Gregg Nicholas M, White Brian R, Zeff Benjamin W, Berger Andrew J, Culver Joseph P
Department of Radiology, Washington University in St. Louis, MO USA.
Front Neuroenergetics. 2010 Jul 14;2. doi: 10.3389/fnene.2010.00014. eCollection 2010.
Functional near infrared spectroscopy (fNIRS) is a portable monitor of cerebral hemodynamics with wide clinical potential. However, in fNIRS, the vascular signal from the brain is often obscured by vascular signals present in the scalp and skull. In this paper, we evaluate two methods for improving in vivo data from adult human subjects through the use of high-density diffuse optical tomography (DOT). First, we test whether we can extend superficial regression methods (which utilize the multiple source-detector pair separations) from sparse optode arrays to application with DOT imaging arrays. In order to accomplish this goal, we modify the method to remove physiological artifacts from deeper sampling channels using an average of shallow measurements. Second, DOT provides three-dimensional image reconstructions and should explicitly separate different tissue layers. We test whether DOT's depth-sectioning can completely remove superficial physiological artifacts. Herein, we assess improvements in signal quality and reproducibility due to these methods using a well-characterized visual paradigm and our high-density DOT system. Both approaches remove noise from the data, resulting in cleaner imaging and more consistent hemodynamic responses. Additionally, the two methods act synergistically, with greater improvements when the approaches are used together.
功能近红外光谱技术（fNIRS）是一种具有广泛临床应用潜力的便携式脑血流动力学监测设备。然而，在fNIRS中，来自大脑的血管信号常常被头皮和颅骨中的血管信号所掩盖。在本文中，我们评估了两种通过使用高密度漫射光学断层扫描（DOT）来改善成年人类受试者体内数据的方法。首先，我们测试是否能够将表面回归方法（利用多个源探测器对间距）从稀疏光极阵列扩展到DOT成像阵列的应用中。为了实现这一目标，我们修改了该方法，通过对浅层测量值进行平均来去除来自更深采样通道的生理伪影。其次，DOT提供三维图像重建，并且应该能够明确区分不同的组织层。我们测试DOT的深度切片是否能够完全去除表面生理伪影。在此，我们使用一种特征明确的视觉范式和我们的高密度DOT系统评估这些方法在信号质量和可重复性方面的改善情况。两种方法都能去除数据中的噪声，从而实现更清晰的成像和更一致的血流动力学反应。此外，这两种方法具有协同作用，当它们一起使用时改善效果更佳。
