Tang Yuqi, Yao Junjie
Department of Biomedical Engineering, Duke University, Durham, NC, USA.
Quant Imaging Med Surg. 2021 Mar;11(3):1046-1059. doi: 10.21037/qims-20-815.
Photoacoustic computed tomography (PACT) detects light-induced ultrasound (US) waves to reconstruct the optical absorption contrast of the biological tissues. Due to its relatively deep penetration (several centimeters in soft tissue), high spatial resolution, and inherent functional sensitivity, PACT has great potential for imaging mouse brains with endogenous and exogenous contrasts, which is of immense interest to the neuroscience community. However, conventional PACT either assumes homogenous optical fluence within the brain or uses a simplified attenuation model for optical fluence estimation. Both approaches underestimate the complexity of the fluence heterogeneity and can result in poor quantitative imaging accuracy.
To optimize the quantitative performance of PACT, we explore for the first time 3D Monte Carlo (MC) simulation to study the optical fluence distribution in a complete mouse brain model. We apply the MCX MC simulation package on a digital mouse (Digimouse) brain atlas that has complete anatomy information. To evaluate the impact of the brain vasculature on light delivery, we also incorporate the whole-brain vasculature in the Digimouse atlas. k-wave toolbox was used to investigate the effect of inhomogeneous illumination on the reconstructed images and chromophore concentration estimation.
The simulation results clearly show that the optical fluence in the mouse brain is heterogeneous at the global level and can decrease by a factor of five with increasing depth. Moreover, the strong absorption and scattering of the brain vasculature also induce the fluence disturbance at the local level.
Both global and local fluence heterogeneity contributes to the reduced quantitative accuracy of the reconstructed PACT images of mouse brain. Correcting the optical fluence distribution can improve the quantitative accuracy of PACT.
光声计算机断层扫描(PACT)通过检测光诱导的超声波来重建生物组织的光吸收对比度。由于其相对较深的穿透深度(在软组织中可达几厘米)、高空间分辨率和固有的功能敏感性,PACT在利用内源性和外源性对比度对小鼠大脑进行成像方面具有巨大潜力,这引起了神经科学界的极大兴趣。然而,传统的PACT要么假定大脑内的光通量均匀,要么使用简化的衰减模型来估计光通量。这两种方法都低估了光通量异质性的复杂性,可能导致定量成像精度较差。
为了优化PACT的定量性能,我们首次探索使用三维蒙特卡罗(MC)模拟来研究完整小鼠脑模型中的光通量分布。我们将MCX MC模拟软件包应用于具有完整解剖信息的数字小鼠(Digimouse)脑图谱。为了评估脑血管系统对光传输的影响,我们还将全脑脉管系统纳入Digimouse图谱中。使用k波工具箱研究不均匀照明对重建图像和发色团浓度估计的影响。
模拟结果清楚地表明,小鼠大脑中的光通量在整体水平上是不均匀的,并且随着深度增加可降低五倍。此外,脑血管系统的强吸收和散射也会在局部水平上引起光通量扰动。
整体和局部的光通量异质性都会导致小鼠脑重建PACT图像定量准确性的降低。校正光通量分布可以提高PACT的定量准确性。