Diffuse correlation spectroscopy (DCS) is an optical technique that allows for non-invasive measurements of tissue perfusion, and is often used for neuromonitoring applications. However, a major challenge of DCS is low SNR for deep tissue measurements. Recent works have demonstrated the potential for SPAD arrays to provide significant SNR increases by averaging autocorrelation signals from individual speckles. Such methods may still be suboptimal for efficient signal extraction, as the individual signals may each be low fidelity. In this work, we explore alternative methods of integrating parallelized DCS signals in low photon regimes for accurate blood flow estimation.
Functional near-infrared spectroscopy (fNIRS) and diffuse correlation spectroscopy (DCS) have shown promise as non-invasive optical methods for cerebral functional imaging. Both approaches currently have limits to sensitivity in adults. Sensitivity can be improved using temporal discrimination, where the laser excitation is of short (~400ps) duration and the detector rejects early photons that have not penetrated into the brain while maintain high sensitivity to those that have. We report here further demonstration of a high-speed Read-Out Integrated Circuit (ROIC) that integrates with a 32x32 Single-Photon Avalanche photo-Detector (SPAD) array that can be either silicon (Si, for visible to infra-red) in indium-phosphide (InP, to allow operation at 1064nm). Data is exfiltrated serially directly to an FPGA where it can be processed in real time. This presentation will include results of recent detector performance tests and phantom demonstrations using this powerful new tool.
Diffuse correlation spectroscopy (DCS) is an optical technique which is used to estimate blood flow in tissue through the analysis of the temporal fluctuations in light intensity. Recently, the development of interferometric techniques (iDCS/iDWS), have allowed for drastic improvement in measurement SNR. In this work, we build upon the iDCS technique by combining it with another advanced DCS modality, time-domain DCS (TD-DCS). This combination allows for the application of pathlength specific coherent gain, which has the potential to further improve the performance of DCS in the non-invasive measurement of deep tissue blood flow.
Interferometric diffuse correlation spectroscopy (iDCS) is an emerging technique that enables high quality measurements of cerebral blood flow. By including a reference arm in the optical setup, the SNR of the measured signals are improved relative to traditional DCS. We report here an expansion of our previously demonstrated 1064 nm single channel line scan camera based iDCS system to a multi-source, multiple detection channel approach to enable imaging of the brain perfusion response to functional activation. We confirm the ability to image multiple detectors on a single camera with minimal cross-talk using phantom experiments and show initial functional imaging results.
Recently we developed the open-source FlexNIRS: a battery-operated, wireless, wearable oximeter whose self-calibrating geometry allows measurements of oxygen saturation in tissue. The first implementation of the device operating at 100 Hz has been validated and is enrolled in several measurement campaigns across different research laboratories. A recent firmware upgrade provides 266 Hz sampling rate, and hardware modifications provide improved form factor, wearability, and multi-modal acquisition. The new version is currently adopted in multiple clinical measurement campaigns focusing on pulsatile component analysis. We will present the instrument performance, its recent and future upgrades, and the applications where the device is currently in use.
Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) noninvasively with high signal-to-noise ratio (SNR). A noise correction procedure has previously been developed to improve SCOS measurement accuracy, which requires precise characterization of camera properties. Here, we provide guidance on choosing and characterizing a camera for SCOS, considering factors such as linearity, read noise, and gain. We then validate a noise-corrected SCOS measurement of flow changes in a liquid phantom against diffuse correlation spectroscopy (DCS).
KEYWORDS: Speckle, Monte Carlo methods, Sensors, Cameras, Pulsed laser operation, Light sources and illumination, Neurophotonics, Tissues, Signal to noise ratio, Cerebral blood flow
SignificanceThe 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.AimWe systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow.ApproachMonte 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.ResultsThrough 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.ConclusionWe provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.
SignificanceCombining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index (pCBFi) can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance (CVRi).AimAlthough current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source–detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform.ApproachTaking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS pCBFi, reducing the coefficient of variation of the recovered pulsatile waveform (pCBFi-fit) and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation (>3 cm).ResultsIn 10 healthy subjects, we verified the quality of the NIRS-PPG pCBFi-fit during common tasks, showing high fidelity against pCBFi (R2 0.98 ± 0.01). We recovered CrCP and CVRi at 0.25 Hz, >10 times faster than previously achieved with DCS.ConclusionsNIRS-PPG improves DCS pCBFi SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and CVRi.
