Interferometric diffuse correlation spectroscopy improves measurements at long source-detector separation and low photon count rate

Comprehensive workflow and its validation for simulating diffuse speckle statistics for optical blood flow measurements

Diffuse optical methods including speckle contrast optical spectroscopy and tomography (SCOS and SCOT), use speckle contrast (κ) to measure deep blood flow. In order to design practical systems, parameters such as signal-to-noise ratio (SNR) and the effects of limited sampling of statistical quantities, should be considered. To that end, we have developed a method for simulating speckle contrast signals including effects of detector noise. The method was validated experimentally, and the simulations were used to study the effects of physical and experimental parameters on the accuracy and precision of κ. These results revealed that systematic detector effects resulted in decreased accuracy and precision of κ in the regime of low detected signals. The method can provide guidelines for the design and usage of SCOS and/or SCOT instruments.

Validation of the Openwater wearable optical system: cerebral hemodynamic monitoring during a breath-hold maneuver

Significance

Bedside cerebral blood flow (CBF) monitoring has the potential to inform and improve care for acute neurologic diseases, but technical challenges limit the use of existing techniques in clinical practice.

Aim

Here, we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics.

Approach

We monitored 25 healthy adults with the Openwater system and concurrent transcranial Doppler (TCD) while performing a breath-hold maneuver to increase CBF. Relative blood flow (rBF) was derived from changes in speckle contrast, and relative blood volume (rBV) was derived from changes in speckle average intensity.

Results

A strong correlation was observed between beat-to-beat optical rBF and TCD-measured cerebral blood flow velocity (CBFv), R = 0.79 ; the slope of the linear fit indicates good agreement, 0.87 (95% CI: 0.83 - 0.92 ). Beat-to-beat rBV and CBFv were also strongly correlated, R = 0.72 , but as expected the two variables were not proportional; changes in rBV were smaller than CBFv changes, with linear fit slope of 0.18 (95% CI: 0.17 to 0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics.

Conclusions

This first in vivo validation of the Openwater optical system highlights its potential as a cerebral hemodynamic monitor, but additional validation is needed in disease states.

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.

Assessing depth sensitivity in laser interferometry speckle visibility spectroscopy (iSVS) through source-to-detector distance variation and cerebral blood flow monitoring in humans and rabbits

Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to monitor cerebral blood flow. The technique, using a multi-pixel detecting device (e.g., camera), allows the detection of a larger number of speckles, increasing the proportion of light that is detected. Due to this increase, it is possible to collect light that has propagated deeper through the brain. As a direct consequence, cerebral blood flow can be monitored. However, isolating the cerebral blood flow from the other layers, such as the scalp or skull components, remains challenging. In this paper, we report our investigations on the depth-sensitivity of laser interferometry speckle visibility spectroscopy (iSVS). Specifically, we varied the depth of penetration of the laser light into the head by tuning the source-to-detector distance, and identified the transition point at which cerebral blood flow in humans and rabbits starts to be detected.

Non-invasive diffuse optical monitoring of cerebral physiology in an adult swine-model of impact traumatic brain injury

In this study, we used diffuse optics to address the need for non-invasive, continuous monitoring of cerebral physiology following traumatic brain injury (TBI). We combined frequency-domain and broadband diffuse optical spectroscopy with diffuse correlation spectroscopy to monitor cerebral oxygen metabolism, cerebral blood volume, and cerebral water content in an established adult swine-model of impact TBI. Cerebral physiology was monitored before and after TBI (up to 14 days post injury). Overall, our results suggest that non-invasive optical monitoring can assess cerebral physiologic impairments post-TBI, including an initial reduction in oxygen metabolism, development of cerebral hemorrhage/hematoma, and brain swelling.

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

Diffuse correlation spectroscopy (DCS) is an optical technique that can be used to characterize blood flow in tissue. The measurement of cerebral hemodynamics has arisen as a promising use case for DCS, though traditional implementations of DCS exhibit suboptimal signal-to-noise ratio (SNR) and cerebral sensitivity to make robust measurements of cerebral blood flow in adults. In this work, we present long wavelength, interferometric DCS (LW-iDCS), which combines the use of a longer illumination wavelength (1064 nm), multi-speckle, and interferometric detection, to improve both cerebral sensitivity and SNR. Through direct comparison with long wavelength DCS based on superconducting nanowire single photon detectors, we demonstrate an approximate 5× improvement in SNR over a single channel of LW-DCS in the measured blood flow signals in human subjects. We show equivalence of extracted blood flow between LW-DCS and LW-iDCS, and demonstrate the feasibility of LW-iDCS measured at 100 Hz at a source-detector separation of 3.5 cm. This improvement in performance has the potential to enable robust measurement of cerebral hemodynamics and unlock novel use cases for diffuse correlation spectroscopy.

