Reflectance-mode interferometric near-infrared spectroscopy quantifies brain absorption, scattering, and blood flow index in vivo

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.

Tutorial on methods for estimation of optical absorption and scattering properties of tissue

Significance

The estimation of tissue optical properties using diffuse optics has found a range of applications in disease detection, therapy monitoring, and general health care. Biomarkers derived from the estimated optical absorption and scattering coefficients can reflect the underlying progression of many biological processes in tissues.

Aim

Complex light-tissue interactions make it challenging to disentangle the absorption and scattering coefficients, so dedicated measurement systems are required. We aim to help readers understand the measurement principles and practical considerations needed when choosing between different estimation methods based on diffuse optics.

Approach

The estimation methods can be categorized as: steady state, time domain, time frequency domain (FD), spatial domain, and spatial FD. The experimental measurements are coupled with models of light-tissue interactions, which enable inverse solutions for the absorption and scattering coefficients from the measured tissue reflectance and/or transmittance.

Results

The estimation of tissue optical properties has been applied to characterize a variety of ex vivo and in vivo tissues, as well as tissue-mimicking phantoms. Choosing a specific estimation method for a certain application has to trade-off its advantages and limitations.

Conclusion

Optical absorption and scattering property estimation is an increasingly important and accessible approach for medical diagnosis and health monitoring.

Interferometric near-infrared spectroscopy (iNIRS) reveals that blood flow index depends on wavelength

Blood flow index (BFI) is an optically accessible parameter, with unit distance-squared-over-time, that is widely used as a proxy for tissue perfusion. BFI is defined as the dynamic scattering probability (i.e. the ratio of dynamic to overall reduced scattering coefficients) times an effective Brownian diffusion coefficient that describes red blood cell (RBC) motion. Here, using a wavelength division multiplexed, time-of-flight- (TOF) - resolved iNIRS system, we obtain TOF-resolved field autocorrelations at 773 nm and 855 nm via the same source and collector. We measure the human forearm, comprising biological tissues with mixed static and dynamic scattering, as well as a purely dynamic scattering phantom. Our primary finding is that forearm BFI increases from 773 nm to 855 nm, though the magnitude of this increase varies across subjects (23% ± 19% for N = 3). However, BFI is wavelength-independent in the purely dynamic scattering phantom. From these data, we infer that the wavelength-dependence of BFI arises from the wavelength-dependence of the dynamic scattering probability. This inference is further supported by RBC scattering literature. Our secondary finding is that the higher-order cumulant terms of the mean squared displacement (MSD) of RBCs are significant, but decrease with wavelength. Thus, laser speckle and related modalities should exercise caution when interpreting field autocorrelations.

Interferometric diffusing wave spectroscopy imaging with an electronically variable time-of-flight filter

Diffuse optics (DO) is a light-based technique used to study the human brain, but it suffers from low brain specificity. Interferometric diffuse optics (iDO) promises to improve the quantitative accuracy and depth specificity of DO, and particularly, coherent light fluctuations (CLFs) arising from blood flow. iDO techniques have alternatively achieved either time-of-flight (TOF) discrimination or highly parallel detection, but not both at once. Here, we break this barrier with a single iDO instrument. Specifically, we show that rapid tuning of a temporally coherent laser during the sensor integration time increases the effective linewidth seen by a highly parallel interferometer. Using this concept to create a continuously variable and user-specified TOF filter, we demonstrate a solution to the canonical problem of DO, measuring optical properties. Then, with a deep TOF filter, we reduce scalp sensitivity of CLFs by 2.7 times at 1 cm source-collector separation. With this unique combination of desirable features, i.e., TOF-discrimination, spatial localization, and highly parallel CLF detection, we perform multiparametric imaging of light intensities and CLFs via the human forehead.