Functional near-infrared spectroscopy (fNIRS) and diffuse correlation spectroscopy (DCS) have shown promise as non-invasive optical methods for cerebral functional imaging. DCS approaches currently have limited sensitivity in adults. fNIRS sensitivity is also limited, particularly in high-detector-density applications. Sensitivity can be improved using temporal discrimination (TD), where the laser excitation is of short (~400ps) duration and the detector rejects early photons that have not penetrated into the brain while maintain high sensitivity to those that have. We report here on the development of a novel 32x32 Single-Photon Avalanche photo-Detector (SPAD) array and Read-Out Integrated Circuit (ROIC) that can operate in either the visible or NIR enabling high-channel-count TD-fNIRS or TD-DCS systems.
Transcatheter aortic valve replacement (TAVR) surgery has a risk of cognitive impairment and neurological injury. Currently, there are few options for non-invasively monitoring brain activity and perfusion, with electroencephalography, transcranial Doppler, and near-infrared spectroscopy (NIRS) all having significant drawbacks. By combining NIRS with diffuse correlation spectroscopy (DCS) we can obtain a more complete picture of cerebral hemodynamics during TAVR procedures and examine the link to neurological outcomes. We show examples of post-valve replacement hemodynamic changes that correspond with worse/better patient outcomes
KEYWORDS: Speckle, Brain, Spectroscopy, Optical spectroscopy, Signal to noise ratio, Tissue optics, Skull, Monte Carlo methods, Laser speckle contrast imaging, Human subjects
Diffuse correlation spectroscopy (DCS) offers non-invasive measurements of tissue perfusion and is increasingly broadly applied in human subject research, in particular in the neuromonitoring arena. However, signal to noise (SNR) limitations have prompted great interest in alternative instrumentation approaches to address this issue, such as the speckle contrast optical spectroscopy (SCOS) technique which uses spatial multi-speckle contrast to estimate blood flow. Here we present a simulation study of the brain perfusion sensitivity achievable by each method on adults, to guide the use of SCOS vs DCS approaches in future studies. We find that SCOS brain sensitivity is comparable to DCS.
We present a novel system based on a four-stage fiber delay network designed for multistate time-domain diffuse correlation spectroscopy, providing three output fibers per each delay state. The fiber delay network is coupled to a custom pulsed laser at 1064 nm and four SNSPDs, allowing to measure up to 12 independent source-detector pairs simultaneously. The system delivers 300ps optical pulses, 100 mW average optical power per fiber output, operates at 62.5 MHz and each cycle provides 4 laser pulses displaced of 4 ns. The instrument has been validated on healthy human subject during functional tasks, proving state-of-the-art performance.
Infants born at an extremely low gestational age are at an increased risk of intraventricular hemorrhaging during the first three postnatal days. We have built a standalone easy-to-use multi-wavelength multi-distance diffuse correlation spectroscopy system, which utilizes three time-multiplexed long coherence lasers at 785, 808, and 853 nm, single photon detectors, and photon time-tagging electronics to simultaneously quantify cerebral blood flow, tissue optical properties, and blood oxygen saturation. The system has been designed specifically for use on preterm infants. The device shows good agreement with a commercially available NIRS-DCS system. We are currently monitoring preterm infants and will show results.
KEYWORDS: Signal to noise ratio, Spectroscopy, Brain, Tissues, Near infrared spectroscopy, Source detector separation, Autocorrelation, Signal detection, Monte Carlo methods, Magnetic resonance imaging
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.
Diffuse correlation spectroscopy (DCS) is an emerging near infrared spectroscopy modality able to measure cerebral blood flow (CBF) non-invasively and continuously in humans. We have reported a limited applicability in adults due to the significant extracerebral tissue thickness and the low signal-to-noise ratio (SNR) of the measurements. Improvements to DCS brain sensitivity and SNR can be achieved by operating DCS at 1064 and using superconducting nanowire single-photon detectors (SNSPDs). Initial human results show a 16-fold improvement in SNR and 20% improvement in depth sensitivity. This allows us to resolve changes in CBF in adult subjects more robustly and accurately than was previously achievable.
We present the design of an innovative time-gated 32×32 InP/InGaAs-based Single Photon Avalanche Diode (SPAD) array with sub-nanosecond gating capabilities operating up to 10MHz repetition rate specifically designed for time-domain diffuse correlation spectroscopy at 1064nm. We present the detector design, experimental characterization and preliminary validations on a liquid phantom. This testing is informing us for a revision of the photodetector which will allow to reach up to 192 optical channels towards functional blood flow changes measurements with full head coverage with improved brain sensitivity thanks to early-photons rejection.
