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Bio-ingénierie

使用光学漫反射相关光谱，基于脑血流的休息状态功能连接

Published: May 27, 2020
doi:
10.3791/60765
, , ,
1Department of Biomedical, Industrial and Human Factors Engineering,Wright State University, 2South China Academy of Advanced Optoelectronics,South China Normal University

Summary

该协议演示如何使用定制的漫反射相关光谱仪测量人类前额叶皮层的静止状态功能连接。报告还讨论了实验的实际方面以及分析数据的详细步骤。

Abstract

为了全面了解人脑，需要利用脑血流（CBF）作为造影源，因为它是与脑氧供应相关的一个关键血液动力学参数。基于氧合对比度的静息状态低频波动已被证明提供功能连接区域之间的相关性。提交的协议使用光学扩散相关光谱（DCS）来评估人脑中基于血流的静息状态功能连通性（RSFC）。基于CBF的RSFC在人前额叶皮层的结果表明，与两种皮质的区域间RSFC相比，区域内RSFC在左右皮质中明显更高。这种协议应该引起研究人员的兴趣，他们使用多模式成像技术来研究人脑功能，特别是在儿科人群中。

Introduction

当大脑处于静止状态时，它显示功能相关区域的自发活动高度同步，这些区域可以位于接近或距离附近。这些同步区域称为功能网络1,1、2、3、4、5、6、7、8、9。2,3,4,5,6,7,8,9这一现象首先通过功能磁共振成像（fMRI）研究发现，该研究使用血液含氧水平依赖（BOLD）的信号，指示脑血55，1010的氧合水平，也称为静息状态功能连接（RSFC）。RSFC的异常与脑疾病有关，如自闭症11、阿尔茨海默氏症12和抑郁症13。因此，RSFC 是研究难以执行基于任务的疾病患者的宝贵工具。然而，许多病人，如年轻的自闭症儿童，是fMRI评估的差劲候选人，因为它要求在14，15,15年，它要求在密闭的空间内长时间留在密闭的空间内。光学成像速度快，可穿戴;因此，它适用于大多数病人，特别是儿科人口16，17，18，19，20，21，22，23，24。16,17,18,19,20,21,22,23,24利用这些优势，功能性近红外光谱（fNIRS）可用于测量人类（包括儿科44、8、258,25和自闭症患者11）。该光谱可以量化大脑中的血红蛋白浓度和氧饱和度参数。

光漫反射相关光谱（DCS）是一种相对较新的光学技术，可以量化大脑血流，这是将氧气供应与代谢66、17、26、27、28、2917,26,27,28,29相关的重要参数。与氧合对比度30相比，DCS量化的光流对比度在大脑中具有更高的灵敏度。因此，利用DCS衍生的CBF参数来评估RSFC是有利的。

DCS对移动的血细胞很敏感。当扩散光子从移动的血细胞中散射时，这会导致检测到的光的强度随时间而波动。DCS 测量基于时间的强度自相关函数，其衰减率取决于光学参数和血流。这些值最终用于获取脑血流指数 （CBFi）。随着移动速度更快的血细胞，强度自相关功能衰变更快。因此，有关组织表面深处运动的信息可以从测量随时间,推导27、31、32、33、34、35。,31,32,3334,35DCS是一种与广为人知的fNIRS技术的补充，它测量血液氧合17，36。17,由于fNIRS和DCS都是光学脑成像技术，在毫秒范围内具有高时态分辨率，因此光学成像设置对运动伪影的敏感程度远不如fMRI。它们还成功地用于儿科人群的功能性脑成像，包括16岁的婴儿。以前，表面血流测量已经用于评估RSFC在临床前研究小鼠37。在这里，血流参数用于量化9个健康成年人的RSFC作为概念验证研究38，39。38,

