Interferometric Near-Infrared Spectroscopy (iNIRS) for determination of optical and dynamical properties of turbid media

Study of Time-Resolved Dynamics in Turbid Medium Using a Single-Cavity Dual-Comb Laser

In measuring cerebral blood flow (CBF) noninvasively using optical techniques, diffusing-wave spectroscopy is often combined with near-infrared spectroscopy to obtain a reliable blood flow index. Measuring the blood flow index at a determined depth remains the ultimate goal. In this study, we present a simple approach using dual-comb lasers where we simultaneously measure the absorption coefficient (μa), the reduced scattering coefficient (μs '), and dynamic properties. This system can also effectively differentiate dynamics from various depths, which is crucial for analyzing multilayer dynamics. For CBF measurements, this capability is particularly valuable as it helps mitigate the influence of the scalp and skull, thereby enhancing the specificity of deep tissue.

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.

Recovering fetal signals transabdominally through interferometric near-infrared spectroscopy (iNIRS)

Noninvasive transabdominal fetal pulse oximetry can provide clinicians critical assessment of fetal health and potentially contribute to improved management of childbirth. Conventional pulse oximetry through continuous wave (CW) light has challenges measuring the signals from deep tissue and separating the weak fetal signal from the strong maternal signal. Here, we propose a new approach for transabdominal fetal pulse oximetry through interferometric near-infrared spectroscopy (iNIRS). This approach provides pathlengths of photons traversing the tissue, which facilitates the extraction of fetal signals by rejecting the very strong maternal signal from superficial layers. We use a multimode fiber combined with a mode-field converter at the detection arm to boost the signal of iNIRS. Together, we can detect signals from deep tissue (>∼1.6 cm in sheep abdomen and in human forearm) at merely 1.1 cm distance from the source. Using a pregnant sheep model, we experimentally measured and extracted the fetal heartbeat signals originating from deep tissue. This validated a key step towards transabdominal fetal pulse oximetry through iNIRS and set a foundation for further development of this method to measure the fetal oxygen saturation.

Experimental demonstration of a new near-infrared spectroscopy technique based on optical dual-comb: DC-NIRS

We present a novel near-infrared spectroscopy technique based on Dual-Comb optical interrogation (DC-NIRS) applied to dispersive media. The technique recovers the frequency response of the medium under investigation by sampling its spectral response in amplitude and phase. The DC-NIRS reference and sample signals are generated using electro-optic modulation which offers a cost-effective, integrable solution while providing high adaptability to the interrogated medium. A careful choice of both line spacing and optical span of the frequency comb ensures that the retrieved information enables the reconstruction of the temporal impulse response of the medium, known as the diffuse-time-of-flight (DTOF), to obtain its optical properties with a 70 µs temporal resolution and 32 ps photon propagation delay resolution. Furthermore, the DC-NIRS technique also offers enhanced penetration due to noiseless optical amplification (interferometric detection). The presented technique was demonstrated on a static bio-mimetic phantom of known optical properties reproducing a typical brain's optical response. The DTOF and optical properties of the phantom were measured, showing the capabilities of this new technique on the estimation of absolute optical properties with a deviation under 3%. Compared to current technologies, our DC-NIRS technique provides enhanced temporal resolution, spatial location capabilities, and penetration depth, with an integrable and configurable cost-effective architecture, paving the way to next-generation, non-invasive and portable systems for functional brain imaging, and brain-computer interfaces, among other. The system is patent pending PCT/ES2022/070176.

Massively parallel, real-time multispeckle diffuse correlation spectroscopy using a 500 × 500 SPAD camera

Diffuse correlation spectroscopy (DCS) is a promising noninvasive technique for monitoring cerebral blood flow and measuring cortex functional activation tasks. Taking multiple parallel measurements has been shown to increase sensitivity, but is not easily scalable with discrete optical detectors. Here we show that with a large 500 × 500 SPAD array and an advanced FPGA design, we achieve an SNR gain of almost 500 over single-pixel mDCS performance. The system can also be reconfigured to sacrifice SNR to decrease correlation bin width, with 400 ns resolution being demonstrated over 8000 pixels.

