Simulation of intravoxel incoherent perfusion signal using a realistic capillary network of a mouse brain

• Published in: NMR in biomedicine 2021-07, Vol.34 (7), p.e4528-n/a
• Main Authors: Van, Valerie Phi, Schmid, Franca, Spinner, Georg, Kozerke, Sebastian, Federau, Christian
• Format: Article
• Language: English
• Subjects: Animals; Biological products; Blood flow; Blood vessels; Brain; Brain - blood supply; Capillaries; Capillaries - diagnostic imaging; Cerebrovascular Circulation - physiology; Computer Simulation; Decay; Diameters; Diffusion coefficient; Diffusion Magnetic Resonance Imaging; Flow simulation; Laser microscopy; Magnetic resonance; Male; Mice; Mice, Inbred C57BL; Microvasculature; Motion; Networks; Perfusion; Signal Processing, Computer-Assisted; Simulation
• ISSN: 0952-3480; 1099-1492
• DOI: 10.1002/nbm.4528

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's law. The trajectories, flow speeds and phases acquired by a fixed number of simulated blood particles during a Stejskal‐Tanner bipolar pulse gradient scheme were computed. The resulting magnitude signal 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 intravoxel incoherent motion (IVIM) perfusion signal, the above was repeated restricting the simulation to various types of vessel. Results The characteristics of the three microvascular networks were respectively vessel lengths (mean ± std. dev.) 67.2 ± 53.6 μm, 59.8 ± 46.2 μm and 64.5 ± 50.9 μm, diameters 6.0 ± 3.5 μm, 5.7 ± 3.6 μm and 6.1 ± 3.7 μm and simulated blood velocity 0.9 ± 1.7 μm/ms, 1.4 ± 2.5 μm/ms and 0.7 ± 2.1 μm/ms. Exponential fitting of the simulated signal decay as a function of b‐value resulted in the following D*‐values [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 for more of 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. We simulated the intravoxel incoherent perfusion magnetic resonance signal from the motion of blood particles in three realistic vascular network graphs, generated from the cortex of a mouse scanned using two‐photon laser microscopy. We found a simulated pseudo‐diffusion coefficient in good agreement with published in vivo measurements, and that all vessel types (artery, arterioles, capillaries, venules and veins) contribute to the IVIM signal. This improves our theoretical understanding of the IVIM perfusion method.