论文标题
使用小鼠脑的逼真的毛细血管网络模拟内腔内不相干灌注信号
Simulation of Intravoxel Incoherent Perfusion Signal Using a Realistic Capillary Network of a Mouse Brain
论文作者
论文摘要
目的:模拟从小鼠大脑的三个逼真的血管网络图中的血液颗粒运动中的运动中的运动型磁共振幅度信号。方法:在由两光子激光显微镜扫描的小鼠皮质产生的三个网络中,使用Poiseuille定律模拟了每个血管中的血流。在Stejskal-Tanner单极脉冲梯度方案中,通过固定数量的模拟血液颗粒获得的轨迹,流速和相位。通过整合所有相通过拟合指数信号衰减来估计所得的幅度信号作为B值的函数,并且伪扩散系数D*估计。为了更好地理解IVIM灌注信号的解剖来源,通过将模拟限制为各种类型的血管来重复上述。结果:三个微血管网络的特征分别是:血管长度[平均+/- std。 DEV。]:67.2 +/- 53.6 UM,59.8 +/- 46.2 UM和64.5 +/- 50.9 UM;直径:6.0 +/- 3.5 UM,网络2:5.7 +/- 3.6 um,网络3:6.1 +/- 3.7 um;模拟血液速度:0.9 +/- 1.7 UM/MS,1.4 +/- 2.5 UM/MS和0.7 +/- 2.1 UM/MS。模拟信号衰减随B值的函数的指数拟合导致以下D* [10-3 mm2/s]:31.7、40.4和33.4。低B值的信号衰减是较大容器中最大的信号,但是较小的血管和毛细血管更占网络的总体积。结论:该模拟通过将IVIM MR灌注信号与微血管网络的超高分辨率测量和逼真的血流模拟联系起来,从而提高了对IVIM灌注估计方法的理论理解。
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.