Coherent hemodynamics spectroscopy in a single step

Kainerstorfer, Jana M.; Sassaroli, Angelo; Fantini, Sergio

doi:10.1364/boe.5.003403

Cited by 7 publications

(7 citation statements)

References 32 publications

(50 reference statements)

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“…4(A)); this noise assignment, in turn, prompted the need for increased temporal averaging. Interestingly, although heartbeat oscillations are well recognized in the NIRS community [63][64][65], the DCS community has been comparatively slow to appreciate the full potential of fast blood flow measurements.…”

Section: Discussionmentioning

confidence: 99%

Fast blood flow monitoring in deep tissues with real-time software correlators

Wang

Parthasarathy

Baker

et al. 2016

Biomed. Opt. Express

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Abstract:We introduce, validate and demonstrate a new software correlator for high-speed measurement of blood flow in deep tissues based on diffuse correlation spectroscopy (DCS). The software correlator scheme employs standard PC-based data acquisition boards to measure temporal intensity autocorrelation functions continuously at 50 − 100 Hz, the fastest blood flow measurements reported with DCS to date. The data streams, obtained in vivo for typical source-detector separations of 2.5 cm, easily resolve pulsatile heart-beat fluctuations in blood flow which were previously considered to be noise. We employ the device to separate tissue blood flow from tissue absorption/scattering dynamics and thereby show that the origin of the pulsatile DCS signal is primarily flow, and we monitor cerebral autoregulation dynamics in healthy volunteers more accurately than with traditional instrumentation as a result of increased data acquisition rates. Finally, we characterize measurement signal-to-noise ratio and identify count rate and averaging parameters needed for optimal performance. References and links 1. D. A. Boas, L. E. Campbell, and A. G. Yodh, "Scattering and imaging with diffusing temporal field correlations," Phy. Rev. Lett. 75, 1855Lett. 75, -1858Lett. 75, (1995

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Section: Discussionmentioning

confidence: 99%

Fast blood flow monitoring in deep tissues with real-time software correlators

Wang

Parthasarathy

Baker

et al. 2016

Biomed. Opt. Express

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“…22 As shown above for the arterial saturation, if blood flow contributions are negligible, then Arg½D − Arg½O ¼ 0. However, we have previously demonstrated, [13][14][15][16]29 and we will show again here that this is not the case for brain measurements, where blood flow contributions cannot be neglected. Hence, it is not correct to use the ratio jOj∕jTj to obtain S ðvÞ from data collected during paced or normal breathing, since O ≠ O V .…”

Section: Measuring the Venous Saturation From Volumementioning

confidence: 57%

“…We have repeatedly shown that oxy-and deoxyhemoglobin measurements on muscle tissue are in phase 14 at the respiratory frequency, indicating that blood volume changes are dominant and blood flow changes can be considered negligible. However, cerebral measurements have shown a consistent out of phase behavior between oxy-and deoxyhemoglobin, [14][15][16][17][18][19] indicating that blood flow changes are not a negligible contributor to the optical signals. The reason for this is that blood volume changes are smaller in the brain than other tissues due to the rigid enclosure of the skull, 20 damping the magnitude of vessel diameter changes.…”

Section: Arterial Saturation Measurements By Pulsementioning

confidence: 99%

“…In our previous applications of the hemodynamic model, which is an analytical model that takes into account dynamic autoregulation and the microvascular blood transit times, we have focused on low-frequency cerebral hemodynamics (of the order of 0.1 Hz or less) [13][14][15][16][17][18]29 for the assessment of blood flow, autoregulation, and blood volume in the microvasculature. In this work, we demonstrate that the pulsatile signals measured in the brain at the heart rate and at the respiration frequency can be quantitatively described by the model and that CBF changes should be taken into account to obtain reliable measurements of the oxygen saturation of hemoglobin of timevarying vascular compartments.…”

Section: Accounting For Contributions From Blood Flow Oscillationsmentioning

confidence: 99%

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Optical oximetry of volume-oscillating vascular compartments: contributions from oscillatory blood flow