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.

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.

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.

Quantifying the Cerebral Hemometabolic Response to Blood Transfusion in Pediatric Sickle Cell Disease With Diffuse Optical Spectroscopies

Red blood cell transfusions are common in patients with sickle cell disease who are at increased risk of stroke. Unfortunately, transfusion thresholds needed to sufficiently dilute sickle red blood cells and adequately restore oxygen delivery to the brain are not well defined. Previous work has shown that transfusion is associated with a reduction in oxygen extraction fraction and cerebral blood flow, both of which are abnormally increased in sickle patients. These reductions are thought to alleviate hemometabolic stress by improving the brain's ability to respond to increased metabolic demand, thereby reducing susceptibility to ischemic injury. Monitoring the cerebral hemometabolic response to transfusion may enable individualized management of transfusion thresholds. Diffuse optical spectroscopies may present a low-cost, non-invasive means to monitor this response. In this study, children with SCD undergoing chronic transfusion therapy were recruited. Diffuse optical spectroscopies (namely, diffuse correlation spectroscopy combined with frequency domain near-infrared spectroscopy) were used to quantify oxygen extraction fraction (OEF), cerebral blood volume (CBV), an index of cerebral blood flow (CBF_i), and an index of cerebral oxygen metabolism (CMRO_2i) in the frontal cortex immediately before and after transfusion. A subset of patients receiving regular monthly transfusions were measured during a subsequent transfusion. Data was captured from 35 transfusions in 23 patients. Transfusion increased median blood hemoglobin levels (Hb) from 9.1 to 11.7 g/dL (p < 0.001) and decreased median sickle hemoglobin (HbS) from 30.9 to 21.7% (p < 0.001). Transfusion decreased OEF by median 5.9% (p < 0.001), CBFi by median 21.2% (p = 0.020), and CBV by median 18.2% (p < 0.001). CMRO_2i did not statistically change from pre-transfusion levels (p > 0.05). Multivariable analysis revealed varying degrees of associations between outcomes (i.e., OEF, CBF_i, CBV, and CMRO_2i), Hb, and demographics. OEF, CBF_i, and CBV were all negatively associated with Hb, while CMRO_2i was only associated with age. These results demonstrate that diffuse optical spectroscopies are sensitive to the expected decreases of oxygen extraction, blood flow, and blood volume after transfusion. Diffuse optical spectroscopies may be a promising bedside tool for real-time monitoring and goal-directed therapy to reduce stroke risk for sickle cell disease.

Scanning interferometric near-infrared spectroscopy

In diffuse optics, quantitative assessment of the human brain is confounded by the skull and scalp. To better understand these superficial tissues, we advance interferometric near-infrared spectroscopy (iNIRS) to form images of the human superficial forehead blood flow index (BFI). We present a null source-collector (S-C) polarization splitting approach that enables galvanometer scanning and eliminates unwanted backscattered light. Images show an order-of-magnitude heterogeneity in superficial dynamics, implying an order-of-magnitude heterogeneity in brain specificity, depending on forehead location. Along the time-of-flight dimension, autocorrelation decay rates support a three-layer model with increasing BFI from the skull to the scalp to the brain. By accurately characterizing superficial tissues, this approach can help improve specificity for the human brain.

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.

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.

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.

Random Multiple Scattering Enhanced Photoacoustic Gas Spectroscopy with Disordered Porous Ceramics

Light-gas interaction can be enhanced by using disordered porous materials because multiple random scattering increases light intensity near the surface of the material. Here we report signal enhancement of photoacoustic gas spectroscopy with disordered porous ceramics. The amplitude and frequency characteristics of photoacoustic signal due to gas absorption in disordered materials are modeled theoretically. Experiment with a porous Al₂O₃ sample demonstrates photoacoustic signal enhancement of ∼4 times at 5 kHz.

