Significance: Time domain diffuse correlation spectroscopy (TD-DCS) can offer increased sensitivity to cerebral hemodynamics and reduced contamination from extracerebral layers by differentiating photons based on their travel time in tissue. We have developed rigorous simulation and evaluation procedures to determine the optimal time gate parameters for monitoring cerebral perfusion considering instrumentation characteristics and realistic measurement noise.
Aim: We simulate TD-DCS cerebral perfusion monitoring performance for different instrument response functions (IRFs) in the presence of realistic experimental noise and evaluate metrics of sensitivity to brain blood flow, signal-to-noise ratio (SNR), and ability to reject the influence of extracerebral blood flow across a variety of time gates to determine optimal operating parameters.
Approach: Light propagation was modeled on an MRI-derived human head geometry using Monte Carlo simulations for 765- and 1064-nm excitation wavelengths. We use a virtual probe with a source–detector separation of 1 cm placed in the pre-frontal region. Performance metrics described above were evaluated to determine optimal time gate(s) for different IRFs. Validation of simulation noise estimates was done with experiments conducted on an intralipid-based liquid phantom.
Results: We find that TD-DCS performance strongly depends on the system IRF. Among Gaussian pulse shapes, ∼300 ps pulse length appears to offer the best performance, at wide gates (500 ps and larger) with start times 400 and 600 ps after the peak of the TPSF at 765 and 1064 nm, respectively, for a 1-s integration time at photon detection rates seen experimentally (600 kcps at 765 nm and 4 Mcps at 1064 nm).
Conclusions: Our work shows that optimal time gates satisfy competing requirements for sufficient sensitivity and sufficient SNR. The achievable performance is further impacted by system IRF with ∼300 ps quasi-Gaussian pulse obtained using electro-optic laser shaping providing the best results.
Non-invasive monitoring of cerebral blood flow at the bedside using diffuse correlation spectroscopy is being investigated as a potential tool to improve brain health outcomes after surgery. In this work we characterize the performance of diffuse correlation spectroscopy measurements in assessing cerebral blood flow in the presence of systemic physiology interference through measurements on several healthy volunteers during CO2 inhalation. We report group averaged responses and the role of multi-layer models in increasing the accuracy of CBF estimates. We compare optical blood flow recordings with transcranial Doppler ultrasound and MRI ASL data.
The ability of diffuse correlation spectroscopy (DCS) to measure tissue perfusion paves the way for monitoring cerebral blood flow (CBF) non-invasively. However, during measurements on human forehead, the measured blood flow index (BFi) is susceptible to contamination due to the blood flow in extracerebral tissue. Time domain DCS addresses this problem by selecting photons based on their travel time to obtain BFi at various depths. We have determined the gate start time(s) and width(s) that can lead to optimal sensitivity of BFi to CBF during actual measurements on human subjects through simulations. The simulated parameters were compared with measurement data.
Significance: Contamination of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow (CBF) due to systemic physiology remains a significant challenge in the clinical translation of DCS for neuromonitoring. Tunable, multi-layer Monte Carlo-based (MC) light transport models have the potential to remove extracerebral flow cross-talk in cerebral blood flow index (CBFi) estimates.
Aim: We explore the effectiveness of MC DCS models in recovering accurate CBFi changes in the presence of strong systemic physiology variations during a hypercapnia maneuver.
Approach: Multi-layer slab and head-like realistic (curved) geometries were used to run MC simulations of photon propagation through the head. The simulation data were post-processed into models with variable extracerebral thicknesses and used to fit DCS multi-distance intensity autocorrelation measurements to estimate CBFi timecourses. The results of the MC CBFi values from a set of human subject hypercapnia sessions were compared with CBFi values estimated using a semi-infinite analytical model, as commonly used in the field.
Results: Group averages indicate a gradual systemic increase in blood flow following a different temporal profile versus the expected rapid CBF response. Optimized MC models, guided by several intrinsic criteria and a pressure modulation maneuver, were able to more effectively separate CBFi changes from scalp blood flow influence than the analytical fitting, which assumed a homogeneous medium. Three-layer models performed better than two-layer ones; slab and curved models achieved largely similar results, though curved geometries were closer to physiological layer thicknesses.
Conclusion: Three-layer, adjustable MC models can be useful in separating distinct changes in scalp and brain blood flow. Pressure modulation, along with reasonable estimates of physiological parameters, can help direct the choice of appropriate layer thicknesses in MC models.