Interferometric diffuse optics: recent advances and future outlook

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

Continuous-wave parallel interferometric near-infrared spectroscopy (CW NIRS) with a fast two-dimensional camera

Interferometric near-infrared spectroscopy (iNIRS) is an optical method that noninvasively measures the optical and dynamic properties of the human brain in vivo. However, the original iNIRS technique uses single-mode fibers for light collection, which reduces the detected light throughput. The reduced light throughput is compensated by the relatively long measurement or integration times (∼1 sec), which preclude monitoring of rapid blood flow changes that could be linked to neural activation. Here, we propose parallel interferometric near-infrared spectroscopy (πNIRS) to overcome this limitation. In πNIRS we use multi-mode fibers for light collection and a high-speed, two-dimensional camera for light detection. Each camera pixel acts effectively as a single iNIRS channel. So, the processed signals from each pixel are spatially averaged to reduce the overall integration time. Moreover, interferometric detection provides us with the unique capability of accessing complex information (amplitude and phase) about the light remitted from the sample, which with more than 8000 parallel channels, enabled us to sense the cerebral blood flow with only a 10 msec integration time (∼100x faster than conventional iNIRS). In this report, we have described the theoretical foundations and possible ways to implement πNIRS. Then, we developed a prototype continuous wave (CW) πNIRS system and validated it in liquid phantoms. We used our CW πNIRS to monitor the pulsatile blood flow in a human forearm in vivo. Finally, we demonstrated that CW πNIRS could monitor activation of the prefrontal cortex by recording the change in blood flow in the forehead of the subject while he was reading an unknown text.

Performance assessment of laser sources for time-domain diffuse correlation spectroscopy

Time-domain diffuse correlation spectroscopy (TD-DCS) is an emerging optical technique that enables noninvasive measurement of microvascular blood flow with photon path-length resolution. In TD-DCS, a picosecond pulsed laser with a long coherence length, adequate illumination power, and narrow instrument response function (IRF) is required, and satisfying all these features is challenging. To this purpose, in this study we characterized the performance of three different laser sources for TD-DCS. First, the sources were evaluated based on their emission spectrum and IRF. Then, we compared the signal-to-noise ratio and the sensitivity to velocity changes of scattering particles in a series of phantom measurements. We also compared the results for in vivo measurements, performing an arterial occlusion protocol on the forearm of three adult subjects. Overall, each laser has the potential to be successfully used both for laboratory and clinical applications. However, we found that the effects caused by the IRF are more significant than the effect of a limited temporal coherence.

Time-domain diffuse correlation spectroscopy (TD-DCS) for noninvasive, depth-dependent blood flow quantification in human tissue in vivo

Monitoring of human tissue hemodynamics is invaluable in clinics as the proper blood flow regulates cellular-level metabolism. Time-domain diffuse correlation spectroscopy (TD-DCS) enables noninvasive blood flow measurements by analyzing temporal intensity fluctuations of the scattered light. With time-of-flight (TOF) resolution, TD-DCS should decompose the blood flow at different sample depths. For example, in the human head, it allows us to distinguish blood flows in the scalp, skull, or cortex. However, the tissues are typically polydisperse. So photons with a similar TOF can be scattered from structures that move at different speeds. Here, we introduce a novel approach that takes this problem into account and allows us to quantify the TOF-resolved blood flow of human tissue accurately. We apply this approach to monitor the blood flow index in the human forearm in vivo during the cuff occlusion challenge. We detect depth-dependent reactive hyperemia. Finally, we applied a controllable pressure to the human forehead in vivo to demonstrate that our approach can separate superficial from the deep blood flow. Our results can be beneficial for neuroimaging sensing applications that require short interoptode separation.

Beyond diffuse correlations: deciphering random flow in time-of-flight resolved light dynamics

Diffusing wave spectroscopy (DWS) and diffuse correlation spectroscopy (DCS) can assess blood flow index (BFI) of biological tissue with multiply scattered light. Though the main biological function of red blood cells (RBCs) is advection, in DWS/DCS, RBCs are assumed to undergo Brownian motion. To explain this discrepancy, we critically examine the cumulant approximation, a major assumption in DWS/DCS. We present a precise criterion for validity of the cumulant approximation, and in realistic tissue models, identify conditions that invalidate it. We show that, in physiologically relevant scenarios, the first cumulant term for random flow and second cumulant term for Brownian motion alone can cancel each other. In such circumstances, assuming pure Brownian motion of RBCs and the first cumulant approximation, a routine practice in DWS/DCS of BFI, can yield good agreement with data, but only because errors due to two incorrect assumptions cancel out. We conclude that correctly assessing random flow from scattered light dynamics requires going beyond the cumulant approximation and propose a more accurate model to do so.