Diffuse correlation spectroscopy: current status and future outlook

Diffuse correlation spectroscopy (DCS) has emerged as a versatile, noninvasive method for deep tissue perfusion assessment using near-infrared light. A broad class of applications is being pursued in neuromonitoring and beyond. However, technical limitations of the technology as originally implemented remain as barriers to wider adoption. A wide variety of approaches to improve measurement performance and reduce cost are being explored; these include interferometric methods, camera-based multispeckle detection, and long path photon selection for improved depth sensitivity. We review here the current status of DCS technology and summarize future development directions and the challenges that remain on the path to widespread adoption.

Influence of oversimplifying the head anatomy on cerebral blood flow measurements with diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) is an emerging optical modality for non-invasive assessment of an index of regional cerebral blood flow. By the nature of this noninvasive measurement, light must pass through extracerebral layers (i.e., skull, scalp, and cerebral spinal fluid) before detection at the tissue surface. To minimize the contribution of these extracerebral layers to the measured signal, an analytical model has been developed that treats the head as a series of three parallel and infinitely extending slabs (mimicking scalp, skull, and brain). The three-layer model has been shown to provide a significant improvement in cerebral blood flow estimation over the typically used model that treats the head as a bulk homogenous medium. However, the three-layer model is still a gross oversimplification of the head geometry that ignores head curvature, the presence of cerebrospinal fluid (CSF), and heterogeneity in layer thickness.

Aim

Determine the influence of oversimplifying the head geometry on cerebral blood flow estimated with the three-layer model.

Approach

Data were simulated with Monte Carlo in a four-layer slab medium and a three-layer sphere medium to isolate the influence of CSF and curvature, respectively. Additionally, simulations were performed on magnetic resonance imaging (MRI) head templates spanning a wide-range of ages. Simulated data were fit to both the homogenous and three-layer model for CBF. Finally, to mitigate the errors in potential CBF estimation due to the difficulty in defining layer thickness, we investigated an approach to identify an equivalent, "optimized" thickness via a pressure modulation.

Results

Both head curvature and failing to account for CSF lead to significant errors in the estimation of CBF. However, the effect of curvature and CSF on relative changes in CBF is minimal. Further, we found that CBF was underestimated in all MRI-templates, although the magnitude of these underestimations was highly influenced by small variations in the source and detector optode positioning. The optimized thickness obtained from pressure modulation did not improve estimation accuracy of CBF, although it did significantly improve the estimation accuracy of relative changes in CBF.

Conclusions

In sum, these findings suggest that the three-layer model holds promise for improving estimation of relative changes in cerebral blood flow; however, estimations of absolute cerebral blood flow with the approach should be viewed with caution given that it is difficult to account for appreciable sources of error, such as curvature and CSF.

Interferometric diffuse optics: recent advances and future outlook

The field of diffuse optics has provided a rich set of neurophotonic tools to measure the human brain noninvasively. Interferometric detection is a recent, exciting methodological development in this field. The approach is especially promising for the measurement of diffuse fluctuation signals related to blood flow. Benefitting from inexpensive sensor arrays, the interferometric approach has already dramatically improved throughput, enabling the measurement of brain blood flow faster and deeper. The interferometric approach can also achieve time-of-flight resolution, improving the accuracy of acquired signals. We provide a historical perspective and summary of recent work in the nascent area of interferometric diffuse optics. We predict that the convergence of interferometric technology with existing economies of scale will propel many advances in the years to come.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Performance optimisation of a holographic Fourier domain diffuse correlation spectroscopy instrument

We have previously demonstrated a novel interferometric multispeckle Fourier domain diffuse correlation spectroscopy system that makes use of holographic camera-based detection, and which is capable of making in vivo pulsatile flow measurements. In this work, we report on a systematic characterisation of the signal-to-noise ratio performance of our system. This includes demonstration and elimination of laser mode hopping, and correction for the instrument's modulation transfer function to ensure faithful reconstruction of measured intensity profiles. We also demonstrate a singular value decomposition approach to ensure that spatiotemporally correlated experimental noise sources do not limit optimal signal-to-noise ratio performance. Finally, we present a novel multispeckle denoising algorithm that allows our instrument to achieve a signal-to-noise ratio gain that is equal to the square root of the number of detected speckles, whilst detecting up to ∼1290 speckles in parallel. The signal-to-noise ratio gain of 36 that we report is a significant step toward mitigating the trade-off that exists between signal-to-noise ratio and imaging depth in diffuse correlation spectroscopy.

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

Diffuse correlation spectroscopy beyond the water peak enabled by cross-correlation of the signals from InGaAs/InP single photon detectors

OBJECTIVE

Diffuse correlation spectroscopy (DCS) is an optical technique that allows for the non-invasive measurement of blood flow. Recent work has shown that utilizing longer wavelengths beyond the traditional NIR range provides a significant improvement to signal-to-noise ratio (SNR). However, current detectors both sensitive to longer wavelengths and suitable for clinical applications (InGaAs/InP SPADs) suffer from suboptimal afterpulsing and dark noise characteristics. To overcome these barriers, we introduce a cross correlation method to more accurately recover blood flow information using InGaAs/InP SPADs.

METHODS

Two InGaAs/InP SPAD detectors were used for during in vitro and in vivo DCS measurements. Cross correlation of the photon streams from each detector was performed to calculate the correlation function. Detector operating parameters were varied to determine parameters which maximized measurement SNR. State-space modeling was performed to determine the detector characteristics at each operating point.

RESULTS

Evaluation of detector characteristics was performed across the range of operating conditions. Modeling the effects of the detector noise on the correlation function provided a method to correct the distortion of the correlation curve, yielding accurate recovery of flow information as confirmed by a reference detector.

CONCLUSION

Through a combination of cross-correlation of the signals from two detectors, model-based characterization of detector response, and optimization of detector operating parameters, the method allows for the accurate estimation of the true blood flow index.

SIGNIFICANCE

This work presents a method by which DCS can be performed at longer NIR wavelengths with existing detector technology, taking advantage of the increased SNR.

Multi-exposure interferometric diffusing wave spectroscopy

We present multi-exposure interferometric diffusing wave spectroscopy (MiDWS), which measures brain blood flow index (BFI) continuously and non-invasively. MiDWS employs interferometry to detect low light levels, probing the optical field autocorrelation indirectly by varying the sensor exposure time. Here MiDWS is compared with conventional interferometric diffusing wave spectroscopy and speckle contrast optical spectroscopy in phantoms. Notably, the MiDWS approach enables the use of low frame rate, two-dimensional complementary metal-oxide semiconductor cameras in a short exposure time regime, where detector noise greatly exceeds the sample photon count. Finally, we show that MiDWS can monitor the BFI simultaneously at two source-collector separations (1 and 3 cm) on the adult human head on a single camera, enabling the use of superficial signal regression techniques to improve brain specificity.

Superconducting nanowire single-photon sensing of cerebral blood flow

Significance: The ability of diffuse correlation spectroscopy (DCS) to measure cerebral blood flow (CBF) in humans is hindered by the low signal-to-noise ratio (SNR) of the method. This limits the high acquisition rates needed to resolve dynamic flow changes and to optimally filter out large pulsatile oscillations and prevents the use of large source-detector separations ( ≥ 3    cm ), which are needed to achieve adequate brain sensitivity in most adult subjects. Aim: To substantially improve SNR, we have built a DCS device that operates at 1064 nm and uses superconducting nanowire single-photon detectors (SNSPD). Approach: We compared the performances of the SNSPD-DCS in humans with respect to a typical DCS system operating at 850 nm and using silicon single-photon avalanche diode detectors. Results: At a 25-mm separation, we detected 13 ± 6 times more photons and achieved an SNR gain of 16 ± 8 on the forehead of 11 subjects using the SNSPD-DCS as compared to typical DCS. At this separation, the SNSPD-DCS is able to detect a clean pulsatile flow signal at 20 Hz in all subjects. With the SNSPD-DCS, we also performed measurements at 35 mm, showing a lower scalp sensitivity of 31 ± 6 % with respect to the 48 ± 8 % scalp sensitivity at 25 mm for both the 850 and 1064 nm systems. Furthermore, we demonstrated blood flow responses to breath holding and hyperventilation tasks. Conclusions: While current commercial SNSPDs are expensive, bulky, and loud, they may allow for more robust measures of non-invasive cerebral perfusion in an intensive care setting.

Recipes for diffuse correlation spectroscopy instrument design using commonly utilized hardware based on targets for signal-to-noise ratio and precision

Over the recent years, a typical implementation of diffuse correlation spectroscopy (DCS) instrumentation has been adapted widely. However, there are no detailed and accepted recipes for designing such instrumentation to meet pre-defined signal-to-noise ratio (SNR) and precision targets. These require specific attention due to the subtleties of the DCS signals. Here, DCS experiments have been performed using liquid tissue simulating phantoms to study the effect of the detected photon count-rate, the number of parallel detection channels and the measurement duration on the precision and SNR to suggest scaling relations to be utilized for device design.

Functional interferometric diffusing wave spectroscopy of the human brain

Cerebral blood flow (CBF) is essential for brain function, and CBF-related signals can inform us about brain activity. Yet currently, high-end medical instrumentation is needed to perform a CBF measurement in adult humans. Here, we describe functional interferometric diffusing wave spectroscopy (fiDWS), which introduces and collects near-infrared light via the scalp, using inexpensive detector arrays to rapidly monitor coherent light fluctuations that encode brain blood flow index (BFI), a surrogate for CBF. Compared to other functional optical approaches, fiDWS measures BFI faster and deeper while also providing continuous wave absorption signals. Achieving clear pulsatile BFI waveforms at source-collector separations of 3.5 cm, we confirm that optical BFI, not absorption, shows a graded hypercapnic response consistent with human cerebrovascular physiology, and that BFI has a better contrast-to-noise ratio than absorption during brain activation. By providing high-throughput measurements of optical BFI at low cost, fiDWS will expand access to CBF.