Boas, D. A. & Yodh, A. G. Spatially varying dynamical properties of turbid media probed with diffusing temporal light correlation. J. Opt. Soc. Am. A 14, 192 (1997).
Google Scholar
Shang, Y., Li, T. & Yu, G. Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging. Physiol. Meas. 38, R1–R1 (2017).
Google Scholar
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, 11009 (2014).
Kaya, K. et al. Intraoperative cerebral hemodynamic monitoring during carotid endarterectomy via diffuse correlation spectroscopy and near-infrared spectroscopy. Brain Sci. 12, 1025 (2022).
Google Scholar
Zavriyev, A. I. et al. The role of diffuse correlation spectroscopy and frequency-domain near-infrared spectroscopy in monitoring cerebral hemodynamics during hypothermic circulatory arrests. JTCVS Tech. 7, 161–177 (2021).
Google Scholar
Shang, Y. et al. Cerebral monitoring during carotid endarterectomy using near-infrared diffuse optical spectroscopies and electroencephalogram. Phys. Med. Biol 56, 3015–3032 (2011).
Google Scholar
Rajaram, A. et al. Cerebral perfusion and metabolic neuromonitoring during cardiopulmonary bypass. In Optical Tomography and Spectroscopy of Tissue (Vol. 11639, pp. 39). (2021).
Busch, D. R. et al. Continuous cerebral hemodynamic measurement during deep hypothermic circulatory arrest. Biomed. Opt. Express 7, 3461 (2016).
Google Scholar
Selb, J. et al. Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients. Neurophotonics 5, 1 (2018).
Busch, D. R. et al. Detection of brain hypoxia based on noninvasive optical monitoring of cerebral blood flow with diffuse correlation spectroscopy. Neurocrit. Care 30, 72–80 (2019).
Google Scholar
Milej, D. et al. Characterizing dynamic cerebral vascular reactivity using a hybrid system combining time-resolved near-infrared and diffuse correlation spectroscopy. Biomed. Opt. Express 11, 4571–4585 (2020).
Google Scholar
Ruesch, A. et al. Estimating intracranial pressure using pulsatile cerebral blood flow measured with diffuse correlation spectroscopy. Biomed. Opt. Express 11, 1462 (2020).
Google Scholar
Flanders, T. M. et al. Optical detection of intracranial pressure and perfusion changes in neonates with hydrocephalus. J. Pediatr. 236, 54-61.e1 (2021).
Google Scholar
Tabassum, S. M. et al. Clinical translation of intracranial pressure sensing with diffuse correlation spectroscopy. J. Neurosurg. 1, 20 (2022).
Wu, K.-C. et al. Validation of diffuse correlation spectroscopy measures of critical closing pressure against transcranial Doppler ultrasound in stroke patients. J. Biomed. Opt. 26, 36008–36009 (2021).
Baker, W. B. et al. Noninvasive optical monitoring of critical closing pressure and arteriole compliance in human subjects. J. Cereb. Blood Flow Metab. 37, 2691–2705 (2017).
Google Scholar
Selb, J. et al. Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: Simulations and experimental findings during hypercapnia. Neurophotonics 1, 15005 (2014).
Beauchamp, M. S. et al. The developmental trajectory of brain-scalp distance from birth through childhood: Implications for functional neuroimaging. PLoS ONE 6, e24981–e24981 (2011).
Google Scholar
Davis, N. J. Variance in cortical depth across the brain surface: Implications for transcranial stimulation of the brain. Eur. J. Neurosci. (2020).
Google Scholar
Xu, J., Jahromi, A. K., Brake, J., Robinson, J. E. & Yang, C. Interferometric speckle visibility spectroscopy (ISVS) for human cerebral blood flow monitoring. APL Photonics 5, 126102 (2020).
Google Scholar
Zhou, W. et al. Functional interferometric diffusing wave spectroscopy of the human brain. Sci. Adv. 7, eabe0150–eabe0150 (2021).
Google Scholar
Zhou, W. et al. Multi-exposure interferometric diffusing wave spectroscopy. Opt. Lett. 46, 4498–4501 (2021).
Google Scholar
Robinson, M. B., Boas, D. A., Sakadzic, S., Franceschini, M. A. & Carp, S. A. Interferometric diffuse correlation spectroscopy improves measurements at long source–detector separation and low photon count rate. J. Biomed. Opt. 25, 97004 (2020).
Google Scholar
James, E., Powell, S. & Munro, P. Performance optimisation of a holographic Fourier domain diffuse correlation spectroscopy instrument. Biomed. Opt. Express 13, 3836 (2022).
