Establishing the diffuse correlation spectroscopy signal relationship with blood flow

Pre-clinical longitudinal monitoring of hemodynamic response to anti-vascular chemotherapy by hybrid diffuse optics

The longitudinal effect of an anti-vascular endothelial growth factor receptor 2 (VEGFR-2) antibody (DC 101) therapy on a xenografted renal cell carcinoma (RCC) mouse model was monitored using hybrid diffuse optics. Two groups of immunosuppressed male nude mice (seven treated, seven controls) were measured. Tumor microvascular blood flow, total hemoglobin concentration and blood oxygenation were investigated as potential biomarkers for the monitoring of the therapy effect twice a week and were related to the final treatment outcome. These hemodynamic biomarkers have shown a clear differentiation between two groups by day four. Moreover, we have observed that pre-treatment values and early changes in hemodynamics are highly correlated with the therapeutic outcome demonstrating the potential of diffuse optics to predict the therapy response at an early time point.

High-density speckle contrast optical tomography (SCOT) for three dimensional tomographic imaging of the small animal brain

High-density speckle contrast optical tomography (SCOT) utilizing tens of thousands of source-detector pairs, was developed for in vivo imaging of blood flow in small animals. The reduction in cerebral blood flow (CBF) due to local ischemic stroke in a mouse brain was transcanially imaged and reconstructed in three dimensions. The reconstructed volume was then compared with corresponding magnetic resonance images demonstrating that the volume of reduced CBF agrees with the infarct zone at twenty-four hours.

Clinical applications of near-infrared diffuse correlation spectroscopy and tomography for tissue blood flow monitoring and imaging

OBJECTIVE

Blood flow is one such available observable promoting a wealth of physiological insight both individually and in combination with other metrics.

APPROACH

Near-infrared diffuse correlation spectroscopy (DCS) and, to a lesser extent, diffuse correlation tomography (DCT), have increasingly received interest over the past decade as noninvasive methods for tissue blood flow measurements and imaging. DCS/DCT offers several attractive features for tissue blood flow measurements/imaging such as noninvasiveness, portability, high temporal resolution, and relatively large penetration depth (up to several centimeters).

MAIN RESULTS

This review first introduces the basic principle and instrumentation of DCS/DCT, followed by presenting clinical application examples of DCS/DCT for the diagnosis and therapeutic monitoring of diseases in a variety of organs/tissues including brain, skeletal muscle, and tumor.

SIGNIFICANCE

Clinical study results demonstrate technical versatility of DCS/DCT in providing important information for disease diagnosis and intervention monitoring.

Derivation of the correlation diffusion equation with static background and analytical solutions

A new correlation diffusion equation has been derived from a correlation transport equation allowing one to take into account the presence of moving scatterers and static background. Solutions for the reflectance from a semi-infinite medium have been obtained (point-like and ring detectors). The solutions have been tested by comparisons with "gold standard" Monte Carlo (MC) simulations. These formulas suitably describe the electric field autocorrelation function, for Brownian or random movement of the scatterers, even in the case where the probability for a photon to interact with a moving scatterer is very low. The proposed analytical models and the MC simulations show that the "classical" model, often used in diffuse correlation spectroscopy, underestimates the normalized field autocorrelation function for increasing correlation times.

Pressure injury prediction using diffusely scattered light

Pressure injuries (PIs) originate beneath the surface of the skin at the interface between bone and soft tissue. We used diffuse correlation spectroscopy (DCS) and diffuse near-infrared spectroscopy (DNIRS) to predict the development of PIs by measuring dermal and subcutaneous red cell motion and optical absorption and scattering properties in 11 spinal cord injury subjects with only nonbleachable redness in the sacrococcygeal area in a rehabilitation hospital and 20 healthy volunteers. A custom optical probe was developed to obtain continuous DCS and DNIRS data from sacrococcygeal tissue while the subjects were placed in supine and lateral positions to apply pressure from body weight and to release pressure, respectively. Rehabilitation patients were measured up to four times over a two-week period. Three rehabilitation patients developed open PIs (POs) within four weeks and eight patients did not (PNOs). Temporal correlation functions in the area of redness were significantly different ( p < 0.01 ) during both baseline and applied pressure stages for POs and PNOs. The results show that our optical method may be used for the early prediction of ulcer progression.

Theoretical model of blood flow measurement by diffuse correlation spectroscopy

Diffuse correlation spectroscopy (DCS) is a noninvasive method to quantify tissue perfusion from measurements of the intensity temporal autocorrelation function of diffusely scattered light. However, DCS autocorrelation function measurements in tissue better match theoretical predictions based on the diffusive motion of the scatterers than those based on a model where the advective nature of blood flow dominates the stochastic properties of the scattered light. We have recently shown using Monte Carlo (MC) simulations and assuming a simplistic vascular geometry and laminar flow profile that the diffusive nature of the DCS autocorrelation function decay is likely a result of the shear-induced diffusion of the red blood cells. Here, we provide theoretical derivations supporting and generalizing the previous MC results. Based on the theory of diffusing-wave spectroscopy, we derive an expression for the autocorrelation function along the photon path through a vessel that takes into account both diffusive and advective scatterer motion, and we provide the solution for the DCS autocorrelation function in a semi-infinite geometry. We also derive the correlation diffusion and correlation transfer equation, which can be applied for an arbitrary sample geometry. Further, we propose a method to take into account realistic vascular morphology and flow profile.

Joint blood flow is more sensitive to inflammatory arthritis than oxyhemoglobin, deoxyhemoglobin, and oxygen saturation

Joint hypoxia plays a central role in the progression and perpetuation of rheumatoid arthritis (RA). Thus, optical techniques that can measure surrogate markers of hypoxia such as blood flow, oxyhemoglobin, deoxyhemoglobin, and oxygen saturation are being developed to monitor RA. The purpose of the current study was to compare the sensitivity of these physiological parameters to arthritis. Experiments were conducted in a rabbit model of RA and the results revealed that joint blood flow was the most sensitive to arthritis and could detect a statistically significant difference (p<0.05, power = 0.8) between inflamed and healthy joints with a sample size of only four subjects. Considering that this a quantitative technique, the high sensitivity to arthritis suggests that joint perfusion has the potential to become a potent tool for monitoring disease progression and treatment response in RA.

Lawrence K. Assessment of a multi-layered diffuse correlation spectroscopy method for monitoring cerebral blood flow in adults

Diffuse correlation spectroscopy (DCS) is a promising technique for brain monitoring as it can provide a continuous signal that is directly related to cerebral blood flow (CBF); however, signal contamination from extracerebral tissue can cause flow underestimations. The goal of this study was to investigate whether a multi-layered (ML) model that accounts for light propagation through the different tissue layers could successfully separate scalp and brain flow when applied to DCS data acquired at multiple source-detector distances. The method was first validated with phantom experiments. Next, experiments were conducted in a pig model of the adult head with a mean extracerebral tissue thickness of 9.8 ± 0.4 mm. Reductions in CBF were measured by ML DCS and computed tomography perfusion for validation; excellent agreement was observed by a mean difference of 1.2 ± 4.6% (CI_95%: -31.1 and 28.6) between the two modalities, which was not significantly different.