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.
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.
The ability of diffuse correlation spectroscopy (DCS) to measure tissue perfusion paves the way for monitoring cerebral blood flow non-invasively. However, during measurements on human forehead, the measured blood flow index (BFi) is susceptible to contamination due to the blood flow in extracerebral tissue. Time domain DCS addresses this problem by selecting photons based on their travel time to obtain BFi at various depths. We have determined the gate start time(s) and width(s) that can lead to optimal sensitivity of BFi to brain blood flow during actual measurements on human subjects using commercially available hardware with accurate noise modelling.
Diffuse correlation spectroscopy (DCS) is an increasingly widespread non-invasive technology to measure tissue perfusion. Extending this technique into adult brain monitoring to assess real-time cerebral blood flow (CBF) requires addressing the influence of extracerebral contributions on DCS measurements. We compare several Monte Carlo based forward simulation models on the efficacy of CBF isolation, including ones generated directly from individual subject MRI scans. We conclude that a multi-layer curved surface representation is beneficial, and that the traditional single-layer homogenous model is insufficient; however, detailed structural information such as cortical folding represented in an individualized tissue-specific model may not be needed.
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 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).
This paper presents a multidistance and multiwavelength diffuse correlation spectroscopy (DCS) approach and its implementation to simultaneously measure the optical proprieties of deep tissue as well as the blood flow. The system consists of three long coherence length lasers at different wavelengths in the near-infrared, eight single-photon detectors, and a correlator board. With this approach, we collect both light intensity and DCS data at multiple distances and multiple wavelengths, which provide unique information to fit for all the parameters of interest: scattering, blood flow, and hemoglobin concentration. We present the characterization of the system and its validation with phantom measurements.
Intracranial pressure (ICP) monitoring has a key role in the management of neurosurgical and neurological injuries. Currently, the standard clinical monitoring of ICP requires an invasive transducer into the parenchymal tissue or the brain ventricle, with possibility of complications such as hemorrhage and infection. A non-invasive method for measuring ICP, would be highly preferable, as it would allow clinicians to promptly monitor ICP during transport and allow for monitoring in a larger number of patients.
We have introduced diffuse correlation spectroscopy (DCS) as a non-invasive ICP monitor by fast measurement of pulsatile cerebral blood flow (CBF). The method is similar to Transcranial Doppler ultrasound (TCD), which derives ICP from the amplitude of the pulsatile cerebral blood flow velocity, with respect to the amplitude of the pulsatile arterial blood pressure. We believe DCS measurement is superior indicator of ICP than TCD estimation because DCS directly measures blood flow, not blood flow velocity, and the small cortical vessels measured by DCS are more susceptible to transmural pressure changes than the large vessels.
For fast DCS measurements to recover pulsatile CBF we have developed a custom high-power long-coherent laser and a strategy for delivering it to the tissue within ANSI standards. We have also developed a custom FPGA-based correlator board, which facilitates DCS data acquisitions at 50-100 Hz. We have tested the feasibility of measuring pulsatile CBF and deriving ICP in two challenging scenarios: humans and rats. SNR is low in human adults due to large optode distances. It is similarly low in rats because the fast heart rate in this setting requires a high repetition rate.
We propose a multi-kHz Single-Photon Counting (SPC) space LIDAR, exploiting low energy pulses with high repetition frequency (PRF). The high PRF allows one to overcome the low signal limitations, as many return shots can be collected from nearly the same scattering area. The ALART space instrument exhibits a multi-beam design, providing height retrieval over a wide area and terrain slope measurements. This novel technique, working with low SNRs, allows multiple beam generation with a single laser, limiting mass and power consumption. As the receiver has a certain probability to detect multiple photons from different levels of canopy, a histogram is constructed and used to retrieve the properties of the target tree, by means of a modal decomposition of the reconstructed waveform. A field demonstrator of the ALART space instrument is currently being developed by a European consortium led by cosine | measurement systems and funded by ESA under the TRP program. The demonstrator requirements have been derived to be representative of the target instrument and it will be tested in an equipped tower in woodland areas in the Netherlands. The employed detectors are state-of-the-art CMOS Single-Photon Avalanche Diode (SPAD) matrices with 1024 pixels. Each pixel is independently equipped with an integrated Time-to-Digital Converter (TDC), achieving a timing accuracy that is much lower than the SPAD dead time, resulting in a distance resolution in the centimeter range. The instrument emits nanosecond laser pulses with energy on the order of several μJ, at a PRF of ~ 10 kHz, and projects on ground a three-beams pattern. An extensive field measurement campaign will validate the employed technologies and algorithms for vegetation height retrieval.