Google Scholar
Samaei, S., Nowacka, K., Gerega, A., Pastuszak, Ż & Borycki, D. Continuous-wave parallel interferometric near-infrared spectroscopy (CW πNIRS) with a fast two-dimensional camera. Biomed. Opt. Express 13, 5753 (2022).
Google Scholar
Liu, W. et al. Fast and sensitive diffuse correlation spectroscopy with highly parallelized single photon detection. APL Photonics 6, 26106 (2021).
Sie, E. J. et al. High-sensitivity multispeckle diffuse correlation spectroscopy. Neurophotonics 7, 35010 (2020).
Google Scholar
Wayne, M. A. et al. Massively parallel, real-time multispeckle diffuse correlation spectroscopy using a 500 × 500 SPAD camera. Biomed. Opt. Express 14, 703 (2023).
Google Scholar
Ling, H., Gui, Z., Hao, H. & Shang, Y. Enhancement of diffuse correlation spectroscopy tissue blood flow measurement by acoustic radiation force. Biomed. Opt. Express 11, 301 (2020).
Google Scholar
Robinson, M. B. et al. Characterization of continuous wave ultrasound for acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS). Biomed. Opt. Express 11, 3071 (2020).
Google Scholar
Tsalach, A. et al. Depth selective acousto-optic flow measurement. Biomed. Opt. Express 6, 4871–4886 (2015).
Google Scholar
Sutin, J. et al. Time-domain diffuse correlation spectroscopy. Optica 3, 1006 (2016).
Google Scholar
Ozana, N. et al. Functional time domain diffuse correlation spectroscopy. Front. Neurosci. 16, 1123 (2022).
Zhao, M., Zhou, W., Aparanji, S., Mazumder, D. & Srinivasan, V. Interferometric diffusing wave spectroscopy imaging with an electronically variable time-of-flight filter. Optica 10, 42–52 (2022).
Google Scholar
Borycki, D., Kholiqov, O. & Srinivasan, V. J. Interferometric near-infrared spectroscopy directly quantifies optical field dynamics in turbid media. Optica 3, 1471 (2016).
Google Scholar
Pagliazzi, M. et al. Time resolved speckle contrast optical spectroscopy at quasi-null source-detector separation for non-invasive measurement of microvascular blood flow. Biomed. Opt. Express 12, 1499 (2021).
Google Scholar
Poon, C.-S. et al. First-in-clinical application of a time-gated diffuse correlation spectroscopy system at 1064 nm using superconducting nanowire single photon detectors in a neuro intensive care unit. Biomed. Opt. Express 13, 1344 (2022).
Google Scholar
Zilpelwar, S. et al. A model of dynamic speckle evolution for evaluating laser speckle contrast measurements of tissue dynamics. Biomed. Opt. Express 13, 6533–6549 (2022).
Google Scholar
Dragojević, T. et al. Compact, multi-exposure speckle contrast optical spectroscopy (SCOS) device for measuring deep tissue blood flow. Biomed. Opt. Express 9, 322 (2018).
Google Scholar
Valdes, C. P. et al. Speckle contrast optical spectroscopy, a non-invasive, diffuse optical method for measuring microvascular blood flow in tissue. Biomed. Opt. Express 5, 2769 (2014).
Google Scholar
Carp, S. A. et al. Diffuse correlation spectroscopy measurements of blood flow using 1064 nm light. J. Biomed. Opt. 25, 97003–97004 (2020).
Google Scholar
Ozana, N. et al. Superconducting nanowire single-photon sensing of cerebral blood flow. Neurophotonics 8, 35006 (2021).
Google Scholar
Robinson, M. B. et al. Diffuse correlation spectroscopy beyond the water peak enabled by cross-correlation of the signals from InGaAs/InP single photon detectors. IEEE Trans. Biomed. Eng. 69, 1943–1953 (2022).
Google Scholar
Zhou, W., Kholiqov, O., Chong, S. P. & Srinivasan, V. J. Highly parallel, interferometric diffusing wave spectroscopy for monitoring cerebral blood flow dynamics. Optica 5, 518 (2018).
Google Scholar
Siegert, A. J. F. On the fluctuations in signals returned by many independently moving scatterers. (Radiation Laboratory, Massachusetts Institute of Technology, 1943).
Bellini, T., Glaser, M. A., Clark, N. A. & Degiorgio, V. Effects of finite laser coherence in quasielastic multiple scattering. Phys. Rev. A (Coll Park) 44, 5215 (1991).
