Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 27 tok/s Pro
GPT-5 High 22 tok/s Pro
GPT-4o 84 tok/s Pro
Kimi K2 195 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Simulation of Intravoxel Incoherent Perfusion Signal Using a Realistic Capillary Network of a Mouse Brain (2012.14749v1)

Published 29 Dec 2020 in physics.med-ph, cs.NA, and math.NA

Abstract: Purpose: To simulate the intravoxel incoherent perfusion magnetic resonance magnitude signal from the motion of blood particles in three realistic vascular network graphs from a mouse brain. Methods: In three networks generated from the cortex of a mouse scanned by two-photon laser microscopy, blood flow in each vessel was simulated using Poiseuille law. The trajectories, flow speeds and phases acquired by a fixed number of simulated blood particles during a Stejskal-Tanner monopolar pulse gradient scheme were computed. The resulting magnitude signal as a function of b-value was obtained by integrating all phases and the pseudo-diffusion coefficient D* was estimated by fitting an exponential signal decay. To better understand the anatomical source of the IVIM perfusion signal, the above was repeated by restricting the simulation to various types of vessels. Results: The characteristics of the three microvascular networks were respectively: vessel lengths [mean +/- std. dev.]: 67.2 +/- 53.6 um, 59.8 +/- 46.2 um, and 64.5 +/- 50.9 um; diameters: 6.0 +/- 3.5 um, network 2: 5.7 +/- 3.6 um, and network 3: 6.1 +/- 3.7 um; simulated blood velocity: 0.9 +/- 1.7 um/ms, 1.4 +/- 2.5 um/ms and 0.7 +/- 2.1 um/ms. Exponential fitting of the simulated signal decay as a function of b-value resulted in the following D* [10-3 mm2/s]: 31.7, 40.4 and 33.4. The signal decay for low b-values was the largest in the larger vessels, but the smaller vessels and the capillaries accounted more to the total volume of the networks. Conclusion:This simulation improves the theoretical understanding of the IVIM perfusion estimation method by directly linking the MR IVIM perfusion signal to an ultra-high resolution measurement of the microvascular network and a realistic blood flow simulation.

Citations (7)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.