2016

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We present a quantitative analysis of dynamic diffuse optical measurements to obtain oxygen saturation of hemoglobin in volume oscillating compartments. We used a phasor representation of oscillatory hemodynamics at the heart rate and respiration frequency to separate the oscillations of tissue concentrations of oxyhemoglobin (O) and deoxyhemoglobin (D) into components due to blood volume (subscript V V ) and blood flow (subscript F F ): O=O V +O F O=OV+OF , D=D V +D F D=DV+DF . This is achieved by setting the phase angle Arg(O F )−Arg(O) Arg(OF)−Arg(O) , which can be estimated by a hemodynamic model that we recently developed. We found this angle to be −72 deg −72 deg for the cardiac pulsation at 1 Hz, and −7 deg −7 deg for paced breathing at 0.1 Hz. Setting this angle, we can obtain the oxygen saturation of hemoglobin of the volume-oscillating vascular compartment, S V =|O V |/(|O V |+|D V |) SV=|OV|/(|OV|+|DV|) . We demonstrate this approach with cerebral near-infrared spectroscopy measurements on healthy volunteers at rest (n=4 n=4 ) and during 0.1 Hz paced breathing (n=3 n=3 ) with a 24-channel system. Rest data at the cardiac frequency were used to calculate the arterial saturation, S (a) S(a) ; over all subjects and channels, we found ⟨S V ⟩=⟨S (a) ⟩=0.96±0.02 ⟨SV⟩=⟨S(a)⟩=0.96±0.02 . In the case of paced breathing, we found ⟨S V ⟩=0.66±0.14 ⟨SV⟩=0.66±0.14 , which reflects venous-dominated hemodynamics at the respiratory frequency.

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“…The search regions for the fitting parameters are defined by ranges found in the literature. 18 The analytical expressions derived from the hemodynamic model and the simplifying assumptions relating these six hemodynamic parameters and the CHS spectra are described in detail in Kainerstorfer et al 19 In the case of breast measurements, because the phasors Dðω i Þ, Oðω i Þ, and Tðω i Þ were found to be in-phase with each other at all measured frequencies, the amplitude ratio jOðω i Þj∕jTðω i Þj provides a measure of the oxygen saturation of hemoglobin in the volume-oscillating vascular compartments, 9 which we indicate here with S V . This measure of hemoglobin saturation is a weighted average of the saturations of the volume-oscillating compartments, where each vascular compartment is weighted according to its relative contributions to the overall blood volume oscillations:…”

Section: Oðωþmentioning

confidence: 99%

Blood-pressure-induced oscillations of deoxy- and oxyhemoglobin concentrations are in-phase in the healthy breast and out-of-phase in the healthy brain

et al. 2016

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Abstract. We present a near-infrared spectroscopy (NIRS) study of local hemodynamics in the breast and the brain (prefrontal cortex) of healthy volunteers in a protocol involving periodic perturbations to the systemic arterial blood pressure. These periodic perturbations were achieved by cyclic inflation (to a pressure of 200 mmHg) and deflation (at frequencies of 0.046, 0.056, 0.063, 0.071, and 0.083 Hz) of two pneumatic cuffs wrapped around the subject's thighs. As a result of these systemic perturbations, the concentrations of deoxy-and oxyhemoglobin in tissue (D and O, respectively) oscillate at the set frequency. We found that the oscillations of D and O in breast tissue are in-phase at all frequencies considered, a result that we attribute to dominant contributions from blood volume oscillations. In contrast, D and O oscillations in brain tissue feature a frequency-dependent phase difference, which we attribute to significant contributions from cerebral blood flow oscillations. Frequency-resolved measurements of D and O oscillations are exploited by the technique of coherent hemodynamics spectroscopy for the assessment of cerebrovascular parameters and cerebral autoregulation. We show the relevant physiological information content of NIRS measurements of oscillatory hemodynamics, which have qualitatively distinct features in the healthy breast and healthy brain. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Coherent hemodynamics spectroscopy in a single step

Cited by 7 publications

References 32 publications

Fast blood flow monitoring in deep tissues with real-time software correlators

Fast blood flow monitoring in deep tissues with real-time software correlators

Optical oximetry of volume-oscillating vascular compartments: contributions from oscillatory blood flow

Blood-pressure-induced oscillations of deoxy- and oxyhemoglobin concentrations are in-phase in the healthy breast and out-of-phase in the healthy brain

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