Google Scholar
Pine, D. J., Weitz, D. A., Chaikin, P. M. & Herbolzheimer, E. Diffusing wave spectroscopy. Phys. Rev. Lett. 60, 1134–1137 (1988).
Google Scholar
Boas, D. A. et al. Establishing the diffuse correlation spectroscopy signal relationship with blood flow. Neurophotonics 3, 31412 (2016).
Verdecchia, K., Diop, M., Morrison, L. B., Lee, T.-Y. & Lawrence, K. S. Assessment of the best flow model to characterize diffuse correlation spectroscopy data acquired directly on the brain. Biomed. Opt. Express 6, 4288 (2015).
Google Scholar
Sakadžic, S. et al. Theoretical model of blood flow measurement by diffuse correlation spectroscopy. J. Biomed. Opt. 22, 27006 (2017).
Google Scholar
Carp, S. A. et al. Due to intravascular multiple sequential scattering, diffuse correlation spectroscopy of tissue primarily measures relative red blood cell motion within vessels. Biomed. Opt. Express 2, 2047 (2011).
Google Scholar
Du Le, V. N. & Srinivasan, V. J. Beyond diffuse correlations: Deciphering random flow in time-of-flight resolved light dynamics. Opt. Express 28, 11191 (2020).
Google Scholar
Koppel, D. Statistical accuracy in FCS. Phys. Rev. A (Coll Park) 10, 1938–1945 (1974).
Google Scholar
American National Standard for Safe Use of Lasers. ANSI Z136.1-2007. (2007).
Farzam, P. et al. Fast diffuse correlation spectroscopy (DCS) for non-invasive measurement of intracranial pressure (ICP)(Conference Presentation). In Clinical and Translational Neurophotonics (eds. Madsen, S. J. & Yang, V. X. D.) vol. 10050 100500U-100500U (International Society for Optics and Photonics, 2017).
Fischer, K., Guensch, D. P. & Friedrich, M. G. Response of myocardial oxygenation to breathing manoeuvres and adenosine infusion. Eur. Heart J. Cardiovasc. Imaging 16, 395–401 (2015).
Google Scholar
Parkes, M. J., Green, S., Stevens, A. M. & Clutton-Brock, T. H. Assessing and ensuring patient safety during breath-holding for radiotherapy. Br. J. Radiol. 87, 20140454 (2014).
Google Scholar
Perini, R. et al. Heart rate and blood pressure time courses during prolonged dry apnoea in breath-hold divers. Eur. J. Appl. Physiol. 104, 1–7 (2008).
Google Scholar
Wilson, D. F. et al. Effect of hyperventilation on oxygenation of the brain cortex of newborn piglets. J. Appl. Physiol. 70, 2691–2696 (1991).
Google Scholar
Meyer, J. S., Gotoh, F., Takagi, Y. & Kakimi, R. Cerebral hemodynamics, blood gases, and electrolytes during breath-holding and the Valsalva maneuver. Circulation 33, II–35 (1966).
Google Scholar
Baker, W. B. et al. Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts. Neurophotonics 2, 35004 (2015).
Skytioti, M., Søvik, S. & Elstad, M. Respiration-related cerebral blood flow variability increases during control-mode non-invasive ventilation in normovolemia and hypovolemia. Eur. J. Appl. Physiol. 117, 2237–2249 (2017).
Google Scholar
Fang, Q. & Boas, D. A. Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units. Opt. Express 17, 20178–20190 (2009).
Google Scholar
Larsen, J. et al. Breath holding for 20 s following extended expiration is a practical, effective and robust standard when measuring cerebrovascular reactivity in healthy adults using BOLD fMRI at 3 T. Neuroimage Rep. 1, 100021 (2021).
Zerweck, L., Hauser, T.-K., Roder, C. & Klose, U. Investigation of the BOLD-based MRI signal time course during short breath-hold periods for estimation of the cerebrovascular reactivity. SN Compr. Clin. Med. 2, 1551–1562 (2020).
Google Scholar
Wu, M. M. et al. Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models. Biomed. Opt. Express 13, 1131 (2022).
Google Scholar
Wu, M. M. et al. Improved accuracy of cerebral blood flow quantification in the presence of systemic physiology cross-talk using multi-layer Monte Carlo modeling. Neurophotonics 8, 15001 (2021).
Zhao, H., Sathialingam, E. & Buckley, E. M. Accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow when using a three-layer analytical model. Biomed. Opt. Express 12, 7149–7161 (2021).
Google Scholar
James, E. & Powell, S. Fourier domain diffuse correlation spectroscopy with heterodyne holographic detection. Biomed. Opt. Express 11, 6755 (2020).
Google Scholar