Comparison of spatially and temporally resolved diffuse transillumination measurement systems for extraction of optical properties of scattering media

This paper discusses the main differences between two different methods for determining the optical properties of tissue optical phantoms by fitting the spatial and temporal intensity distribution functions to the diffusion approximation theory. The consistency in the values of the optical properties is verified by changing the width of the recipient containing the turbid medium; as the optical properties are an intrinsic value of the scattering medium, independently of the recipient width, the stability in these values for different widths implies a better measurement system for the acquisition of the optical properties. It is shown that the temporal fitting method presents higher stability than the spatial fitting method; this is probably due to the addition of the time of flight parameter into the diffusion theory.

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

Interferometric near-infrared spectroscopy (iNIRS) is a new technique that measures time-of-flight- (TOF-) resolved autocorrelations in turbid media, enabling simultaneous estimation of optical and dynamical properties. Here, we demonstrate reflectance-mode iNIRS for noninvasive monitoring of a mouse brain in vivo. A method for more precise quantification with less static interference from superficial layers, based on separating static and dynamic components of the optical field autocorrelation, is presented. Absolute values of absorption, reduced scattering, and blood flow index (BFI) are measured, and changes in BFI and absorption are monitored during a hypercapnic challenge. Absorption changes from TOF-resolved iNIRS agree with absorption changes from continuous wave NIRS analysis, based on TOF-integrated light intensity changes, an effective path length, and the modified Beer-Lambert Law. Thus, iNIRS is a promising approach for quantitative and noninvasive monitoring of perfusion and optical properties in vivo.

Time-domain diffuse correlation spectroscopy

Physiological monitoring of oxygen delivery to the brain has great significance for improving the management of patients at risk for brain injury. Diffuse correlation spectroscopy (DCS) is a rapidly growing optical technology able to non-invasively assess the blood flow index (BFi) at the bedside. The current limitations of DCS are the contamination introduced by extracerebral tissue and the need to know the tissue's optical properties to correctly quantify the BFi. To overcome these limitations, we have developed a new technology for time-resolved diffuse correlation spectroscopy. By operating DCS in the time domain (TD-DCS), we are able to simultaneously acquire the temporal point-spread function to quantify tissue optical properties and the autocorrelation function to quantify the BFi. More importantly, by applying time-gated strategies to the DCS autocorrelation functions, we are able to differentiate between short and long photon paths through the tissue and determine the BFi for different depths. Here, we present the novel device and we report the first experiments in tissue-like phantoms and in rodents. The TD-DCS method opens many possibilities for improved non-invasive monitoring of oxygen delivery in humans.

New frontiers in time-domain diffuse optics, a review

The recent developments in time-domain diffuse optics that rely on physical concepts (e.g., time-gating and null distance) and advanced photonic components (e.g., vertical cavity source-emitting laser as light sources, single photon avalanche diode, and silicon photomultipliers as detectors, fast-gating circuits, and time-to-digital converters for acquisition) are focused. This study shows how these tools could lead on one hand to compact and wearable time-domain devices for point-of-care diagnostics down to the consumer level and on the other hand to powerful systems with exceptional depth penetration and sensitivity.

Interferometric near-infrared spectroscopy directly quantifies optical field dynamics in turbid media

Sensing and imaging methods based on the dynamic scattering of coherent light (including laser speckle, laser Doppler, diffuse correlation spectroscopy, dynamic light scattering, and diffusing wave spectroscopy) quantify scatterer motion using light intensity fluctuations. The underlying optical field autocorrelation, rather than being measured directly, is typically inferred from the intensity autocorrelation through the Siegert relationship, assuming that the scattered field obeys Gaussian statistics. Here, we demonstrate interferometric near-infrared spectroscopy for measuring the time-of-flight (TOF) resolved field and intensity autocorrelations in turbid media. We find that the Siegert relationship breaks down for short TOFs due to static paths whose optical field does not decorrelate over experimental time scales. We also show that eliminating such paths by polarization gating restores the validity of the Siegert relationship. The unique capability of measuring optical field autocorrelations, as demonstrated here, enables the study of non-Gaussian and non-ergodic light scattering processes. Moreover, direct measurements of field autocorrelations are more efficient than indirect measurements based on intensity autocorrelations. Thus, optical field measurements may improve the quantiffcation of scatterer dynamics with coherent light.