Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Neuroimage. 2011 Jun 1;56(3):1362-71. doi: 10.1016/j.neuroimage.2011.03.001. Epub 2011 Mar 6.
Diffuse optical imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R(2) coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p<0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique.
漫射光学成像(DOI)允许恢复与诱发脑活动相关的血液动力学响应。该信号受到系统生理干扰的污染,这些干扰发生在头部的浅层以及脑组织中。测量的反向反射几何形状使得 DOI 信号强烈受到浅层系统干扰的污染。最近的一项发展是使用小源-探测器分离(1cm)光极的信号作为回归量。由于这些额外的测量主要对成人的浅层敏感,它们有助于去除较长分离测量(3cm)中存在的系统干扰。受这些发现的鼓舞,我们开发了一种动态估计程序,使用小光极分离去除全局干扰,并同时估计血液动力学响应。该算法通过恢复在从 6 名静息人类受试者采集的基线 DOI 数据上添加的模拟合成血液动力学响应来进行测试。通过恢复的和模拟的血液动力学响应之间的 Pearson R(2)系数和均方误差(MSE)来量化算法的性能。我们的动态估计器还与静态估计器和传统自适应滤波方法进行了比较。与传统自适应滤波器、静态估计器和标准 GLM 技术相比,我们的卡尔曼滤波动态估计器在 HbO 和 HbR 的恢复方面观察到显著改善(双侧配对 t 检验,p<0.05)。