Portable, high speed blood flow measurements enabled by long wavelength, interferometric diffuse correlation spectroscopy (LW-iDCS)

Combined frequency domain near-infrared spectroscopy and diffuse correlation spectroscopy system for comprehensive metabolic monitoring of inspiratory muscles during loading

Significance

Mechanical ventilation (MV) is a cornerstone technology in the intensive care unit as it assists with the delivery of oxygen in critically ill patients. The process of weaning patients from MV can be long and arduous and can lead to serious complications for many patients. Despite the known importance of inspiratory muscle function in the success of weaning, current clinical standards do not include direct monitoring of these muscles.

Aim

The goal of this project was to develop and validate a combined frequency domain near-infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) system for the noninvasive characterization of inspiratory muscle response to a load.

Approach

The system was fabricated by combining a custom digital FD-NIRS and DCS system. It was validated via liquid phantom titrations and a healthy volunteer study. The sternocleidomastoid (SCM), an accessory muscle of inspiration, was monitored during a short loading period in fourteen young, healthy volunteers. Volunteers performed two different respiratory exercises, a moderate load and a high load, which consisted of a one-minute baseline, a one-minute load, and a six-minute recovery period.

Results

The system has low crosstalk between absorption, reduced scattering, and flow when tested in a set of liquid titrations. Faster dynamics were observed for changes in blood flow index (BF i ), and metabolic rate of oxygen (MRO 2 ) compared with hemoglobin + myoglobin (Hb+Mb) based parameters after the onset of loads in males. Additionally, larger percent changes in BF i , and MRO 2 were observed compared with Hb+Mb parameters in both males and females. There were also sex differences in baseline values of oxygenated Hb+Mb, total Hb+Mb, and tissue saturation.

Conclusions

The dynamic characteristics of Hb+Mb concentration and blood flow were distinct during loading of the SCM, suggesting that the combination of FD-NIRS and DCS may provide a more complete picture of inspiratory muscle dynamics.

Measuring pulsatile cortical blood flow and volume during carotid endarterectomy

Carotid endarterectomy (CEA) involves removal of plaque in the carotid artery to reduce the risk of stroke and improve cerebral perfusion. This study aimed to investigate the utility of assessing pulsatile blood volume and flow during CEA. Using a combined near-infrared spectroscopy/diffuse correlation spectroscopy instrument, pulsatile hemodynamics were assessed in 12 patients undergoing CEA. Alterations to pulsatile amplitude, pulse transit time, and beat morphology were observed in measurements ipsilateral to the surgical side. The additional information provided through analysis of pulsatile hemodynamic signals has the potential to enable the discovery of non-invasive biomarkers related to cortical perfusion.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

Significance

The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique.

Aim

We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.

Approach

Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy.

Results

Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow.

Conclusion

We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.

Comparison of diffuse correlation spectroscopy analytical models for measuring cerebral blood flow in adults

Significance

Although multilayer analytical models have been proposed to enhance brain sensitivity of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow, the traditional homogeneous model remains dominant in clinical applications. Rigorous in vivo comparison of these analytical models is lacking.

Aim

We compare the performance of different analytical models to estimate a cerebral blood flow index (CBFi) with DCS in adults.

Approach

Resting-state data were obtained on a cohort of 20 adult patients with subarachnoid hemorrhage. Data at 1 and 2.5 cm source-detector separations were analyzed with the homogenous, two-layer, and three-layer models to estimate scalp blood flow index and CBFi. The performance of each model was quantified via fitting convergence, fit stability, brain-to-scalp flow ratio (BSR), and correlation with transcranial Doppler ultrasound (TCD) measurements of cerebral blood flow velocity in the middle cerebral artery (MCA).

Results

The homogeneous model has the highest pass rate (100%), lowest coefficient of variation (CV) at rest (median [IQR] at 1 Hz of 0.18 [0.13, 0.22]), and most significant correlation with MCA blood flow velocities (R s = 0.59 , p = 0.010 ) compared with both the two- and three-layer models. The multilayer model pass rate was significantly correlated with extracerebral layer thicknesses. Discarding datasets with non-physiological BSRs increased the correlation between DCS measured CBFi and TCD measured MCA velocities for all models.

Conclusions

We found that the homogeneous model has the highest pass rate, lowest CV at rest, and most significant correlation with MCA blood flow velocities. Results from the multilayer models should be taken with caution because they suffer from lower pass rates and higher coefficients of variation at rest and can converge to non-physiological values for CBFi. Future work is needed to validate these models in vivo, and novel approaches are merited to improve the performance of the multimodel models.

Impaired cerebrovascular reactivity in pediatric sickle cell disease using diffuse correlation spectroscopy

Cerebrovascular reactivity (CVR), defined as the ability of cerebral vasculature to dilate in response to a vasodilatory stimulus, is an integral mechanism in brain homeostasis that is thought to be impaired in sickle cell disease (SCD). This study used diffuse correlation spectroscopy and a simple breath-hold stimulus to quantify CVR non-invasively in a cohort of 12 children with SCD and 14 controls. Median [interquartile range] CVR was significantly decreased in SCD compared to controls (2.03 [1.31, 2.44] versus 3.49 [3.00, 4.11] %/mmHg, p = 0.028). These results suggest DCS may provide a feasible means to routinely monitor CVR impairments in pediatric SCD.

Interferometric speckle visibility spectroscopy (iSVS) for measuring decorrelation time and dynamics of moving samples with enhanced signal-to-noise ratio and relaxed reference requirements

Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering medium and measuring the speckle decorrelation time to quantify the scattering medium's dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement. This SNR is often low in certain applications because of high noise variances and low signal intensity, especially in biological applications with restricted exposure and emission levels. To address this photon-limited signal-to-noise ratio problem, we investigated, theoretically and experimentally, the SNR of an interferometric speckle visibility spectroscopy (iSVS) compared to more traditional DWS methods. We found that iSVS can provide excellent SNR performance through its ability to overcome camera noise. We also proved an iSVS system has more relaxed constraints on the reference beam properties. For an iSVS system to function properly, we only require the reference beam to exhibit local temporal stability, while incident angle, reference phase and intensity uniformity do not need to be constrained. This flexibility can potentially enable more unconventional iSVS implementation schemes.

Optical Flow-Based Full-Field Quantitative Blood-Flow Velocimetry Using Temporal Direction Filtering and Peak Interpolation

The quantitative measurement of the microvascular blood-flow velocity is critical to the early diagnosis of microvascular dysfunction, yet there are several challenges with the current quantitative flow velocity imaging techniques for the microvasculature. Optical flow analysis allows for the quantitative imaging of the blood-flow velocity with a high spatial resolution, using the variation in pixel brightness between consecutive frames to trace the motion of red blood cells. However, the traditional optical flow algorithm usually suffers from strong noise from the background tissue, and a significant underestimation of the blood-flow speed in blood vessels, due to the errors in detecting the feature points in optical images. Here, we propose a temporal direction filtering and peak interpolation optical flow method (TPIOF) to suppress the background noise, and improve the accuracy of the blood-flow velocity estimation. In vitro phantom experiments and in vivo animal experiments were performed to validate the improvements in our new method.