We present a high performance Time-to-Digital Converter (TDC) card that provides 10 ps timing resolution and 20 ps
(rms) timing precision with a programmable full-scale-range from 160 ns to 10 μs. Differential Non-Linearity (DNL) is
better than 1.3% LSB (rms) and Integral Non-Linearity (INL) is 5 ps rms. Thanks to the low power consumption (400
mW) and the compact size (78 mm x 28 mm x 10 mm), this card is the building block for developing compact
multichannel time-resolved instrumentation for Time-Correlated Single-Photon Counting (TCSPC). The TDC-card
outputs the time measurement results together with the rates of START and STOP signals and the number of valid TDC
conversions. These additional information are needed by many TCSPC-based applications, such as: Fluorescence
Lifetime Imaging (FLIM), Time-of-Flight (TOF) ranging measurements, time-resolved Positron Emission Tomography
(PET), single-molecule spectroscopy, Fluorescence Correlation Spectroscopy (FCS), Diffuse Optical Tomography
(DOT), Optical Time-Domain Reflectometry (OTDR), quantum optics, etc.
We present our latest results concerning CMOS Single-Photon Avalanche Diode (SPAD) arrays for high-throughput parallel single-photon counting. We exploited a high-voltage 0.35 μm CMOS technology in order to develop low-noise CMOS SPADs. The Dark Count Rate is 30 cps at room temperature for 30 μm devices, increases to 2 kcps for 100 μm SPADs and just to 100 kcps for 500 μm ones. Afterpulsing is less than 1% for hold-off time longer than 50 ns, thus allowing to reach high count rates. Photon Detection Efficiency is > 50% at 420 nm, > 40% below 500 nm and is still 5% at 850 nm. Timing jitter is less than 100 ps (FWHM) in SPADs with active area diameter up to 50 μm.
We developed CMOS SPAD imagers with 150 μm pixel pitch and 30 μm SPADs. A 64×32 SPAD array is based on pixels including three 9-bit counters for smart phase-resolved photon counting up to 100 kfps. A 32x32 SPAD array includes 1024 10-bit Time-to-Digital Converters (TDC) with 300 ps resolution and 450 ps single-shot precision, for 3D ranging and FLIM. We developed also linear arrays with up to 60 pixels (with 100 μm SPAD, 150 μm pitch and in-pixel 250 ps TDC) for time-resolved parallel spectroscopy with high fill factor.
We present a compact time-resolved spectrometer suitable for optical spectroscopy from 400 nm to 1 μm wavelengths.
The detector consists of a monolithic array of 16 high-precision Time-to-Digital Converters (TDC) and Single-Photon
Avalanche Diodes (SPAD). The instrument has 10 ps resolution and reaches 70 ps (FWHM) timing precision over a 160
ns full-scale range with a Differential Non-Linearity (DNL) better than 1.5 % LSB. The core of the spectrometer is the
application-specific integrated chip composed of 16 pixels with 250 μm pitch, containing a 20 μm diameter SPAD and
an independent TDC each, fabricated in a 0.35 μm CMOS technology. In front of this array a monochromator is used to
focus different wavelengths into different pixels. The spectrometer has been used for fluorescence lifetime spectroscopy:
5 nm spectral resolution over an 80 nm bandwidth is achieved. Lifetime spectroscopy of Nile blue is demonstrated.
KEYWORDS: Picosecond phenomena, Luminescence, Clocks, Field programmable gate arrays, Electronics, Power supplies, Fluorescence lifetime imaging, Time metrology, Interfaces, Data acquisition
We present a low-power Time-to-Digital Converter (TDC) chip, fabricated in a standard cost-effective 0.35 μm CMOS
technology, which provides 160 ns dynamic range, 10 ps timing resolution and Differential Non-Linearity better than
0.01 LSB rms. This chip is the core of a compact TDC module equipped with an USB 2.0 interface for user-friendly
control and data-acquisition. The TDC module is suitable for a wide variety of applications such as Fluorescence
Lifetime Imaging (FLIM), time-resolved spectroscopy, Diffuse Optical Spectroscopy (DOS), Optical Time-Domain
Reflectometry (OTDR), quantum optics, etc. In particular, we show the application of our TDC module to fluorescence
lifetime measurements.
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