Measurements of time-resolved reflectance from a homogenous turbid medium can be employed to retrieve the absolute values of its optical transport coefficients. However, the uncertainty in the temporal shift of the experimentally determined instrument response function (IRF) with respect to the real system response can lead to errors in optical property reconstructions. Instrument noise and measurement of the IRF in a reflectance geometry can exacerbate these errors. Here, we examine three reconstruction approaches that avoid requiring direct measurements of photon launch times. They work by (a) fitting relative shapes of the reflectance profile with a pre-determined constraint on the scattering coefficient, (b) calibrating launch-time differences via a reference sample, and (c) freely fitting for the launch-time difference within the inverse problem. Analysis methods that can place a tight bound on the scattering coefficient can produce errors within 5-15% for both absorption and scattering at source-detector separations of 10 and 15 mm. Including the time-shift in the fitting procedure also recovered optical coefficients to under 20% but showed large crosstalk between extracted scattering and absorption coefficients. We find that the uncertainty in the temporal shift greatly impacts the reconstructed reduced scattering coefficient compared to absorption.
Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique that can measure brain perfusion by quantifying temporal intensity fluctuations of multiply scattered light. A primary limitation for accurate quantitation of cerebral blood flow (CBF) is the fact that experimental measurements contain information about both extracerebral scalp blood flow (SBF) as well as CBF. Separating CBF from SBF is typically achieved using multiple source-detector channels when using continuous-wave (CW) light sources, or more recently with use of time-domain (TD) techniques. Analysis methods that account for these partial volume effects are often employed to increase CBF contrast. However, a robust, real-time analysis procedure that can separate and quantify SBF and CBF with both traditional CW and TD-DCS measurements is still needed. Here, we validate a data analysis procedure based on the diffusion equation in layered media capable of quantifying both extra- and cerebral blood flow in the CW and TD. We find that the model can quantify SBF and CBF coefficients with less than 5% error compared to Monte Carlo simulations using a 3-layered brain model in both the CW and TD. The model can accurately fit data at a rate of <10 ms for CW data and <250 ms for TD data when using a least-squares optimizer.
A heuristic method for estimating the reduced scattering coefficient (µs’) of turbid media using time-resolved reflectance is presented. The technique requires measurements of the distributions of times-of-flight (DTOF) of photons arriving at two identical detection channels placed at unique distances relative to a source. Measured temporal shifts in DTOF peak intensities at the two channels were used to estimate µs’ of the medium using Monte Carlo (MC) simulation-based lookup tables. MC simulations were used to compute temporal shifts in modeled reflectance at experimentally employed source-detector separations (SDS) for media spanning a wide range of optical properties to construct look up tables. Experiments in Intralipid (IL) phantoms demonstrated that we could retrieve µs’ with errors ranging between 6-25% of expected (literature) values, using reflectance measured across 650-800 nm and SDS of 5-15 mm. Advantages of the technique include direct processing of measured data without requiring iterative non-linear curve fitting. We also discuss applicability of this approach for media with low scattering coefficients where the commonly employed diffusion theory analysis could be inaccurate, with practical recommendations for use.
In reconstructive surgery, the ability to detect blood flow interruptions to grafted tissue represents a critical step in preventing postsurgical complications. We have developed and pilot tested a compact, fiber-based device that combines two complimentary modalities-diffuse correlation spectroscopy (DCS) and diffuse reflectance spectroscopy-to quantitatively monitor blood perfusion. We present a proof-of-concept study on an in vivo porcine model (n=8). With a controllable arterial blood flow supply, occlusion studies (n=4) were performed on surgically isolated free flaps while the device simultaneously monitored blood flow through the supplying artery as well as flap perfusion from three orientations: the distal side of the flap and two transdermal channels. Further studies featuring long-term monitoring, arterial failure simulations, and venous failure simulations were performed on flaps that had undergone an anastomosis procedure (n=4). Additionally, benchtop verification of the DCS system was performed on liquid flow phantoms. Data revealed relationships between diffuse optical measures and state of occlusion as well as the ability to detect arterial and venous compromise. The compact construction of the device, along with its noninvasive and quantitative nature, would make this technology suitable for clinical translation.
It is essential to monitor tissue perfusion during and after reconstructive surgery, as restricted blood flow can result in graft failures. Current clinical procedures are insufficient to monitor tissue perfusion, as they are intermittent and often subjective. To address this unmet clinical need, a compact, low-cost, multimodal diffuse correlation spectroscopy and diffuse reflectance spectroscopy system was developed. We verified system performance via tissue phantoms and experimental protocols for rigorous bench testing. Quantitative data analysis methods were employed and tested to enable the extraction of tissue perfusion parameters. This design verification study assures data integrity in future in vivo studies.
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