Blog Viewer

Diffuse Correlation Spectroscopy: Same Particle, Different Wave

By Currents Editor posted 02-23-2021 12:06

  
By Kia Ghiassi, Department of Neurology, Missouri University, Columbia Missouri;  Jesyree Veitia, Universidad Central de Venezuela, Caracas, Venezuela; and Francisco Gomez, Department of Neurology, Missouri University, Columbia Missouri

Adequate cerebral blood flow (CBF) is a key component in ensuring optimal oxygen delivery to brain parenchyma, considered a biomarker of tisular health and function with clinical utility. CBF when combined with MAP allows for inference of cerebral autoregulation, as a measure recommended by the NCS and European Society of Intensive Care medicine. 

An ideal monitoring tool would be able to accurately detect local CBF changes in real time and monitor over long periods of time, as well as to provide ease of use while being non-invasive. 

Readers will be familiar with light spectroscopy, commonly utilized in pulse oximeters. As the light absorbency of hemoglobin and deoxyhemoglobin at specific wavelengths is known, the contained oxygen is inferable. Near InfraRed Spectroscopy (NIRS) was developed to take advantage of these properties, yielding several applications such as measurement of brain oxygenation and relative cerebral oxygen extraction. However, NIRS technology has met several hurdles such as limited validity of rSO2, contamination by ambient light or extra cerebral tissues and limited depth of penetrance.  

Diffuse correlation spectroscopy

Diffuse correlation spectroscopy (DCS) utilized an entirely different assay method to that of NIRS, to determine relative blood flow as opposed to measuring tissue absorbency to a known wavelength, diffuse correlation spectroscopy (DCS) evaluates light scattering. As light penetrates cerebral tissue, it exhibits variabilities in scattering by motile erythrocytes. This scattering is derived into flow, yielding information about CBF.   



DCS system uses a coherent waveform laser delivered through tissue via an optical fiber. Photon samples are gathered again via optic fiber. Detectors compose count photons, and the temporal intensity autocorrelation function is derived as discussed above. 

Besides providing information about tissue blood flow, oxygenation and metabolism can be calculated through hybrid NIRS-DCS systems. Newer devices are more portable and more easily used at the bedside. Additionally, varieties of probe types are also available depending on the depth and type of tissue. DCS carries several advantages over NIRS. It can allow for better penetration up to 1.5 cm while allowing for higher temporal resolution, and potentially improved signal to noise ratio. While some modalities of NIRS allow for a flow derivation, these modalities are also limited.

Applications 

DCS has been in use for some time in neonates with congenital heart defects or preterm birth via the BabyLux device. More recently, Neurocritical Care Units have started to employ DCS. Cerebral blood flow measurements obtained via DCS were validated against Xenon-CT in an adult population with either subarachnoid hemorrhage, traumatic brain injury, or ischemic stroke.  Additionally, DCS has been used to monitor blood flow in brain tissue and tumors to the extent of monitoring CBF before and after therapies for stroke and traumatic brain injury. In these studies, DCS was found to have appropriate correlation with computer simulation.

Device

The Neuro-Monitor FloMo by Hemophotonics is a new device employing the above phenomena and is now commercially available. A fiber optic sensor is placed on the patient’s forehead whereby the laser is applied and samples are detected via a sensor placed at a set distance.  Its light wavelength is 785 nm (IR is 700nm). Single channel’s blood flow and the average are displayed on the interface in real time. It can be used with NIRS-diffuse optical spectroscopy (DOS) thus deriving CBF and O2 content.

Future Directions

The combination of NIRS and Diffuse Correlation Spectroscopy, offers a new noninvasive alternative in multimodality monitoring. A combined approach permits bedside real-time monitoring of CBF, oxygen extraction fraction and cerebral metabolic rate as well as derivation of neurovascular reactivity. There are currently very preliminary studies regarding DCS in the measurement of ICP that noninvasively measure of microvascular CBF permit continuous quantitative, bedside estimation of

DCS and NIRS are low cost and portable tools requiring no surgery, which can be used as a bedside monitor for several parameters .The potential of DCS and NIRS combined based on Cerebral Metabolic Rate of Oxygen extraction should be explored as an alternative of cerebral parameters such SO2. DCS can be used also for therapies at altering Cerebral Microvascular Perfusion. Additionally, monitor Cerebral Blood Flow with DCS and CMRO, SO2, AND CBF will help us understand the nature of Neurovascular response.

