Pathlength-selective, interferometric diffuse correlation spectroscopy (PaLS-iDCS).

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 the technique has enabled several clinical applications for deep tissue blood flow measurements, including cerebral blood flow monitoring as well as tumor blood flow mapping. While a promising technique, in measurement configurations targeting deep tissue hemodynamics, the 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 improves upon both the sensitivity of the measurement to deep tissue hemodynamics and the SNR of the measurement using pathlength-specific coherent gain. 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 new 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 without the need for a separate spectroscopic measurement. 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, enabling further applications of this non-invasive technology.

Choosing a camera and optimizing system parameters for speckle contrast optical spectroscopy.

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal-oxide-semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems.

Measuring pulsatile cortical blood flow and volume during carotid endarterectomy.

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

Multi-wavelength multi-distance diffuse correlation spectroscopy system for assessment of premature infants' cerebral hemodynamics.

Infants born at an extremely low gestational age (ELGA, < 29 weeks) are at an increased risk of intraventricular hemorrhage (IVH), and there is a need for standalone, safe, easy-to-use tools for monitoring cerebral hemodynamics. We have built a multi-wavelength multi-distance diffuse correlation spectroscopy device (MW-MD-DCS), which utilizes time-multiplexed, long-coherence lasers at 785, 808, and 853 nm, to simultaneously quantify the index of cerebral blood flow (CBFi) and the hemoglobin oxygen saturation (SO2). We show characterization data on liquid phantoms and demonstrate the system performance on the forearm of healthy adults, as well as clinical data obtained on two preterm infants.

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.

Enhancing diffuse correlation spectroscopy pulsatile cerebral blood flow signal with near-infrared spectroscopy photoplethysmography.

Significance: Combining 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). Aim: Although 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. Approach: Taking 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). Results: In 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. Conclusions: NIRS-PPG improves DCS pCBFi SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and CVRi.

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

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

Diffuse correlation spectroscopy: current status and future outlook.

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

Functional Time Domain Diffuse Correlation Spectroscopy.

Time-domain diffuse correlation spectroscopy (TD-DCS) offers a novel approach to high-spatial resolution functional brain imaging based on the direct quantification of cerebral blood flow (CBF) changes in response to neural activity. However, the signal-to-noise ratio (SNR) offered by previous TD-DCS instruments remains a challenge to achieving the high temporal resolution needed to resolve perfusion changes during functional measurements. Here we present a next-generation optimized functional TD-DCS system that combines a custom 1,064 nm pulse-shaped, quasi transform-limited, amplified laser source with a high-resolution time-tagging system and superconducting nanowire single-photon detectors (SNSPDs). System characterization and optimization was conducted on homogenous and two-layer intralipid phantoms before performing functional CBF measurements in six human subjects. By acquiring CBF signals at over 5 Hz for a late gate start time of the temporal point spread function (TPSF) at 15 mm source-detector separation, we demonstrate for the first time the measurement of blood flow responses to breath-holding and functional tasks using TD-DCS.

How Machine Learning is Powering Neuroimaging to Improve Brain Health.

This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we aresharing the information presented at a symposium, "Neuroimaging Indicators of Brain Structure and Function - Closing the Gap Between Research and Clinical Application", co-hosted by the McCance Center for Brain Health at Mass General Hospital and the MIT HST Neuroimaging Training Program on February 12, 2021. The symposium focused on the potential for machine learning approaches, applied to increasingly large-scale neuroimaging datasets, to transform healthcare delivery and change the trajectory of brain health by addressing brain care earlier in the lifespan. While not exhaustive, this overview uniquely addresses many of the technical challenges from image formation, to analysis and visualization, to synthesis and incorporation into the clinical workflow. Some of the ethical challenges inherent to this work are also explored, as are some of the regulatory requirements for implementation. We seek to educate, motivate, and inspire graduate students, postdoctoral fellows, and early career investigators to contribute to a future where neuroimaging meaningfully contributes to the maintenance of brain health.

Diffuse Correlation Spectroscopy Beyond the Water Peak Enabled by Cross-Correlation of the Signals From InGaAs/InP Single Photon Detectors.

OBJECTIVE: Diffuse correlation spectroscopy (DCS) is an optical technique that allows for the non-invasive measurement of blood flow. Recent work has shown that utilizing longer wavelengths beyond the traditional NIR range provides a significant improvement to signal-to-noise ratio (SNR). However, current detectors both sensitive to longer wavelengths and suitable for clinical applications (InGaAs/InP SPADs) suffer from suboptimal afterpulsing and dark noise characteristics. To overcome these barriers, we introduce a cross correlation method to more accurately recover blood flow information using InGaAs/InP SPADs. METHODS: Two InGaAs/InP SPAD detectors were used for during in vitro and in vivo DCS measurements. Cross correlation of the photon streams from each detector was performed to calculate the correlation function. Detector operating parameters were varied to determine parameters which maximized measurement SNR.State-space modeling was performed to determine the detector characteristics at each operating point. RESULTS: Evaluation of detector characteristics was performed across the range of operating conditions. Modeling the effects of the detector noise on the correlation function provided a method to correct the distortion of the correlation curve, yielding accurate recovery of flow information as confirmed by a reference detector. CONCLUSION: Through a combination of cross-correlation of the signals from two detectors, model-based characterization of detector response, and optimization of detector operating parameters, the method allows for the accurate estimation of the true blood flow index. SIGNIFICANCE: This work presents a method by which DCS can be performed at longer NIR wavelengths with existing detector technology, taking advantage of the increased SNR.

Superconducting nanowire single-photon sensing of cerebral blood flow.

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

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

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.