Time-of-flight resolved light field fluctuations reveal deep human tissue physiology

Red blood cells (RBCs) transport oxygen to tissues and remove carbon dioxide. Diffuse optical flowmetry (DOF) assesses deep tissue RBC dynamics by measuring coherent fluctuations of multiply scattered near-infrared light intensity. While classical DOF measurements empirically correlate with blood flow, they remain far-removed from light scattering physics and difficult to interpret in layered media. To advance DOF measurements closer to the physics, here we introduce an interferometric technique, surmounting challenges of bulk motion to apply it in awake humans. We reveal two measurement dimensions: optical phase, and time-of-flight (TOF), the latter with 22 picosecond resolution. With this multidimensional data, we directly confirm the unordered, or Brownian, nature of optically probed RBC dynamics typically assumed in classical DOF. We illustrate how incorrect absorption assumptions, anisotropic RBC scattering, and layered tissues may confound classical DOF. By comparison, our direct method enables accurate and comprehensive assessment of blood flow dynamics in humans.

Spatially-enhanced time-domain NIRS for accurate determination of tissue optical properties

A multivariate method integrating time and space resolved techniques of near-infrared spectroscopy is proposed for simultaneously retrieving the absolute quantities of optical absorption and scattering properties in tissues. The time-domain feature of photon migration is advantageously constrained and regularized by its spatially-resolved amplitude patterns in the inverse procedure. Measurements of tissue-mimicking phantoms with various optical properties are analyzed with Monte-Carlo simulations to validate the method performance. The uniqueness, stability, and uncertainty of the method are discussed.

Effects of the instrument response function and the gate width in time-domain diffuse correlation spectroscopy: model and validations

Time-domain diffuse correlation spectroscopy (TD-DCS) is an emerging noninvasive optical technique with the potential to resolve blood flow (BF) and optical coefficients (reduced scattering and absorption) in depth. Here, we study the effects of finite temporal resolution and gate width in a realistic TD-DCS experiment. We provide a model for retrieving the BF from gated intensity autocorrelations based on the instrument response function, which allows for the use of broad time gates. This, in turn, enables a higher signal-to-noise ratio that is critical for in vivo applications. In numerical simulations, the use of the proposed model reduces the error in the estimated late gate BF from 34% to 3%. Simulations are also performed for a wide set of optical properties and source–detector separations. In a homogeneous phantom experiment, the discrepancy between later gates BF index and ungated BF index is reduced from 37% to 2%. This work not only provides a tool for data analysis but also physical insights, which can be useful for studying and optimizing the system performance.

Probing complex dynamics with spatiotemporal coherence-gated DLS

We discuss the specific features of fiber-based implementations of optical sensing techniques based on spatiotemporal coherence-gated dynamic light scattering (DLS). This sensing approach has a number of unique capabilities such as an effective isolation of single scattering, a large sensitivity, and high collection efficiency, and it can also operate over a wide range of optical regimes while providing means for proper ensemble averaging. We review a number of applications in which these specific characteristics permit recovering information beyond the capabilities of traditional light-scattering-based techniques.

Low-cost high integration IR polymer microlens array

In this Letter, a low-cost refractive convex microlens array device based on infrared a polymer is fabricated by a nanoimprinting technique. The device integrates more than 4000 microlenslets within a footprint of 10  mm×10  mm. The surface quality, spectral transmittance, imaging resolution, and surface damage threshold of the device have been fully characterized. The IR imaging and parallel laser inscription experiments confirm the remarkable optical performance of the fabricated device. Owing to the merits of high optical quality, low fluence lose, and simple fabrication, this device is promising in cutting-edge IR applications, such as IR imaging, laser fabrication, and so on.