We present the design of an innovative instrument for time-gated diffuse correlation spectroscopy. It features a 1064nm pulsed sub-ns long coherence-length laser operating up to 75MHz, a 100-channel in-FPGA correlator and a novel time-gated 32×32 InP/InGaAs-based Single Photon Avalanche Diode (SPAD) array with sub-nanosecond gating capabilities operating up to 10MHz repetition rate. We present components experimental characterization and preliminary validations on a liquid phantom. This testing is informing us for a revision of the photodetector which will allow to reach up to 192 optical channels towards functional blood flow changes measurements with full head coverage.
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.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. DCS cerebral blood flow measurements in clinical applications have shown promise, but measurements contain contamination of the signal from changes in superficial blood flow. Recent studies have shown that moving to wavelengths beyond the water absorption peak at 970 nm when making DCS measurements improves SNR and reduced influence of superficial flow. Here, we present a DCS system operating at 1064 nm utilizing two InGaAs SPADs to calculate the cross correlation to address detector non-idealities.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. Recent advances in the field have seen the introduction of iDWS/iDCS, which have allowed for the use of conventional photodetectors to replace the single photon counting detectors required to measure the traditional, homodyne DCS signal. Here we detail a high framerate, highly parallel iDCS system at 1064 nm which allows for improved signal to noise ratio at extended source detector separations.
Recently, we developed a time-domain diffuse correlation spectroscopy (TD-DCS) method for neurovascular sensing with higher brain sensitivity. In this paper, laser pulse shaping was designed and demonstrated for TD-DCS at 1064 nm. A quantum superconducting nanowire single-photon detector (SNSPD) with high photon detection efficiency (PDE) and low jitter collects the back-scattered light from the brain. The presented approach is the first step towards scaling up a full fiber optic cap with 96 source channels and 192 custom-made single-photon detectors which will cover most of an adult head.
Significance: The use of diffuse correlation spectroscopy (DCS) has shown efficacy in research studies as a technique capable of noninvasively monitoring blood flow in tissue with applications in neuromonitoring, exercise science, and breast cancer management. The ability of DCS to resolve blood flow in these tissues is related to the optical sensitivity and signal-to-noise ratio (SNR) of the measurements, which in some cases, particularly adult cerebral blood flow measurements, is inadequate in a significant portion of the population. Improvements to DCS sensitivity and SNR could allow for greater clinical translation of this technique.
Aim: Interferometric diffuse correlation spectroscopy (iDCS) was characterized and compared to traditional homodyne DCS to determine possible benefits of utilizing heterodyne detection.
Approach: An iDCS system was constructed by modifying a homodyne DCS system with fused fiber couplers to create a Mach–Zehnder interferometer. Comparisons between homodyne and heterodyne detection were performed using an intralipid phantom characterized at two extended source–detector separations (2.4, 3.6 cm), different photon count rates, and a range of reference arm power levels. Characterization of the iDCS signal mixing was compared to theory. Precision of the estimation of the diffusion coefficient and SNR of the autocorrelation curve were compared between different measurement conditions that mimicked what would be seen in vivo.
Results: The mixture of signals present in the heterodyne autocorrelation function was found to agree with the derived theory and resulted in accurate measurement of the diffusion coefficient of the phantom. Improvement of the SNR of the autocorrelation curve up to ∼2 × and up to 80% reduction in the variability of the diffusion coefficient fit were observed for all measurement cases as a function of increased reference arm power.
Conclusions: iDCS has the potential to improve characterization of blood flow in tissue at extended source–detector separations, enhancing depth sensitivity and SNR.
KEYWORDS: Blood circulation, Absorption, Scattering, Signal to noise ratio, Tissue optics, Near infrared spectroscopy, Spectroscopy, Tissues, Signal attenuation, Sensors
Significance: Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths (>1000 nm) for the DCS measurement due to a variety of biophysical and regulatory factors.
Aim: We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations.
Approach: We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers.
Results: DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source–detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS.
Conclusions: DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. As a non-invasive technique, DCS has been used to monitor patient cerebral blood flow at the bedside. Though an effective measurement tool, extra-cerebral contamination of the DCS signal limits the sensitivity to changes in brain blood flow. In order to overcome this depth sensitivity challenge, we present a method, overlapping volumes, acousto-optic modulated DCS (AOM-DCS), to improve sensitivity to deeper tissue structures.