在这项研究中，使用了商用FD-fNIRS系统和定制DCS系统（参见材料表）。内部制造的 DCS 由两个 785 nm、100 mW 长相干长度连续波激光器组成，这些激光器与 FC 连接器耦合，8 台单光子计数机 （SPCM） 连接到自动腐蚀器。还专门为该系统制作了一个自定义软件图形用户界面 （GUI），以实时显示和保存每个 SPCM 通道的光子计数、自相关曲线和半定量血流。39该系统的零件通常用于DCS 16、17、31、32、40、42、43、44，所得结果也经过内部验证，并在最近的一项研究中使用。16,17,31,32,40,42,43,44

Protocol

该议定书得到赖特州立大学机构审查委员会的批准，在实验前，每个参与者都征得了知情同意。 1. 主题准备 在开始对主体进行任何测量之前，请为 FD-fNIRS 和 DCS 系统预热至少 10 分钟（有关详细信息，请参阅第 2 节和第 3 节）。图1显示了使用紧凑型DCS仪器进行主体测量的示例。 首先，使用磁带测量测量每个受试者头部的切口到内因之间?…

Representative Results

使用DCS测量功能连接的可行性被成功消除39。测量了九个受试者前额皮质的休息状态功能连接。结果显示，左侧区域区域（0.64 ± 0.25）和右侧 （0.62 = 0.23） 皮质的相关性较高， 与左侧区域间区域（0.32 = 0.32）、（0.34 ± 0.27）和右侧（0.34 ± 0.29）、（0.34 ± 0.26）皮质相比。（图5）。还进行了功率为0.8和显著性水平为0.05的功率分析，结果功率为0.82，样本大小?…

Discussion

为了确定由DCS测量的CBF是否准确检测到RSFC，检查了大脑中具有已知RSFC特性的两个区域。DLFC 区域之间以及 DLFC 和 IFC 之间的功能连接假定存在57、58,58、59。,选择左和右两个站点之间的连接，因为区域内连接通常较高。此外，IFC和DLFC之间的连接被选择，因为区域间连接已知较弱。

DCS 技术显示 DLFC 区域内的?…

Divulgations

The authors have nothing to disclose.

Acknowledgements

作者感谢俄亥俄州第三前沿对俄亥俄成像研究和创新网络（OIRAIN，667750）和中国国家自然科学基金（第81771876号）的财政支持。

Materials

3D Printed Probe In-house N/A 3D printed PLA probe (Craftbot, Craft unique)
785nm, 100mW, CW, FC coupled Laser CrystaLaser DL785-100-S DCS component (light source)
Auto-correlator Correlator.com Flex05-8ch DCS component (output g2 curve to PC)
Data Acquisition GUI In-house N/A GUI coded in LabVIEW to run the DCS system
Data analysis software In-house N/A Matlab code used for obtaining RSFC results
EEG Electrode Cap OpenBCI N/A EEG mesh cap with standard 10/20 positions
Multi-mode fiber OZ Optics QMMJ-3,2.5-IRVIS-600/630-3PCBK-3 DCS component (source fiber)
Oxiplex calibration phantom ISS 75019, 75020 Set of 2 PDMS Calibration Phantom
Oxiplex muscle probe ISS 86010 4 channel muscle probe
Oxiplex Oximeter ISS 95205 FD-fNIRS (690nm, 830nm)
Power meter Thorlabs PM100D Laser light power adjuster
Sensor card Thorlabs F-IRC1-S laser IR beam viewer
Single-mode fiber OZ Optics SMJ-3S2.5-780-5/125-3PCBK-3 DCS component (detector fiber)
Single-Photon Counting Machine Excelitas SPMC-NIR-1×2-FC DCS component (detector)
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References

