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In this work we introduce a modified form of laser speckle imaging (LSI) referred to as affixed transmission speckle analysis (ATSA) that uses a single coherent light source to probe two physiological signals: one related to pulsatile vascular expansion (classically known as the photoplethysmographic (PPG) waveform) and one related to pulsatile vascular blood flow (named here the speckle plethysmographic (SPG) waveform). The PPG signal is determined by recording intensity fluctuations, and the SPG signal is determined via the LSI dynamic light scattering technique. These two co-registered signals are obtained by transilluminating a single digit (e.g. finger) which produces quasi-periodic waveforms derived from the cardiac cycle. Because PPG and SPG waveforms probe vascular expansion and flow, respectively, in cm-thick tissue, these complementary phenomena are offset in time and have rich dynamic features. We characterize the timing offset and harmonic content of the waveforms in 16 human subjects and demonstrate physiologic relevance for assessing microvascular flow and resistance.

In this work we introduce a modified form of laser speckle imaging (LSI) referred to as affixed transmission speckle analysis (ATSA) that uses a single coherent light source to probe two physiological signals: one related to pulsatile vascular expansion (classically known as the photoplethysmographic (PPG) waveform) and one related to pulsatile vascular blood flow (named here the speckle plethysmographic (SPG) waveform). The PPG signal is determined by recording intensity fluctuations, and the SPG signal is determined via the LSI dynamic light scattering technique. These two co-registered signals are obtained by transilluminating a single digit (e.g. finger) which produces quasi-periodic waveforms derived from the cardiac cycle. Because PPG and SPG waveforms probe vascular expansion and flow, respectively, in cm-thick tissue, these complementary phenomena are offset in time and have rich dynamic features. We characterize the timing offset and harmonic content of the waveforms in 16 human subjects and demonstrate physiologic relevance for assessing microvascular flow and resistance.

We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI.

We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI.

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

There is a need for cost effective, quantitative tissue spectroscopy and imaging systems in clinical diagnostics and pre-clinical biomedical research. A platform that utilizes a commercially available light-emitting diode (LED) based projector, cameras, and scaled Monte Carlo model for calculating tissue optical properties is presented. These components are put together to perform spatial frequency domain imaging (SFDI), a model-based reflectance technique that measures and maps absorption coefficients (μa) and reduced scattering coefficients (μs') in thick tissue such as skin or brain. We validate the performance of the flexible LED and modulation element (FLaME) system at 460, 530, and 632 nm across a range of physiologically relevant μa values (0.07 to 1.5  mm-1) in tissue-simulating intralipid phantoms, showing an overall accuracy within 11% of spectrophotometer values for μa and 3% for μs'. Comparison of oxy- and total hemoglobin fits between the FLaME system and a spectrophotometer (450 to 1000 nm) is differed by 3%. Finally, we acquire optical property maps of a mouse brain in vivo with and without an overlying saline well. These results demonstrate the potential of FLaME to perform tissue optical property mapping in visible spectral regions and highlight how the optical clearing effect of saline is correlated to a decrease in μs' of the skull.

The feasibility of spatial frequency domain imaging (SFDI) for breast surgical margin assessment was evaluated in tissue-simulating phantoms and in fully intact lumpectomy specimens at the time of surgery. Phantom data was evaluated according to contrast-detail resolution, quantitative accuracy and model-data goodness of fit, where optical parameters were estimated by minimizing the residual sum of squares between the measured modulation amplitude and its solutions, modeled according to diffusion and scaled-Monte Carlo simulations. In contrast-detail phantoms, a 1.25-mm-diameter surface inclusion was detectable for scattering contrast >28%; a fraction of this scattering contrast (7%) was detectable for a 10 mm surface inclusion and at least 33% scattering contrast was detected up to 1.5 mm below the phantom surface, a probing depth relevant to breast surgical margin assessment. Recovered hemoglobin concentrations were insensitive to changes in scattering, except for overestimation at visible wavelengths for total hemoglobin concentrations

The feasibility of spatial frequency domain imaging (SFDI) for breast surgical margin assessment was evaluated in tissue-simulating phantoms and in fully intact lumpectomy specimens at the time of surgery. Phantom data was evaluated according to contrast-detail resolution, quantitative accuracy and model-data goodness of fit, where optical parameters were estimated by minimizing the residual sum of squares between the measured modulation amplitude and its solutions, modeled according to diffusion and scaled-Monte Carlo simulations. In contrast-detail phantoms, a 1.25-mm-diameter surface inclusion was detectable for scattering contrast >28%; a fraction of this scattering contrast (7%) was detectable for a 10 mm surface inclusion and at least 33% scattering contrast was detected up to 1.5 mm below the phantom surface, a probing depth relevant to breast surgical margin assessment. Recovered hemoglobin concentrations were insensitive to changes in scattering, except for overestimation at visible wavelengths for total hemoglobin concentrations

Laser speckle imaging (LSI) is a fast, noninvasive method to obtain relative particle dynamics in highly light scattering media, such as biological tissue. To make quantitative measurements, we combine LSI with spatial frequency domain imaging, a technique where samples are illuminated with sinusoidal intensity patterns of light that control the characteristic path lengths of photons in the sample. We use both diffusion and radiative transport to predict the speckle contrast of coherent light remitted from turbid media. We validate our technique by measuring known Brownian diffusion coefficients (D(b)) of scattering liquid phantoms. Monte Carlo (MC) simulations of radiative transport were found to provide the most accurate contrast predictions. For polystyrene microspheres of radius 800 nm in water, the expected and fit D(b) using radiative transport were 6.10E-07 and 7.10E-07 mm²/s, respectively. For polystyrene microspheres of radius 1026 nm in water, the expected and fit D(b) were 4.7E-07 and 5.35 mm²/s, respectively. For scattering particles in water-glycerin solutions, the fit fractional changes in D(b) with changes in viscosity were all found to be within 3% of the expected value.

Laser speckle imaging (LSI) is a fast, noninvasive method to obtain relative particle dynamics in highly light scattering media, such as biological tissue. To make quantitative measurements, we combine LSI with spatial frequency domain imaging, a technique where samples are illuminated with sinusoidal intensity patterns of light that control the characteristic path lengths of photons in the sample. We use both diffusion and radiative transport to predict the speckle contrast of coherent light remitted from turbid media. We validate our technique by measuring known Brownian diffusion coefficients (D(b)) of scattering liquid phantoms. Monte Carlo (MC) simulations of radiative transport were found to provide the most accurate contrast predictions. For polystyrene microspheres of radius 800 nm in water, the expected and fit D(b) using radiative transport were 6.10E-07 and 7.10E-07 mm²/s, respectively. For polystyrene microspheres of radius 1026 nm in water, the expected and fit D(b) were 4.7E-07 and 5.35 mm²/s, respectively. For scattering particles in water-glycerin solutions, the fit fractional changes in D(b) with changes in viscosity were all found to be within 3% of the expected value.