Dehghani Hamid, White Brian R, Zeff Benjamin W, Tizzard Andrew, Culver Joseph P
School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
Appl Opt. 2009 Apr 1;48(10):D137-43. doi: 10.1364/ao.48.00d137.
The development of diffuse optical tomography (DOT) instrumentation for neuroimaging of humans is challenging due to the large size and the geometry of the head and the desire to distinguish signals at different depths. One approach to this problem is to use dense imaging arrays that incorporate measurements at different source-detector distances. We previously developed a high-density DOT system that is able to obtain retinotopic measurements in agreement with functional magnetic resonance imaging and positron emission tomography. Further extension of high-density DOT neuroimaging necessitates a thorough study of the measurement and imaging sensitivity that incorporates the complex geometry of the head--including the head curvature and layered tissue structure. We present numerical simulations using a finite element model of the adult head to study the sensitivity of the measured signal as a function of the imaging array and data sampling strategy. Specifically, we quantify the imaging sensitivity available within the brain (including depths beyond superficial cortical gyri) as a function of increasing the maximum source-detector separation included in the data. Through the use of depth related sensitivity analysis, it is shown that for a rectangular grid [with 1.3 cm first nearest neighbor (NN) spacing], second NN measurements are sufficient to record absorption changes along the surface of the brain's cortical gyri (brain tissue depth <5 mm). The use of fourth and fifth NN measurements would permit imaging down into the cortical sulci (brain tissue depth >15 mm).
由于头部的尺寸较大和形状以及区分不同深度信号的需求,用于人类神经成像的扩散光学断层扫描(DOT)仪器的开发具有挑战性。解决这个问题的一种方法是使用密集成像阵列,该阵列结合了不同源 - 探测器距离处的测量。我们之前开发了一种高密度DOT系统,该系统能够获得与功能磁共振成像和正电子发射断层扫描一致的视网膜拓扑测量结果。高密度DOT神经成像的进一步扩展需要对测量和成像灵敏度进行深入研究,该研究要考虑头部的复杂几何形状,包括头部曲率和分层组织结构。我们使用成人头部的有限元模型进行数值模拟,以研究测量信号的灵敏度作为成像阵列和数据采样策略的函数。具体而言,我们量化了大脑内部(包括超出浅表皮质脑回的深度)的成像灵敏度,作为增加数据中包含的最大源 - 探测器间距的函数。通过使用与深度相关的灵敏度分析,结果表明,对于具有1.3厘米第一最近邻(NN)间距的矩形网格,第二NN测量足以记录沿大脑皮质脑回表面(脑组织深度<5毫米)的吸收变化。使用第四和第五NN测量将允许成像深入到皮质沟(脑组织深度>15毫米)。