  1. Cohen, A. L., et al. Defining functional areas in individual human brains using resting functional connectivity MRI. NeuroImage. 41 (1), 45-57 (2008).
  2. Pizoli, C. E., et al. Resting state activity in development and maintenance of normal brain function. Proceedings of the National Academy of Sciences of the United States of America. 108 (28), 11638-11643 (2011).
  3. Duan, L., Zhang, Y. J., Zhu, C. Z. Quantitative comparison of resting state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study. NeuroImage. 60 (4), 2008-2018 (2012).
  4. White, B. R., et al. Resting state functional connectivity in the human brain revealed with diffuse optical tomography. NeuroImage. 47 (1), 148-156 (2009).
  5. Biswal, B., Yetkin, F. Z., Haughton, V. M., Hyde, J. S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic resonance in medicine official journal of the Society of Magnetic Resonance in Medicine/Society of Magnetic Resonance in Medicine. 34 (4), 537-541 (1995).
  6. Mesquita, R. C., et al. Direct measurement of tissue blood flow and metabolism with diffuse optics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering. , (2011).
  7. Zhang, H., et al. Test-retest assessment of independent component analysis-derived resting state functional connectivity based on functional near-infrared spectroscopy. NeuroImage. 55 (2), 607-615 (2011).
  8. Lu, C. M., et al. Use of fNIRS to assess resting state functional connectivity. Journal of Neuroscience Methods. 186 (2), 242-249 (2010).
  9. Zhang, Y. -. J., et al. Detecting Resting state Functional Connectivity in the Language System using Functional Near-Infrared Spectroscopy. Journal of Biomedical Optics. 15 (4), 047003 (2010).
  10. Fransson, P. Spontaneous low-frequency BOLD signal fluctuations: An fMRI investigation of the resting state default mode of brain function hypothesis. Human Brain Mapping. , (2005).
  11. Li, J., et al. Characterization of autism spectrum disorder with spontaneous hemodynamic activity. Biomedical Optics Express. , (2016).
  12. Sheline, Y. I., Raichle, M. E. Resting state functional connectivity in preclinical Alzheimer’s disease. Biological Psychiatry. , (2013).
  13. Mulders, P. C., van Eijndhoven, P. F., Schene, A. H., Beckmann, C. F., Tendolkar, I. Resting state functional connectivity in major depressive disorder: A review. Neuroscience and Biobehavioral Reviews. , (2015).
  14. Kiviniemi, V., et al. Slow vasomotor fluctuation in fMRI of anesthetized child brain. Magnetic Resonance in Medicine. , (2000).
  15. Fransson, P., et al. Resting state networks in the infant brain. Proceedings of the National Academy of Sciences of the United States of America. , (2007).
  16. Durduran, T., Yodh, A. G. Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement. Neuroimage. 85, 51-63 (2014).
  17. Buckley, E. M., Parthasarathy, A. B., Grant, P. E., Yodh, A. G., Franceschini, M. A. Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects. Neurophotonics. 1 (1), 011009 (2014).
  18. Buckley, E. M., et al. Cerebral hemodynamics in preterm infants during positional intervention measured with diffuse correlation spectroscopy and transcranial Doppler ultrasound. Optics Express. , (2009).
  19. Dehaes, M., et al. Cerebral oxygen metabolism in neonatal hypoxic ischemic encephalopathy during and after therapeutic hypothermia. Journal of Cerebral Blood Flow. , (2014).
  20. Lin, P. Y., et al. Non-invasive optical measurement of cerebral metabolism and hemodynamics in infants. Journal of Visualized Experiments. , (2013).
  21. Lin, P. Y., et al. Regional and hemispheric asymmetries of cerebral hemodynamic and oxygen metabolism in newborns. Cerebral Cortex. 23 (2), (2013).
  22. Busch, D. R., et al. Cerebral Blood Flow Response to Hypercapnia in Children with Obstructive Sleep Apnea Syndrome. Sleep. , (2016).
  23. Durduran, T., et al. Cerebral oxygen metabolism (CMRO2) reactivity to hypercapnia in neonates with severe congenital heart defects measured with diffuse optics. Journal of Cerebral Blood Flow and Metabolism. , (2009).
