion imaging. The estimated blood flows are within the physiologically reported values for major cerebral arteries and the predicted perfusion territories are similar to the literature and perfusion imaging. Further, the model demonstrates more robustness to segmentation uncertainties compared to Murray's law. The proposed model is shown to estimate physiologically plausible cerebrovascular blood flow and perfusion territory in a subject-specific manner using medical image data only. It may be used to simulate blood flow more realistically by developing boundary conditions based on this model in the cerebrovascular system.
No takes yet. Share an insight, caveat, or question.
Lee et al. (2025) conducted an observational in Healthy and cerebrovascular disease (n=42). Physiologic model based on supply and demand relationship vs. Murray's law and literature PC-MRI data was evaluated on Blood flow distribution and perfusion territories. A physiologic model based on a supply and demand relationship estimated cerebrovascular blood flows within physiologically reported values and demonstrated greater robustness to segmentation uncertainties compared to Murray's law.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: