Diffuse correlation spectroscopy: current status and future outlook

Two paths to one destination: altered low-frequency oscillations of cerebral perfusion and oxygenation but not oxygen metabolism in mild cognitive impairment

Cerebrovascular dysfunction, a risk factor for dementia, is challenging to detect in mild cognitive impairment (MCI). Herein, we used novel, light-based technology to investigate low-frequency hemodynamic oscillations (LFOs; 0.02-0.16 Hz) in cerebral perfusion, oxygenation, and relative metabolic rate of oxygen (rCMRO2) in MCI (n = 13; 74 ± 6 yr) and cognitively intact controls (n = 10; 69 ± 6 yr). Relative cerebral microvascular perfusion and tissue oxygenation changes were recorded using a depth-enhanced optical monitoring system. Continuous wavelet transforms were used to compare average LFO power between groups (α = 0.025). Compared with controls, MCI had lower LFO power in microvascular perfusion, greater power in oxygenation (P ≤ 0.02), and no statistical difference in oscillatory power for rCMRO2. Similar rCMRO2 but opposing changes in oscillatory power for cerebral perfusion and oxygenation associated with MCI suggest an adaptation to maintain energy production.NEW & NOTEWORTHY We used a novel, depth-enhanced optical monitoring system to investigate low-frequency hemodynamic oscillations (0.02-0.16 Hz) in cerebral microvascular perfusion, oxygenation, and relative metabolic rate of oxygen in patients with MCI and cognitively intact controls. Our findings indicate cerebrovascular dysfunction in MCI, wherein the regulation of oxygenation is altered to maintain metabolism in an environment with attenuated vascular control. These findings highlight the potential of using optical technology to assess cerebrovascular function in MCI.

Electroconvulsive therapy generates a postictal wave of spreading depolarization in mice and humans

Electroconvulsive therapy (ECT) is a fast-acting, highly effective, and safe treatment for medication-resistant depression. Historically, the clinical benefits of ECT have been attributed to generating a controlled seizure; however, the underlying neurobiology is understudied and unresolved. Using optical neuroimaging of neural activity and hemodynamics in a mouse model of ECT, we demonstrated that a second brain event follows seizure: cortical spreading depolarization (CSD). We found that ECT pulse parameters and electrode configuration directly shaped the wave dynamics of seizure and subsequent CSD. To translate these findings to human patients, we used non-invasive diffuse optical monitoring of cerebral blood flow and oxygenation during routine ECT treatments. We observed that human brains reliably generate hyperemic waves after ECT seizure which are highly consistent with CSD. These results challenge a long-held assumption that seizure is the primary outcome of ECT and point to new opportunities for optimizing ECT stimulation parameters and treatment outcomes.

1060 nm interferometric near-infrared spectroscopy

Recently, interferometric near-infrared spectroscopy (iNIRS) has emerged to measure diffuse light field fluctuations with time-of-flight (TOF) resolution. Yet, current iNIRS implementations suffer from low signal-to-noise ratio (SNR). Longer wavelengths, with lower photon energy, lower reduced scattering in biological tissues, and higher permissible exposures, have the potential to increase SNR. Here, we investigate iNIRS at 1060 nm. Across various forehead locations, we find that the autocorrelation SNR is improved 3.7-9.3 times compared to 855 nm and 6.0-33.5 times compared to 773 nm at TOFs of 800-1000 ps. Physical system parameters account for much of this improvement, but the tissue response may also play a role. We conclude that wavelengths near 1060 nm can potentially improve iNIRS measurements of TOF-resolved speckle fluctuations.

Beneath the surface: revealing deep-tissue blood flow in human subjects with massively parallelized diffuse correlation spectroscopy

Significance

Diffuse correlation spectroscopy (DCS) allows label-free, non-invasive investigation of microvascular dynamics deep within tissue, such as cerebral blood flow (CBF). However, the signal-to-noise ratio (SNR) in DCS limits its effective cerebral sensitivity in adults, in which the depth to the brain, through the scalp and skull, is substantially larger than in infants.

Aim

Therefore, we aim to increase its SNR and, ultimately, its sensitivity to CBF through new DCS techniques.

Approach

We present an in vivo demonstration of parallelized DCS (PDCS) to measure cerebral and muscular blood flow in healthy adults. Our setup employs an innovative array with hundreds of thousands single photon avalanche diodes (SPAD) in a 500 × 500 grid to boost SNR by averaging all independent pixel measurements. We tested this device on different total pixel counts and frame rates. A secondary, smaller array was used for reference measurements from shallower tissue at lower source-detector-separation (SDS).

Results

The new system can measure pulsatile blood flow in cerebral and muscular tissue, at up to 4 cm SDS, while maintaining a similar measurement noise as compared with a previously published 32 × 32 PDCS system at 1.5 cm SDS. Data from a cohort of 15 adults provide strong experimental evidence for functional CBF activity during a cognitive memory task and allowed analysis of pulse markers. Additional control experiments on muscular blood flow in the forearm with a different technical configuration provide converging evidence for the efficacy of this technique.

Conclusions

Our results outline successful PDCS measurements with large SPAD arrays to enable detect CBF in human adults. The ongoing development of SPAD camera technology is expected to result in larger and faster detectors in the future. In combination with new data processing techniques, tailored for the sparse signal of binary photon detection events in SPADs, this could lead to even greater SNR increase and ultimately greater depth sensitivity of PDCS.

Direct 3-D printing of complex optical phantoms using dynamic filament mixing

We report a method to directly 3-D print complex heterogeneous optical phantoms with programmable tissue-mimicking absorption and scattering properties. The proposed approach utilizes commercially available multi-color mixing extruders and off-the-shelf polylactic acid filaments, making this technique low-cost and broadly accessible. We systematically characterized optical properties, including both absorption and reduced scattering coefficients, at a wide range of mixing ratios of gray, white, and translucent filaments and validated our hypothesis of a linear-mixing model between the filament mixing ratios and the resulting optical properties. Various techniques were used to design and fabricate sophisticated solid phantoms, including the design of color-purging towers, and the optimization of several printing parameters to improve print quality. To demonstrate the feasibility of this technique for generating anatomically complex phantoms with tunable optical absorption and scattering properties within tissue-relevant ranges, we designed and fabricated three heterogeneous optical phantoms. One of the presented phantoms was specifically designed to support quality assurance efforts in evaluating diffuse optics instruments and methodologies across various institutions. We have characterized the printed phantoms and observed an average error between 12%-15% compared to our linear-mixing model-predicted values. Future studies will target the usage of additional filament materials to expand potential imaging applications.

Portable cerebral blood flow monitor to detect large vessel occlusion in patients with suspected stroke

BACKGROUND

Early detection of large vessel occlusion (LVO) facilitates triage to an appropriate stroke center to reduce treatment times and improve outcomes. Prehospital stroke scales are not sufficiently sensitive, so we investigated the ability of the portable Openwater optical blood flow monitor to detect LVO.

METHODS

Patients were prospectively enrolled at two comprehensive stroke centers during stroke alert evaluation within 24 hours of onset with National Institutes of Health Stroke Scale (NIHSS) score ≥2. A 70 s bedside optical blood flow scan generated cerebral blood flow waveforms based on relative changes in speckle contrast. Anterior circulation LVO was determined by CT angiography. A deep learning model trained on all patient data using fivefold cross-validation and learned discriminative representations from the raw speckle contrast waveform data. Receiver operating characteristic (ROC) analysis compared the Openwater diagnostic performance (ie, LVO detection) with prehospital stroke scales.

RESULTS

Among 135 patients, 52 (39%) had an anterior circulation LVO. The median NIHSS score was 8 (IQR 4-14). The Openwater instrument had 79% sensitivity and 84% specificity for the detection of LVO. The rapid arterial occlusion evaluation (RACE) scale had 60% sensitivity and 81% specificity and the Los Angeles motor scale (LAMS) had 50% sensitivity and 81% specificity. The binary Openwater classification (high-likelihood vs low-likelihood) had an area under the ROC (AUROC) of 0.82 (95% CI 0.75 to 0.88), which outperformed RACE (AUC 0.70; 95% CI 0.62 to 0.78; P=0.04) and LAMS (AUC 0.65; 95% CI 0.57 to 0.73; P=0.002).

CONCLUSIONS

The Openwater optical blood flow monitor outperformed prehospital stroke scales for the detection of LVO in patients undergoing acute stroke evaluation in the emergency department. These encouraging findings need to be validated in an independent test set and the prehospital environment.

Pathlength-selective, interferometric diffuse correlation spectroscopy

Diffuse correlation spectroscopy (DCS) is an optical method that offers non-invasive assessment of blood flow in tissue through the analysis of intensity fluctuations in diffusely backscattered coherent light. The non-invasive nature of DCS has enabled several clinical application areas for deep tissue blood flow measurements, including neuromonitoring, cancer imaging, and exercise physiology. While promising, in measurement configurations targeting deep tissue hemodynamics, standard DCS implementations suffer from insufficient signal-to-noise ratio (SNR), depth sensitivity, and sampling rate, limiting their utility. In this work, we present an enhanced DCS method called pathlength-selective, interferometric DCS (PaLS-iDCS), which uses pathlength-specific coherent gain to improve both the sensitivity to deep tissue hemodynamics and measurement SNR. Through interferometric detection, PaLS-iDCS can provide time-of-flight (ToF) specific blood flow information without the use of expensive time-tagging electronics and low-jitter detectors. The technique is compared to time-domain DCS (TD-DCS), another enhanced DCS method able to resolve photon ToF in tissue, through Monte Carlo simulation, phantom experiments, and human subject measurements. PaLS-iDCS consistently demonstrates improvements in SNR (>2x) for similar measurement conditions (same photon ToF), and the SNR improvements allow for measurements at extended photon ToFs, which have increased sensitivity to deep tissue hemodynamics (~50% increase). Further, like TD-DCS, PaLS-iDCS allows direct estimation of tissue optical properties from the sampled ToF distribution. This method offers a relatively straightforward way to allow DCS systems to make robust measurements of blood flow with greatly enhanced sensitivity to deep tissue hemodynamics without the need for time-resolved detection, enabling further applications of this non-invasive technology.

Electroconvulsive therapy generates a postictal wave of spreading depolarization in mice and humans

Electroconvulsive therapy (ECT) is a fast-acting, highly effective, and safe treatment for medication-resistant depression. Historically, the clinical benefits of ECT have been attributed to generating a controlled seizure; however, the underlying neurobiology is understudied and unresolved. Using optical neuroimaging of neural activity and hemodynamics in a mouse model of ECT, we demonstrated that a second brain event follows seizure: cortical spreading depolarization (CSD). We found that ECT pulse parameters and electrode configuration directly shaped the wave dynamics of seizure and subsequent CSD. To translate these findings to human patients, we used non-invasive diffuse optical monitoring of cerebral blood flow and oxygenation during routine ECT treatments. We observed that human brains reliably generate hyperemic waves after ECT seizure which are highly consistent with CSD. These results challenge a long-held assumption that seizure is the primary outcome of ECT and point to new opportunities for optimizing ECT stimulation parameters and treatment outcomes.

Relationship Between Signals from Cerebral near Infrared Spectroscopy Sensor Technology and Objectively Measured Cerebral Blood Volume: A Systematic Scoping Review

Cerebral blood volume (CBV) is an essential metric that indicates and evaluates various healthy and pathologic conditions. Most methods of CBV measurement are cumbersome and have a poor temporal resolution. Recently, it has been proposed that signals and derived metrics from cerebral near-infrared spectroscopy (NIRS), a non-invasive sensor, can be used to estimate CBV. However, this association remains vastly unexplored. As such, this scoping review aimed to examine the literature on the relationship between cerebral NIRS signals and CBV. A search of six databases was conducted conforming to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to assess the following search question: What are the associations between various NIRS cerebral signals and CBV? The database search yielded 3350 unique results. Seven of these articles were included in this review based on the inclusion and exclusion criteria. An additional study was identified and included while examining the articles' reference sections. Overall, the literature for this systematic scoping review shows extreme variation in the association between cerebral NIRS signals and CBV, with few sources objectively documenting a true statistical association between the two. This review highlights the current critical knowledge gap and emphasizes the need for further research in the area.

Fundamental effects of array density and modulation frequency on image quality of diffuse optical tomography

BACKGROUND

Diffuse optical tomography (DOT) provides three-dimensional image reconstruction of chromophore perturbations within a turbid volume. Two leading strategies to optimize DOT image quality include, (i) arrays of regular, interlacing, high-density (HD) grids of sources and detectors with closest spacing less than 15 mm, or (ii) source modulated light of order ∼100 MHz.

PURPOSE

However, the general principles for how these crucial design parameters of array density and modulation frequency may interact to provide an optimal system design have yet to be elucidated.

METHODS

Herein, we systematically evaluated how these design parameters effect image quality via multiple key metrics. Specifically, we simulated 32 system designs with realistic measurement noise and quantified localization error, spatial resolution, signal-to-noise, and localization depth of field for each of ∼85 000 point spread functions in each model.

RESULTS

We found that array density had a far stronger effect on image quality metrics than modulation frequency. Additionally, model fits for image quality metrics revealed that potential improvements diminish with regular arrays denser than 9 mm closest spacing. Further, for a given array density, 300 MHz source modulation provided the deepest reliable imaging compared to other frequencies.

CONCLUSIONS

Our results indicate that both array density and modulation frequency affect the spatial sampling of tissue, which asymptotically saturates due to photon diffusivity within a turbid volume. In summary, our results provide comprehensive perspectives for optimizing future DOT system designs in applications from wearable functional brain imaging to breast tumor detection.

Portable six-channel laser speckle system for simultaneous measurement of cerebral blood flow and volume with potential applications in characterization of brain injury

Significance

Cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics for regional cerebrovascular monitoring. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting.

Aim

We aim to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain.

Approach

The system is based on speckle contrast optical spectroscopy and consists of laser diodes and board cameras, which have been both tested and investigated for safe use on the human head. Apart from the universal serial bus connection for the camera, the entire system, including its battery power source, is integrated into a wearable headband and is powered by 9-V batteries.

Results

The temporal dynamics of both CBF and CBV in a cohort of five healthy subjects were synchronized and exhibited similar cardiac period waveforms across all six channels. The potential use of our six-channel system for detecting the physiological sequelae of brain injury was explored in two subjects, one with moderate and one with significant structural brain damage, where the six-point CBF and CBV measurements were referenced to structural magnetic resonance imaging (MRI) scans.

Conclusions

We pave the way for a viable multi-point optical instrument for measuring CBF and CBV. Its cost-effectiveness allows for baseline metrics to be established prior to injury in populations at risk for brain injury.

Fabrication of complex optical phantoms using on-the-fly multi-filament mixing 3-D printing

We report a method to directly 3-D print complex heterogeneous optical phantoms with programmable tissue-mimicking absorption and scattering properties. The proposed approach utilizes commercially available multi-color mixing extruders and off-the-shelf polylactic acid (PLA) filaments, making this technique low-cost and broadly accessible. We systematically characterized optical properties, including both absorption and reduced scattering coefficients, at a wide range of mixing ratios of gray, white and translucent filaments and validated our hypothesis of a linear-mixing model between the filament mixing ratios and the resulting optical properties. Various techniques were used to design and fabricate sophisticated solid phantoms, including the design of color-purging towers, and the optimization of several printing parameters to improve print quality. To demonstrate the feasibility of this technique for generating anatomically complex phantoms with tunable optical absorption and scattering properties within tissue-relevant ranges, we designed and fabricated three heterogeneous optical phantoms. One of the presented phantoms was specifically designed to support quality assurance efforts in evaluating diffuse optics instruments and methodologies across various institutions. We have characterized the printed phantoms and observed an average error between 12%-15% compared to our linear-mixing model predicted values.

Proof of concept validation of bioresorbable optical fibers for diffuse correlation spectroscopy

Optical quality bioresorbable materials have been gaining interest in recent years for various interstitial biomedical/medical application. An example of this is when the implant gradually dissolves in the body, providing physiological information over extended periods of time, hence reducing the need for revision surgeries. This study reports for the first time the in-house fabrication of single mode (at 785 nm) calcium phosphate glass (CPG) based bioresorbable optical fibers and investigates their suitability for microvascular blood flow monitoring using diffuse correlation spectroscopy (DCS). Ex vivo experiments in liquid phantom and non-invasive in vivo experiments on the human forearm muscle were conducted using multimode and single mode CPG bioresorbable optical fibers. The retrieved flow index from the correlation curves acquired using CPG fibers was in good agreement with that obtained using standard silica (Si) fibers, both ex vivo and in vivo. The results demonstrate the potential of CPG optical fibers for further exploration.

Portable Six-Channel Laser Speckle System for Simultaneous Cerebral Blood Flow and Volume Measurement with Potential Application for Characterization of Brain Injury

In regional cerebrovascular monitoring, cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection, as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting. This study's aim is to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain. The system is based on speckle contrast optical spectroscopy (SCOS) and consists of laser diodes and board cameras which have been both tested and investigated for safe use on the human head. Results on a cohort of five healthy subjects indicated that the dynamics of both CBF and CBV were synchronized and exhibited similar cardiac period waveforms across all six channels. As a preliminary investigation, we also explored the potential use of our six-channel system for detecting the physiological sequela of brain injury, involving a subject with significant structural brain damage compared to another with lesser structural brain damage. The six-point CBF and CBV measurements were compared to MRI scans, revealing that regions with altered blood dynamics closely correlated with the injury sites identified by MRI.

ATLAS: a large array, on-chip compute SPAD camera for multispeckle diffuse correlation spectroscopy

We present ATLAS, a 512 × 512 single-photon avalanche diode (SPAD) array with embedded autocorrelation computation, implemented in 3D-stacked CMOS technology, suitable for single-photon correlation spectroscopy applications, including diffuse correlation spectroscopy (DCS). The shared per-macropixel SRAM architecture provides a 128 × 128 macropixel resolution, with parallel autocorrelation computation, with a minimum autocorrelation lag-time of 1 µs. We demonstrate the direct, on-chip computation of the autocorrelation function of the sensor, and its capability to resolve changes in decorrelation times typical of body tissue in real time, at long source-detector separations similar to those achieved by the current leading optical modalities for cerebral blood flow monitoring. Finally, we demonstrate the suitability for in-vivo measurements through cuff-occlusion and forehead cardiac signal measurements.

Towards high-performance deep learning architecture and hardware accelerator design for robust analysis in diffuse correlation spectroscopy

This study proposes a compact deep learning (DL) architecture and a highly parallelized computing hardware platform to reconstruct the blood flow index (BFi) in diffuse correlation spectroscopy (DCS). We leveraged a rigorous analytical model to generate autocorrelation functions (ACFs) to train the DL network. We assessed the accuracy of the proposed DL using simulated and milk phantom data. Compared to convolutional neural networks (CNN), our lightweight DL architecture achieves 66.7% and 18.5% improvement in MSE for BFi and the coherence factor β, using synthetic data evaluation. The accuracy of rBFi over different algorithms was also investigated. We further simplified the DL computing primitives using subtraction for feature extraction, considering further hardware implementation. We extensively explored computing parallelism and fixed-point quantization within the DL architecture. With the DL model's compact size, we employed unrolling and pipelining optimizations for computation-intensive for-loops in the DL model while storing all learned parameters in on-chip BRAMs. We also achieved pixel-wise parallelism, enabling simultaneous, real-time processing of 10 and 15 autocorrelation functions on Zynq-7000 and Zynq-UltraScale+ field programmable gate array (FPGA), respectively. Unlike existing FPGA accelerators that produce BFi and the β from autocorrelation functions on standalone hardware, our approach is an encapsulated, end-to-end on-chip conversion process from intensity photon data to the temporal intensity ACF and subsequently reconstructing BFi and β. This hardware platform achieves an on-chip solution to replace post-processing and miniaturize modern DCS systems that use single-photon cameras. We also comprehensively compared the computational efficiency of our FPGA accelerator to CPU and GPU solutions.

Lawrence K. All-optics technique for monitoring absolute cerebral blood flow: validation against magnetic resonance imaging perfusion

Significance

The ability to monitor cerebral blood flow (CBF) at the bedside is essential to managing critical-care patients with neurological emergencies. Diffuse correlation spectroscopy (DCS) is ideal because it is non-invasive, portable, and inexpensive. We investigated a near-infrared spectroscopy (NIRS) approach for converting DCS measurements into physiological units of blood flow.

Aim

Using magnetic resonance imaging perfusion as a reference, we investigated the accuracy of absolute CBF measurements from a bolus-tracking NIRS method that used transient hypoxia as a flow tracer and hypercapnia-induced increases in CBF measured by DCS.

Approach

Twelve participants (7 female, 28 ± 6 years) completed a hypercapnia protocol with simultaneous CBF recordings from DCS and arterial spin labeling (ASL). Nine participants completed the transient hypoxia protocol while instrumented with time-resolved NIRS. The estimate of baseline CBF was subsequently used to calibrate hypercapnic DCS data.

Results

Moderately strong correlations at baseline ( slope = 0.79 andR 2 = 0.59 ) and during hypercapnia ( slope = 0.90 andR 2 = 0.58 ) were found between CBF values from calibrated DCS and ASL (range 34 to 85    mL / 100    g / min ).

Conclusions

Results demonstrated the feasibility of an all-optics approach that can both quantify CBF and perform continuous perfusion monitoring.

How the heterogeneity of the severely injured brain affects hybrid diffuse optical signals: case examples and guidelines

Significance

A shortcoming of the routine clinical use of diffuse optics (DO) in the injured head has been that the results from commercial near-infrared spectroscopy-based devices are not reproducible, often give physiologically invalid values, and differ among systems. Besides the limitations due to the physics of continuous-wave light sources, one culprit is the head heterogeneity and the underlying morphological and functional abnormalities of the probed tissue.

Aim

The aim is to investigate the effect that different tissue alterations in the damaged head have on DO signals and provide guidelines to avoid data misinterpretation.

Approach

DO measurements and computed tomography scans were acquired on brain-injured patients. The relationship between the signals and the underlying tissue types was classified on a case-by-case basis.

Results

Examples and suggestions to establish quality control routines were provided. The findings suggested guidelines for carrying out DO measurements and speculations toward improved devices.

Conclusions

We advocate for the standardization of the DO measurements to secure a role for DO in neurocritical care. We suggest that blind measurements are unacceptably problematic due to confounding effects and care using a priori and a posteriori quality control routines that go beyond an assessment of the signal-to-noise ratio that is typically utilized.

Correlating stroke risk with non-invasive cerebrovascular perfusion dynamics using a portable speckle contrast optical spectroscopy laser device

Stroke poses a significant global health threat, with millions affected annually, leading to substantial morbidity and mortality. Current stroke risk assessment for the general population relies on markers such as demographics, blood tests, and comorbidities. A minimally invasive, clinically scalable, and cost-effective way to directly measure cerebral blood flow presents an opportunity. This opportunity has the potential to positively impact effective stroke risk assessment prevention and intervention. Physiological changes in the cerebrovascular system, particularly in response to hypercapnia and hypoxia during voluntary breath-holding can offer insights into stroke risk assessment. However, existing methods for measuring cerebral perfusion reserves, such as blood flow and blood volume changes, are limited by either invasiveness or impracticality. Herein we propose a non-invasive transcranial approach using speckle contrast optical spectroscopy (SCOS) to non-invasively monitor regional changes in brain blood flow and volume during breath-holding. Our study, conducted on 50 individuals classified into two groups (low-risk and higher-risk for stroke), shows significant differences in blood dynamic changes during breath-holding between the two groups, providing physiological insights for stroke risk assessment using a non-invasive quantification paradigm. Given its cost-effectiveness, scalability, portability, and simplicity, this laser-centric tool has significant potential for early diagnosis and treatment of stroke in the general population.

Acoustomotive diffuse correlation spectroscopy for sensing mechanical stiffness in tissue-mimicking phantoms

Many diseases, such as inflammation, dropsy, or tumors, often cause alterations in the mechanical stiffness of human tissues. Ultrasound-based techniques are commonly adopted in clinics for stiffness assessment, whereas optical methodologies hold promise for sensing strain changes and providing optical information pertaining to the microcirculatory network, thereby facilitating comprehensive measurements of tissue physiopathology. Diffuse correlation spectroscopy (DCS), an emerging dynamic light scattering technique, has been used to capture the enhanced motion of light scatterers induced by acoustic radiation force (ARF). Theoretically, the amplitude of this enhanced scatterers motion is related to the medium stiffness. Based on this relationship, we report a light coherent technique that combines ARF and DCS to qualitatively evaluate changes in the stiffness of medium. We experimentally demonstrate the accuracy and feasibility of this technique for probing stiffness in homogeneous phantom by comparing it with independent ultrasound methods. Additionally, we explore a potential application of this technique in distinguishing between fluid filled lesion and homogeneous tissue through heterogeneous phantom experiments. This unique combination of ARF and DCS, namely, acoustomotive DCS (AM-DCS), would provide an alternative way to measure particle-motion related stiffness, thereby assisting in the diagnosis and treatment of diseases.

A comprehensive overview of diffuse correlation spectroscopy: Theoretical framework, recent advances in hardware, analysis, and applications

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Modified Beer-Lambert algorithm to measure pulsatile blood flow, critical closing pressure, and intracranial hypertension

We introduce a frequency-domain modified Beer-Lambert algorithm for diffuse correlation spectroscopy to non-invasively measure flow pulsatility and thus critical closing pressure (CrCP). Using the same optical measurements, CrCP was obtained with the new algorithm and with traditional nonlinear diffusion fitting. Results were compared to invasive determination of intracranial pressure (ICP) in piglets (n = 18). The new algorithm better predicted ICP elevations; the area under curve (AUC) from logistic regression analysis was 0.85 for ICP ≥ 20 mmHg. The corresponding AUC for traditional analysis was 0.60. Improved diagnostic performance likely results from better filtering of extra-cerebral tissue contamination and measurement noise.

Compact and cost-effective laser-powered speckle contrast optical spectroscopy fiber-free device for measuring cerebral blood flow

Significance

In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF noninvasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain.

Aim

Our study aims to introduce a compact speckle contrast optical spectroscopy device for noninvasive CBF measurements at long source-to-detector distances, offering cost-effectiveness, and scalability while tracking blood flow (BF) with remarkable sensitivity and temporal resolution.

Approach

The wearable sensor module consists solely of a laser diode and a board camera. It can be easily placed on a subject's head to measure BF at a sampling rate of 80 Hz.

Results

Compared to the single-fiber-based version, the proposed device achieved a signal gain of about 70 times, showed superior stability, reproducibility, and signal-to-noise ratio for measuring BF at long source-to-detector distances. The device can be distributed in multiple configurations around the head.

Conclusions

Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing noninvasive cerebral monitoring technologies.

Dynamic Light Scattering in Biomedical Applications: feature issue introduction

The feature Issue on "Dynamic Light Scattering in Biomedical Applications" presents a compilation of research breakthroughs and technological advancements that have shaped the field of biophotonics, particularly in the non-invasive exploration of biological tissues. Highlighting the significance of dynamic light scattering (DLS) alongside techniques like laser Doppler flowmetry (LDF), diffusing wave spectroscopy (DWS), and laser speckle contrast imaging (LSCI), this issue underscores the versatile applications of these methods in capturing the intricate dynamics of microcirculatory blood flow across various tissues. Contributions explore developments in fluorescence tomography, the integration of machine learning for data processing, enhancements in microscopy for cancer detection, and novel approaches in optical biophysics, among others. Innovations featured include a high-resolution speckle contrast tomography system for deep blood flow imaging, a rapid estimation technique for real-time tissue perfusion imaging, and the use of convolutional neural networks for efficient blood flow mapping. Additionally, studies delve into the impact of skin strain on spectral reflectance, the sensitivity of cerebral blood flow measurement techniques, and the potential of photobiomodulation for enhancing brain function. This issue not only showcases the latest theoretical and experimental strides in DLS-based imaging but also anticipates the continued evolution of these modalities for groundbreaking applications in disease detection, diagnosis, and monitoring, marking a pivotal contribution to the field of biomedical optics.

Muscle Oximetry in Sports Science: An Updated Systematic Review

BACKGROUND

In the last 5 years since our last systematic review, a significant number of articles have been published on the technical aspects of muscle near-infrared spectroscopy (NIRS), the interpretation of the signals and the benefits of using the NIRS technique to measure the physiological status of muscles and to determine the workload of working muscles.

OBJECTIVES

Considering the consistent number of studies on the application of muscle oximetry in sports science published over the last 5 years, the objectives of this updated systematic review were to highlight the applications of muscle oximetry in the assessment of skeletal muscle oxidative performance in sports activities and to emphasize how this technology has been applied to exercise and training over the last 5 years. In addition, some recent instrumental developments will be briefly summarized.

METHODS

Preferred Reporting Items for Systematic Reviews guidelines were followed in a systematic fashion to search, appraise and synthesize existing literature on this topic. Electronic databases such as Scopus, MEDLINE/PubMed and SPORTDiscus were searched from March 2017 up to March 2023. Potential inclusions were screened against eligibility criteria relating to recreationally trained to elite athletes, with or without training programmes, who must have assessed physiological variables monitored by commercial oximeters or NIRS instrumentation.

RESULTS

Of the identified records, 191 studies regrouping 3435 participants, met the eligibility criteria. This systematic review highlighted a number of key findings in 37 domains of sport activities. Overall, NIRS information can be used as a meaningful marker of skeletal muscle oxidative capacity and can become one of the primary monitoring tools in practice in conjunction with, or in comparison with, heart rate or mechanical power indices in diverse exercise contexts and across different types of training and interventions.

CONCLUSIONS

Although the feasibility and success of the use of muscle oximetry in sports science is well documented, there is still a need for further instrumental development to overcome current instrumental limitations. Longitudinal studies are urgently needed to strengthen the benefits of using muscle oximetry in sports science.

A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow

In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on a subject's head to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies.

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.

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.

Diffuse Correlation Spectroscopy: A Review of Recent Advances in Parallelisation and Depth Discrimination Techniques

Diffuse correlation spectroscopy is a non-invasive optical modality used to measure cerebral blood flow in real time, and it has important potential applications in clinical monitoring and neuroscience. As such, many research groups have recently been investigating methods to improve the signal-to-noise ratio, imaging depth, and spatial resolution of diffuse correlation spectroscopy. Such methods have included multispeckle, long wavelength, interferometric, depth discrimination, time-of-flight resolution, and acousto-optic detection strategies. In this review, we exhaustively appraise this plethora of recent advances, which can be used to assess limitations and guide innovation for future implementations of diffuse correlation spectroscopy that will harness technological improvements in the years to come.

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.

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

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. Here we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics. 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 the changes in speckle contrast, and relative blood volume (rBV) was derived from the changes in speckle average intensity. 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 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:0.17-0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics. 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.