  24. Durduran, T., et al. Optical measurement of cerebral hemodynamics and oxygen metabolism in neonates with congenital heart defects. Journal of Biomedical Optics. , (2010).
  25. Mesquita, R. C., Franceschini, M. A., Boas, D. A. Resting state functional connectivity of the whole head with near-infrared spectroscopy. Biomedical optics express. 1 (1), 324-336 (2010).
  26. Boas, D. A., Franceschini, M. A. Haemoglobin oxygen saturation as a biomarker: The problem and a solution. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering. , (2011).
  27. Durduran, T., Yodh, A. G. Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement. NeuroImage. , (2014).
  28. Yu, G. Diffuse Correlation Spectroscopy (DCS): A Diagnostic Tool for Assessing Tissue Blood Flow in Vascular-Related Diseases and Therapies. Current Medical Imaging Reviews. (8), 194-210 (2012).
  29. Yu, G., Durduran, T., Zhou, C., Cheng, R., Yodh, A. G. Near-Infrared Diffuse Correlation Spectroscopy for Assessment of Tissue Blood Flow. Handbook of Biomedical Optics. , 195-216 (2011).
  30. Selb, J., et al. Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia. Neurophotonics. 1 (1), (2014).
  31. Cheung, C., et al. In vivo cerebrovascular measurement combining diffuse near-infrared absorption and correlation spectroscopies. Physics in Medicine and Biology. 46 (8), 2053-2065 (2001).
  32. Mesquita, R. C., et al. Direct measurement of tissue blood flow and metabolism with diffuse optics. Philos Trans A Math Phys Eng Sci. 369 (1955), 4390-4406 (2011).
  33. Maret, G., Wolf, P. E. Multiple Light Scattering from Disordered Media. The Effect of Brownian Motion of Scatterers. Z. Phys. B – Condensed Matter. 65, 409-413 (1987).
  34. Yu, G. Q. Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring. Journal of Biomedical Optics. 17 (1), (2012).
  35. Carp, S. A., Dai, G. P., Boas, D. A., Franceschini, M. A., Kim, Y. R. Validation of diffuse correlation spectroscopy measurements of rodent cerebral blood flow with simultaneous arterial spin labeling MRI; towards MRI-optical continuous cerebral metabolic monitoring. Biomedical Optics Express. 1 (2), 553-565 (2010).
  36. Roche-Labarbe, N., et al. Near-infrared spectroscopy assessment of cerebral oxygen metabolism in the developing premature brain. Journal of Cerebral Blood Flow. , (2012).
  37. Bergonzi, K. M., Bauer, A. Q., Wright, P. W., Culver, J. P. Mapping functional connectivity using cerebral blood flow in the mouse brain. J Cereb Blood Flow Metab. 35 (3), 367-370 (2015).
  38. Poon, C. S., Li, J., Kress, J., Rohrbach, D. J., Sunar, U. Resting state Functional Connectivity measured by Diffuse Correlation Spectroscopy. Optics InfoBase Conference Papers. , (2018).
  39. Li, J., Poon, C. -. S., Kress, J., Rohrbach, D. J., Sunar, U. Resting state functional connectivity measured by diffuse correlation spectroscopy. Journal of Biophotonics. 11 (2), (2018).
  40. Yu, G. Q. Near-infrared diffuse correlation spectroscopy in cancer diagnosis and therapy monitoring. J Biomed Opt. 17 (1), (2012).
  41. Li, J., et al. Measurements of human motor and visual activities with diffusing-wave spectroscopy. Novel Optical Instrumentation for Biomedical Applications II. 5864, 58640 (2005).
  42. Wang, D., et al. Fast blood flow monitoring in deep tissues with real-time software correlators. Biomedical Optics Express. 7 (3), 776 (2016).
  43. Boas, D. A., Yodh, A. G. Spatially varying dynamical properties of turbid media probed with diffusing temporal light correlation. Journal of the Optical Society of America a-Optics Image Science and Vision. 14 (1), 192-215 (1997).
  44. Diop, M., Lee, T. -. Y., St. Lawrence, K. Continuous monitoring of absolute cerebral blood flow by combining diffuse correlation spectroscopy and time-resolved near-infrared technology. Spie. 7896, 78960 (2011).
  45. Medical, I. . ISS Oxiplex Manual. , (2008).