KEYWORDS: Photons, Blood, Liver, Tissue optics, Signal to noise ratio, Tissues, Monte Carlo methods, Near infrared spectroscopy, Computer simulations, Picosecond phenomena
Time-domain near-infrared spectroscopy (TD-NIRs) and Time-Domain Diffuse Correlation Spectroscopy (TD-DCS) are emerging imaging techniques that use a near-infrared, long coherence, pulsed laser to characterize oxygenation levels and blood flow. TD-DCS is a promising tool for bedside monitoring of brain activity due to its high time-resolution and portability. One potential new application area for TD-DCS is for detecting non-compressible torso hemorrhages (NCTH). NCTH is a serious traumatic injury that requires surgical intervention and is a leading cause of death in the military due to the lack of a rapid and portable imaging system sensitive enough to detect injury. Applying long wavelengths (1064 nm and 1120 nm) and time gating, TD-DCS can penetrate the superficial tissue layers and potentially detect bleeding deep within an organ. One limitation of current time-gating system is its reliance on full knowledge of the target tissue layers and properties in order to apply gating effectively. An automatic gating scheme that can adjust the time gate to quickly recalibrate itself to different imaging conditions, such as a different body area, can eliminate this limitation. Here, we use modeling and Monte Carlo simulations to search for characteristics in return signal profiles, specifically the time-of-flight and intensity profiles, as first step toward an automatic time-gating algorithm. We detail the simulation setups, parameter sweeps, and preliminary results in this report. These results show promise for TD-DCS as a tool for rapid and continuous monitoring of injuries in the field.
Diffuse correlation spectroscopy (DCS) is an established diffuse optical technique that uses the analysis of temporal speckle intensity fluctuations to measure blood flow in tissue. DCS has been shown to be an effective monitor of cerebral blood flow in many neuro-monitoring applications, though still suffers from depth sensitivity issues. Recent studies have shown that moving to 1064 nm when making DCS measurements improves SNR and sensitivity to depth, but detector challenges have slowed the change to that wavelength. Here, we present on a multipixel, interferometric DCS (iDCS) system that improves measurement capabilities at this wavelength.
Our team has recently shown the SNR and depth-sensitivity advantages of using 1064 nm light for diffuse correlation spectroscopy as well as the challenges of commercially available single-photon detectors at this wavelength. We will review two strategies for custom readout integrated circuit designs that simultaneously target lower pixel dead times and lower afterpulsing probabilities. Both designs use macropixels comprising many detectors, each having a programmable hold-off time. We will compare simulated autocorrelations for our detector models and compare predicted performance against commercial InGaAs/InP detectors.
Diffuse correlation spectroscopy (DCS) is an emerging technology that allows for the quantitative estimation of blood flow in tissue. By monitoring the autocorrelation of the time course of light speckle intensity, information about the motion of scattering particles, mostly red blood cells in the microvasculature of biological tissues, can be determined. The speckle fluctuations are due to motion of scatters along the entire path length of the photon from the source to the detector, which makes the determination of the location of the motion a difficult task. Multi-distance and tomographic methods have been employed to measure decorrelation times at different source detector separations, which helps to separate superficial blood flow from blood flow deeper in the tissue. DCS in the time-domain (TD-DCS) is being evaluated as a method to increase depth sensitivity by considering only the late arriving photons. Depth resolved quantification of blood flow is especially important when blood flow measurements of the brain are desired, as the superficial blood flow of the scalp is a known contaminant to the cortical signal. Recent demonstrations by other groups have shown the utility of ultrasound tagging of light to be an effective method to discriminate flow at different depths.1 Here we utilize ultrasound pulses to modulate the motion of particles at specific depths, which is dependent upon the time-of-flight of the ultrasound pulse. By analyzing the autocorrelation of the speckle intensity at different delay periods after the pulse, quantitative, depth specific information about the flow can be determined.