Diffuse correlation spectroscopy measurements of blood flow using 1064 nm light.

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.

Characterization of continuous wave ultrasound for acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS).

Intra and post-operative blood flow monitoring of tissue has been shown to be effective in the improvement of patient outcomes. Diffuse correlation spectroscopy (DCS) has been shown to be effective in measuring blood flow at the bedside, and is a useful technique in measuring cerebral blood flow (CBF) in many clinical settings. However, DCS suffers from reduced sensitivity to blood flow changes at larger tissue depths, making measurements of CBF in adults difficult. This issue can be addressed with acousto-optic modulated diffuse correlation spectroscopy (AOM-DCS), which is a hybrid technique that combines the sensitivity of DCS to blood flow with ultrasound resolution to allow for improved spatial resolution of the optical signal based on knowledge of the area which is insonified by ultrasound. We present a quantitative model for perfusion estimation based on AOM-DCS in the presence of continuous wave ultrasound, supported by theoretical derivations, Monte Carlo simulations, and phantom and human subject experiments. Quantification of the influence of individual mechanisms that contribute to the temporal fluctuations of the optical intensity due to ultrasound is shown to agree with previously derived results. By using this model, the recovery of blood-flow induced scatterer dynamics based on ultrasound-modulated light is shown to deviate by less than one percent from the standard DCS measurement of scatterer dynamics over a range of optical scattering values and scatterer motion conditions. This work provides an important step towards future implementation of AOM-DCS setups with more complex spatio-temporal distributions of ultrasound pressure, which are needed to enhance the DCS spatial resolution.

Hybrid-electric passenger car energy utilization and emissions: Relationships for real-world driving conditions that account for road grade.

Past research showed on-road emissions patterns unique to hybrid electric vehicles (HEVs), indicating the need to account for them in emissions models as projected HEV sales increase over the coming decades. This work defines and characterizes a variable that quantifies HEV operating behavior to inform future development of new HEV emissions models based on current knowledge of conventional vehicle (CV) emissions patterns. Instantaneous hybridization factor (IHF), was quantified using on-road data collected from a 2010 Toyota Camry HEV. IHF is the ratio of electric system power to total system power and accounts for energy storage in the high voltage battery (IHF ranges from -1 to +1). Relationships between IHF and vehicle specific power (VSP), road type and road grade were examined. Negative VSP resulted in regenerative braking operation (IHF = -0.01 to -1) 90% of the time. IHF identified the VSP range where HEV operation was highly variable (VSP = -1 to 8 kW/ton) when driving at speeds below the ICE-off threshold (42 mph). VSP and IHF together account for 76-86% of the variability in HEV CO2 emissions in this study. CO2 model results using VSP computed with the measured real-world road grade (R2 = 0.86) gave improved fits over the no-grade VSP model (R2 = 0.69). This study establishes one framework for calculating the instantaneous HEV power split, confirms the need to include road grade in VSP for accurate modeling of vehicle emissions, and identified the need for significant improvements in on-board diagnostic (OBD) scantool measurement requirements for HEVs in three areas: (1) temporal resolution (sub-second to capture transient events such as ICE restarts); (2) simultaneous data logging capability for multiple controller area networks (i.e., engine and HEV parameters together); and (3) improved data precision.

Evidence-Based Clinical Practice Guidelines for the Management of Patients with Lentigo Maligna.

INTRODUCTION: Lentigo maligna (LM) is a subtype of melanoma in situ that usually occurs in sun-damaged skin and is characterised by an atypical proliferation of melanocytes within the basal epidermis. If left untreated, LM can develop into invasive melanoma, termed lentigo maligna melanoma, which shares the same prognosis as other types of invasive melanoma. The incidence rates of LM are steadily increasing worldwide, in parallel with increases in the incidence rates of invasive melanoma, and establishing appropriate guidelines for the management of LM is therefore of great importance. METHODS: A multidisciplinary working party established by Cancer Council Australia has recently produced up-to-date, evidence-based clinical practice guidelines for the management of melanoma and LM. Following selection of the most relevant clinical questions, a comprehensive literature search for relevant studies was conducted, followed by systematic review of these studies. Data were summarised and the evidence was assessed, leading to the development of recommendations. After public consultation and approval by the full guidelines working party, these recommendations were published on the Cancer Council Australia wiki platform (https://wiki.cancer.org.au/australia/Clinical_question:Effective_interventions_to_improve_outcomes_in_lentigo_maligna%3F). Main Recommendations: Surgical removal of LM remains the standard treatment, with 5- to 10-mm clinical margins when possible. While yet to be fully validated, the use of peri-operative reflectance confocal microscopy to assess margins should be considered where available. There is a lack of high-quality evidence to infer the most effective non-surgical treatment. When surgical removal of LM is not possible or refused, radiotherapy is recommended. When both surgery and radiotherapy are not appropriate or refused, topical imiquimod is the recommended treatment. Cryotherapy and laser therapy are not recommended for the treatment of LM.

Reflectance confocal microscopy margin mapping and monitoring of an amelanotic melanoma in situ of the ear.

In situ amelanotic melanoma represents a diagnostic and therapeutic challenge for clinicians. Poor demarcation of these lesions often results in repeated therapeutic intervention until appropriate clearance has been achieved. Reflectance confocal microscopy (RCM) is a noninvasive bedside imaging modality which allows real-time visualisation, to a near-histological level, of the epidermis and reticular dermis. We present a case of an amelanotic melanoma in situ in which reflectance confocal microscopy margin mapping allowed for demarcation of the melanocytic proliferation and targeted therapeutic intervention with topical imiquimod. Reflectance confocal microscopy was further utilised for noninvasive assessment of therapeutic response.