  46. Fantini, S., et al. Quantitative optical monitoring of the hemoglobin concentration and saturation in the piglet brain. Biomedical Optical Spectroscopy and Diagnostics. , (2000).
  47. Hueber, D. M., et al. Non-invasive and quantitative near-infrared haemoglobin spectrometry in the piglet brain during hypoxic stress, using a frequency-domain multidistance instrument. Physics in Medicine and Biology. , (2001).
  48. Zhang, J., et al. Application of I&Q detection system in scouting the curative effect of neck squamous cell carcinoma. Optical Tomography and Spectroscopy of Tissue V. , (2003).
  49. Zhao, J., Ding, H. S., Hou, X. L., Le Zhou, C., Chance, B. In vivo determination of the optical properties of infant brain using frequency-domain near-infrared spectroscopy. Journal of Biomedical Optics. , (2005).
  50. Tu, T., Chen, Y., Zhang, J., Intes, X., Chance, B. Analysis on performance and optimization of frequency-domain near-infrared instruments. Journal of Biomedical Optics. , (2002).
  51. Choe, R., et al. Transabdominal near infrared oximetry of hypoxic stress in fetal sheep brain in utero. Proceedings of the National Academy of Sciences of the United States of America. , (2003).
  52. Sunar, U., et al. Noninvasive diffuse optical measurement of blood flow and blood oxygenation for monitoring radiation therapy in patients with head and neck tumors: a pilot study. Journal of Biomedical Optics. 11 (6), (2006).
  53. Sunar, U., et al. Hemodynamic responses to antivascular therapy and ionizing radiation assessed by diffuse optical spectroscopies. Optics Express. , (2007).
  54. Durduran, T., Choe, R., Baker, W. B., Yodh, A. G. Diffuse Optics for Tissue Monitoring and Tomography T. Rep Prog Phys. 73 (7), (2010).
  55. Boas, D. A., Campbell, L. E., Yodh, A. G. Scattering and imaging with diffusing temporal field correlations. Physical Review Letters. , (1995).
  56. Boas, D. A., Yodh, A. G. Spatially varying dynamical properties of turbid media probed with diffusing temporal light correlation. Journal of the Optical Society of America A. , (1997).
  57. Chuang, C. -. C., Sun, C. -. W. Gender-related effects of prefrontal cortex connectivity: a resting state functional optical tomography study. Biomedical Optics Express. 5 (8), 2503 (2014).
  58. Okamoto, M., et al. Multimodal assessment of cortical activation during apple peeling by NIRS and fMRI. NeuroImage. , (2004).
  59. Koessler, L., et al. Automated cortical projection of EEG sensors: Anatomical correlation via the international 10-10 system. NeuroImage. , (2009).
  60. Farzam, P., et al. Shedding light on the neonatal brain: Probing cerebral hemodynamics by diffuse optical spectroscopic methods. Scientific Reports. , (2017).
  61. Shang, Y., Li, T., Yu, G. Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging. Physiological Measurement. , (2017).
  62. Mesquita, R. C., et al. Direct measurement of tissue blood flow and metabolism with diffuse optics. Philos Trans A Math Phys Eng Sci. 369 (1955), 4390-4406 (2011).
  63. Durduran, T., et al. Diffuse optical measurement of blood flow, blood oxygenation, and metabolism in a human brain during sensorimotor cortex activation. Optics Letters. , (2004).
  64. Kim, M. N., et al. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocritical Care. , (2010).
  65. Irwin, D., et al. Influences of tissue absorption and scattering on diffuse correlation spectroscopy blood flow measurements. Biomedical Optics Express. , (2011).

Tags

Keywords: Cerebral Blood FlowResting State Functional ConnectivityOptical Diffuse Correlation SpectroscopyWearable Optical Probes3D-printed ProbeMulti-mode FibersSingle-mode Fibers785 Nanometer LaserSingle-photon Counting MachinesFD-fNIRS SystemCalibration Phantom
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Poon, C., Rinehart, B., Li, J., Sunar, U. Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy. J. Vis. Exp. (159), e60765, doi:10.3791/60765 (2020).
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