References and Links

  1. Yu, G. (2012). Diffuse Correlation Spectroscopy (DCS): A Diagnostic Tool for Assessing Tissue Blood Flow in Vascular-Related Diseases and Therapies. Current Medical Imaging Reviews, 8(3), 194–210. doi:10.2174/157340512803759875
  2. Durduran, Turgut, and Arjun G. Yodh. "Diffuse correlation spectroscopy for non-invasive, micro-vascular cerebral blood flow measurement." Neuroimage 85 (2014): 51-63.
  3. Kim MN, Durduran T, Frangos S, 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 Apr;12(2):173-180. DOI: 10.1007/s12028-009-9305-x.
  4. Ssali T, Anazodo UC, Thiessen JD, Prato FS, St Lawrence K. A Noninvasive Method for Quantifying Cerebral Blood Flow by Hybrid PET/MRI. J Nucl Med. 2018 Aug;59(8):1329-1334. doi: 10.2967/jnumed.117.203414. Epub 2018 Mar 9. PMID: 29523628.
  5. Durduran T, Choe R, Baker WB, Yodh AG. Diffuse Optics for Tissue Monitoring and Tomography. Rep Prog Phys. 2010;73(7):076701. doi:10.1088/0034-4885/73/7/076701
  6. Pham T, Tgavalekos K, Sassaroli A, Blaney G, Fantini S. Quantitative measurements of cerebral blood flow with near-infrared spectroscopy. Biomed Opt Express. 2019;10(4):2117-2134. Published 2019 Mar 28. doi:10.1364/BOE.10.002117
  7. Polinder-Bos HA, Elting JWJ, Aries MJ, García DV, Willemsen AT, van Laar PJ, Kuipers J, Krijnen WP, Slart RH, Luurtsema G, Westerhuis R, Gansevoort RT, Gaillard CA, Franssen CF. Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - A simultaneous near-infrared spectroscopy and positron emission tomography study. J Cereb Blood Flow Metab. 2020 Feb;40(2):328-340. doi: 10.1177/0271678X18818652. Epub 2018 Dec 12. PMID: 30540219; PMCID: PMC7370620.
  8. Campagnola P, Cote D, Pavone F, Reece P, Srinivasan VJ, Tkaczyk T, Volpe G. Biophotonics feature: introduction. Biomed Opt Express. 2018 Feb 20;9(3):1229-1231. doi: 10.1364/BOE.9.001229. PMID: 29541515; PMCID: PMC5846525.
  9. Leopold AV, Shcherbakova DM, Verkhusha VV. Fluorescent Biosensors for Neurotransmission and Neuromodulation: Engineering and Applications. Front Cell Neurosci. 2019 Oct 23;13:474. doi: 10.3389/fncel.2019.00474. PMID: 31708747; PMCID: PMC6819510.
  10. Shen, Xun, and Roel van Wijk, eds. Biophotonics: Optical Science and Engineering for the 21st Century. Springer Science & Business Media, 2006.
  11. P. Zirak, R. {Delgado-Mederos}, L. Dinia, D. Carrera, J. {Martí–Fàbregas}, and T. Durduran, “Transcranial, diffuse optical monitoring of micro-vascular cerebral hemodynamics after thrombolysis in ischemic stroke,” J. biomed. opt., vol. 19, iss. 1, p. 18002, 2014.
  12. C. H. Favilla, R. C. Mesquita, M. Mullen, T. Durduran, X. Lu, M. N. Kim, D. L. Minkoff, S. E. Kasner, J. H. Greenberg, A. G. Yodh, and J. A. Detre, “Optical bedside monitoring of cerebral blood flow in acute ischemic stroke patients during head of bed manipulation,” Stroke, vol. advance online, 2014.
  13. M. N. Kim, B. L. Edlow, T. Durduran, S. Frangos, R. C. Mesquita, J. M. Levine, J. H. Greenberg, A. G. Yodh, and J. A. Detre, “Continuous optical monitoring of cerebral hemodynamics during head-of-bed manipulation in brain-injured adults,” Neurocrit. care, vol. accepted in press, 2013.