References:
1. Tsalach, A. et al. Depth selective acousto-optic flow measurement. Biomed. Opt. Express 6, 4871–86 (2015).
Diffuse correlation spectroscopy (DCS) is an emerging technique that allows for estimation of the motion of particles. By monitoring the time course of the speckle intensity fluctuations, the motion of the scattering particles, usually red blood cells in the microvasculature of biological tissues, can be quantified. Though these measurements are traditionally taken at near infrared wavelengths, where the attenuation of light by tissue chromophores, primarily hemoglobin, is reduced, the multiply scattered field is still heavily attenuated and expensive photon counting detectors are required to measure the signal intensity. By decreasing the cost of these systems, they may be more applicable in measuring patient hemodynamics at the bedside. Other groups have explored the use of heterodyne techniques [1,2] to amplify the intensity of the scattered field for detection with less expensive detectors, showing the potential for lowering the cost of DCS systems. Here we detail the performance characteristics of a single mode fiber (SMF) interferometer as well as follow through to investigate the theoretical relationship between the measured correlation function and the underlying dynamics. DCS measurements in the traditional homodyne configuration made with photon counting detectors are compared with those made with the interferometer with the photon counting detectors to explore experimental parameters that optimize the SNR of the blood flow index. The feasibility of utilizing fast photodiodes in the detection of the amplified field is also explored. Through the use of amplified optical signals, the detection of the DCS signal using less expensive detectors is shown to be possible.
References:
1. Nakaji, H. US Application. No. 15/424581 (2017).
2. Zhou, W., Kholiqov, O., Chong, S. P. & Srinivasan, V. J. Highly parallel, interferometric diffusing wave spectroscopy for monitoring cerebral blood flow dynamics. Optica 5, 518 (2018).
Traumatic injury resulting in hemorrhage is a prevalent cause of death worldwide. The current standard of care for trauma patients is to restore hemostasis by controlling bleeding and administering intravenous volume resuscitation. Adequate resuscitation to restore tissue blood flow and oxygenation is critical within the first hours following admission to assess severity and avoid complications. However, current clinical methods for guiding resuscitation are not sensitive or specific enough to adequately understand the patient condition. To better address the shortcomings of the current methods, an approach to monitor intestinal perfusion and oxygenation using a multiwavelength (470, 560, and 630 nm) optical sensor has been developed based on photoplethysmography and reflectance spectroscopy. Specifically, two sensors were developed using three wavelengths to measure relative changes in the small intestine. Using vessel occlusion, systemic changes in oxygenation input, and induction of hemorrhagic shock, the capabilities and sensitivity of the sensor were explored in vivo. Pulsatile and nonpulsatile components of the red, blue, and green wavelength signals were analyzed for all three protocols (occlusion, systemic oxygenation changes, and shock) and were shown to differentiate perfusion and oxygenation changes in the jejunum. The blue and green signals produced better correlation to perfusion changes during occlusion and shock, while the red and blue signals, using a new correlation algorithm, produced better data for assessing changes in oxygenation induced both systemically and locally during shock. The conventional modulation ratio method was found to be an ineffective measure of oxygenation in the intestine due to noise and an algorithm was developed based on the Pearson correlation coefficient. The method utilized the difference in phase between two different wavelength signals to assess oxygen content. A combination of measures from the three wavelengths provided verification of oxygenation and perfusion states, and showed promise for the development of a clinical monitor.
Monte Carlo modeling of photon propagation has been used in the examination of particular areas of the body to further enhance the understanding of light propagation through tissue. This work seeks to improve upon the established simulation methods through more accurate representations of the simulated tissues in the wrist as well as the characteristics of the light source. The Monte Carlo simulation program was developed using Matlab. Generation of different tissue domains, such as muscle, vasculature, and bone, was performed in Solidworks, where each domain was saved as a separate .stl file that was read into the program. The light source was altered to give considerations to both viewing angle of the simulated LED as well as the nominal diameter of the source. It is believed that the use of these more accurate models generates results that more closely match those seen in-vivo, and can be used to better guide the design of optical wrist-worn measurement devices.
From the miniaturization of large sample processing machines to the creation of handheld point-of-care devices, microfluidics has the potential to be a powerful tool in the advancement of diagnostic technologies. Here, we compare different prototyping modalities towards the generation of an inertial microfluidic blood filter: i.e. a 'centrifuge-on-a-chip'. While photolithography is currently the method of choice for soft lithography mold fabrication, offering high design fidelity, we believe simpler methods, such as milling or 3D printing, will soon become equally viable options in the field of microfluidic device fabrication. Three modalities for optofluidic PDMS chip fabrication were compared: micromachining, 3D printing, and SU8 photolithography. The filtration efficiency of the chips were tested with whole blood and compared spectroscopically by monitoring the outlet absorbance at the 540 nm peak intrinsic to oxyhemoglobin at the outlet of each filter chip.
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