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Abstract #3440

From microscopy data to hemodynamic simulations: a vascular graph approach to understand the fMRI signal formation

Vanja Curcic1, Mario Gilberto Báez-Yáñez1, Prakash Kara2, Chao Liu2, Matthias J.P. van Osch3, and Natalia Petridou1
1UMC Utrecht, Utrecht, Netherlands, 2University of Minnesota, Minneapolis, MN, United States, 3LUMC, Leiden, Netherlands

Synopsis

Keywords: Task/Intervention Based fMRI, fMRI, modeling

Motivation: Understanding the impact of cortical vascular architecture on the spatiotemporal features of hemodynamic responses.

Goal(s): Automatic extraction of realistic cortical vasculature models from microscopy data, and simulation of hemodynamic changes across the extracted vascular network.

Approach: We present a pipeline that utilizes graph theory for extracting the vasculature from microscopy data, representing it as a vascular graph. Simulations were performed using the extracted vascular graphs by converting the connectivity matrix into a dynamic system modeled by RC circuits.

Results: We extracted two realistic vascular graphs and used them to mimic hemodynamic changes resulting from simulated arterial dilation.

Impact: Vascular graphs extracted by the developed pipeline could serve to simulate hemodynamic changes across the cortical vasculature. This provides a tool to enhance fMRI signal interpretation and provide valuable insights into the role of vascular dysfunction in cerebrovascular diseases.

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