  14. E. M. Buckley, D. Hance, T. Pawlowski, J. Lynch, F. B. Wilson, R. C. Mesquita, T. Durduran, L. K. Diaz, M. E. Putt, D. J. Licht, M. A. Fogel, and A. G. Yodh, “Validation of diffuse correlation spectroscopic measurement of cerebral blood flow using phase-encoded velocity mapping MRI,” Journal of biomedical optics, vol. 17, iss. 3, pp. 37007-1, 2012.
  15. Liu J, Li Y, Yu Y, Yuan X, Lv H, Liu L, Zhao Y, Wang Y, Ma Z. Simultaneous detection of cerebral blood perfusion and cerebral edema using swept-source optical coherence tomography. J Biophotonics. 2020 Feb;13(2):e201960087. doi: 10.1002/jbio.201960087. Epub 2019 Nov 24. PMID: 31702865.
  16. Busch, D.R., Balu, R., Baker, W.B. et al. Detection of Brain Hypoxia Based on Noninvasive Optical Monitoring of Cerebral Blood now with Diffuse Correlation Spectroscopy.Neurocrit Care 30, 72–80 (2019).lhttps://doi.org/10.1007/s12028-018-0573-1
  17. V. C. Kavuri, W. Baker, A. Parthasarthy, R. Balu, A. Yodh, and W. A. Kofke, "A Combined Diffuse Correlation and Time-Resolved Spectroscopy Instrument for Continuous monitoring of Absolute Cerebral Blood Flow," in Biomedical Optics 2016, OSA Technical Digest (online) (Optical Society of America, 2016), paper JW3A.8.
  18. Sergio Fantini, Angelo Sassaroli, Kristen T. Tgavalekos, Joshua Kornbluth, "Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods," Neurophoton. 3(3) 031411 (21 June 2016)https://doi.org/10.1117/1.NPh.3.3.031411.
  19. Yang Muyue, Yang Zhen, Yuan Tifei, Feng Wuwei, Wang Pu. “A Systemic Review of Functional Near-Infrared Spectroscopy for Stroke: Current Application and Future Directions” ;Frontiers in Neurology.vol 10; 2019. Pp: 58.  https://doi.org/10.3389/fneur.2019.00058   
  20. McNett, M.M., Horowitz, D.A. & The Participants in the International Multidisciplinary Consensus Conference on Multimodality Monitoring. International Multidisciplinary Consensus Conference on Multimodality Monitoring: ICU Processes of Care. Neurocrit Care 21, 215–228 (2014). https://doi.org/10.1007/s12028-014-0020-x
  21. From: Yu, G. (2012). Diffuse Correlation Spectroscopy (DCS): A Diagnostic Tool for Assessing Tissue Blood Flow in Vascular-Related Diseases and Therapies. Current Medical Imaging Reviews, 8(3), 194–210. doi:10.2174/157340512803759875

#LeadingInsights
FURTHER READING
By Shweta Goswami, MD; Eunice J Lee, MD; Rachael Scott, PharmD, BCCCP; Naomi Niznick, MD; Sasha Yakhkind, MD; Pouya Ameli, MD, MS; and Marc Babi, MD The role of practice management education—an umbrella term to describe salary negotiation, billing and coding, law and malpractice, and so on—has been ...
By: NCS Research Operations Subcommittee: Caitlin Brown PharmD, Michelle Schober MD, Shraddha Mainali MD, Cassia Righy MD, Minjee Kim MD, Tom Lawson CNP, Jennifer Kim MD, PhD, Ruchi Jha MD Can you tell me a little about yourself and how you got involved in the Neurocritical Care Society?   I ...
Yasser B. Abulhasan, MBChB, FRCPC, FNCS, Chairman, Neurocritical Care-MENA Chapter of IPACCMS It was a great pleasure organizing the 2 nd Neurocritical Care Regional Meeting in the Middle East and Africa in conjunction with the 17 th edition of the Emirates Critical Care Conference (ECCC). The meeting ...