Correlation gating quantifies the optical properties of dynamic media in transmission

Quantifying light transport in turbid media is a long-standing challenge. This challenge arises from the difficulty in experimentally separating unscattered, ballistic light from forward scattered light. Correlation gating is a new approach that numerically separates light paths based on statistical dynamics of the optical field. Here we apply correlation gating with interferometric near-infrared spectroscopy (iNIRS) to separate and independently quantify ballistic and scattered light transmitted through thick samples. First, we present evidence that correlation gating improves the isolation of ballistic light in a thick, intrinsically dynamic medium with Brownian motion. Then, from a single set of iNIRS transmission measurements, we determine the ballistic attenuation coefficient and group refractive index from the time-of-flight (TOF) resolved static intensity, and we determine the reduced scattering and absorption coefficients from the diffusive part of the TOF resolved dynamic intensity. Finally, we show that correlation gating is applicable in intrinsically static media in which motion is induced externally. Thus, for the first time, to the best of our knowledge, the key optical properties of a turbid medium can be derived from a single set of transmission measurements.

Highly parallel, interferometric diffusing wave spectroscopy for monitoring cerebral blood flow dynamics

Light-scattering methods are widely used in soft matter physics and biomedical optics to probe dynamics in turbid media, such as diffusion in colloids or blood flow in biological tissue. These methods typically rely on fluctuations of coherent light intensity, and therefore cannot accommodate more than a few modes per detector. This limitation has hindered efforts to measure deep tissue blood flow with high speed, since weak diffuse light fluxes, together with low single-mode fiber throughput, result in low photon count rates. To solve this, we introduce multimode fiber (MMF) interferometry to the field of diffuse optics. In doing so, we transform a standard complementary metal-oxide-semiconductor (CMOS) camera into a sensitive detector array for weak light fluxes that probe deep in biological tissue. Specifically, we build a novel CMOS-based, multimode interferometric diffusing wave spectroscopy (iDWS) system and show that it can measure ∼20 speckles simultaneously near the shot noise limit, acting essentially as ∼20 independent photon-counting channels. We develop a matrix formalism, based on MMF mode field solutions and detector geometry, to predict both coherence and speckle number in iDWS. After validation in liquid phantoms, we demonstrate iDWS pulsatile blood flow measurements at 2.5 cm source-detector separation in the adult human brain in vivo. By achieving highly sensitive and parallel measurements of coherent light fluctuations with a CMOS camera, this work promises to enhance performance and reduce cost of diffuse optical instruments.

Near-infrared diffuse reflectance signals for monitoring spreading depolarizations and progression of the lesion in a male rat focal cerebral ischemia model

In ischemic stroke research, a better understanding of the pathophysiology and development of neuroprotection methods are crucial, for which in vivo imaging to monitor spreading depolarizations (SDs) and evolution of tissue damage is desired. Since these events are accompanied by cellular morphological changes, light-scattering signals, which are sensitive to cellular and subcellular morphology, can be used for monitoring them. In this study, we performed transcranial imaging of near-infrared (NIR) diffuse reflectance at ∼800 nm, which sensitively reflects light-scattering change, and examined how NIR reflectance is correlated with simultaneously measured cerebral blood flow (CBF) for a rat middle cerebral artery occlusion (MCAO) model. After MCAO, wavelike NIR reflectance changes indicating occurrence of SDs were generated and propagated around the ischemic core for ∼90 min, during which time NIR reflectance increased not only within the ischemic core but also in the peripheral region. The area with increased reflectance expanded with increase in the number of SD occurrences, the correlation coefficient being 0.7686 (n = 5). The area with increased reflectance had become infarcted at 24 hr after MCAO. The infarct region was found to be associated with hypoperfusion or no-flow response to SD, but hyperemia or hypoperfusion followed by hyperemia response to SD was also observed, and the regional heterogeneity seemed to be connected with the rat cerebrovasculature and hence existence/absence of collateral flow. The results suggest that NIR reflectance signals depicted early evolution of tissue damage, which was not seen by CBF changes, and enabled lesion progression monitoring in the present stroke model.