A simple algorithm for diffuse optical tomography without Jacobian inversion.

A computationally simpler algorithm to reconstruct the optical property distribution of turbid media using diffuse optical tomographic principles is presented. The proposed algorithm eliminates the requirement of large Jacobian matrix inversion which otherwise is essential for tomographic imaging. The most significant Jacobians are identified based on proper thresholding of the measurement and the intersection of these Jacobians gives the approximate spatial location of the inhomogeneity. The algorithm is tested and optimized using simulations and further validated using tissue-mimicking phantom-based experiments andin-vivosmall-animal experiments.

Laser speckle simulation tool based on stochastic differential equations for bio imaging applications.

Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from in-vivo studies in mice and healthy human subject.

High-density diffuse correlation tomography with enhanced depth localization and minimal surface artefacts.

A spatially weighted filter applied to both the measurement and the Jacobian is proposed for high-density diffuse correlation tomography (DCT) to remove unwanted extracerebral interferences and artefacts along with better depth localization in the reconstructed blood flow images. High-density DCT is implemented by appropriate modification of recently introduced Multi-speckle Diffuse Correlation Spectroscopy (M-DCS) system. Additionally, we have used autocorrelation measurements at multiple delay-times in an iterative manner to improve the reconstruction results. The proposed scheme has been validated by simulations, phantom experiments and in-vivo human experiments.

Multi-speckle diffuse correlation spectroscopy to measure cerebral blood flow.

We present a multi-speckle diffuse correlation spectroscopy (DCS) system for measuring cerebral blood flow in the healthy adult human brain. In contrast to the need for a high frame rate camera to measure the multi-speckle intensity auto-correlation, we employ a low frame rate camera to measure the auto-correlation using the recently introduced multi-step volterra integral method (MVIM). The results are validated by comparison against the blood flow measured using standard DCS system.

On the equivalence of speckle contrast-based and diffuse correlation spectroscopy methods in measuring in vivo blood flow.

We establish the equivalence between laser speckle contrast-based and diffuse correlation spectroscopy methods inin vivo imaging of blood flow using the Volterra integral equation theory. We further substantiate the need of regularized fitting while employing the multiexposure speckle contrast imaging to recover autocorrelation function.

Recovery of the diffuse correlation spectroscopy data-type from speckle contrast measurements: towards low-cost, deep-tissue blood flow measurements.

A multi-step Volterra integral equation-based algorithm was developed to measure the electric field auto-correlation function from multi-exposure speckle contrast data. This enabled us to derive an estimate of the full diffuse correlation spectroscopy data-type from a low-cost, camera-based system. This method is equally applicable for both single and multiple scattering field auto-correlation models. The feasibility of the system and method was verified using simulation studies, tissue mimicking phantoms and subsequently in in vivo experiments.

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.

High-speed multi-exposure laser speckle contrast imaging with a single-photon counting camera.

Laser speckle contrast imaging (LSCI) has emerged as a valuable tool for cerebral blood flow (CBF) imaging. We present a multi-exposure laser speckle imaging (MESI) method which uses a high-frame rate acquisition with a negligible inter-frame dead time to mimic multiple exposures in a single-shot acquisition series. Our approach takes advantage of the noise-free readout and high-sensitivity of a complementary metal-oxide-semiconductor (CMOS) single-photon avalanche diode (SPAD) array to provide real-time speckle contrast measurement with high temporal resolution and accuracy. To demonstrate its feasibility, we provide comparisons between in vivo measurements with both the standard and the new approach performed on a mouse brain, in identical conditions.

Speckle contrast optical spectroscopy, a non-invasive, diffuse optical method for measuring microvascular blood flow in tissue.

We introduce a new, non-invasive, diffuse optical technique, speckle contrast optical spectroscopy (SCOS), for probing deep tissue blood flow using the statistical properties of laser speckle contrast and the photon diffusion model for a point source. The feasibility of the method is tested using liquid phantoms which demonstrate that SCOS is capable of measuring the dynamic properties of turbid media non-invasively. We further present an in vivo measurement in a human forearm muscle using SCOS in two modalities: one with the dependence of the speckle contrast on the source-detector separation and another on the exposure time. In doing so, we also introduce crucial corrections to the speckle contrast that account for the variance of the shot and sensor dark noises.

Speckle contrast optical tomography: A new method for deep tissue three-dimensional tomography of blood flow.

A novel tomographic method based on the laser speckle contrast, speckle contrast optical tomography (SCOT) is introduced that allows us to reconstruct three dimensional distribution of blood flow in deep tissues. This method is analogous to the diffuse optical tomography (DOT) but for deep tissue blood flow. We develop a reconstruction algorithm based on first Born approximation to generate three dimensional distribution of flow using the experimental data obtained from tissue simulating phantoms.

Mannose-binding lectin promotes local microvascular thrombosis after transient brain ischemia in mice.

BACKGROUND AND PURPOSE: Several lines of evidence support the involvement of mannose-binding lectin (MBL) in stroke brain damage. The lectin pathway of the complement system facilitates thrombin activation and clot formation under certain experimental conditions. In the present study, we examine whether MBL promotes thrombosis after ischemia/reperfusion and influences the course and prognosis of ischemic stroke. METHODS: Middle cerebral artery occlusion/reperfusion was performed in MBL-deficient (n=85) and wild-type (WT; n=83) mice, and the brain lesion was assessed by MRI at days 1 and 7. Relative cerebral blood flow was monitored up to 6 hours after middle cerebral artery occlusion with laser speckle contrast imaging. Fibrin(ogen) was analyzed in the brain vasculature and plasma, and the effects of thrombin inhibitor argatroban were evaluated to assess the role of MBL in thrombin activation. RESULTS: Infarct volumes and neurological deficits were smaller in MBL knockout mice than in WT mice. Relative cerebral blood flow values during middle cerebral artery occlusion and at reperfusion were similar in both groups, but decreased during the next 6 hours in the WT group only. Also, the WT mice showed more fibrin(ogen) in brain vessels and a better outcome after argatroban treatment. In contrast, argatroban did not improve the outcome in MBL knockout mice. CONCLUSIONS: MBL promotes brain damage and functional impairment after brain ischemia/reperfusion in mice. These effects are secondary to intravascular thrombosis and impaired relative cerebral blood flow during reperfusion. Argatroban protects WT mice, but not MBL knockout mice, emphasizing a role of MBL in local thrombus formation in acute ischemia/reperfusion.

Ultrasound-modulated optical tomography: recovery of amplitude of vibration in the insonified region from boundary measurement of light correlation.

We address a certain inverse problem in ultrasound-modulated optical tomography: the recovery of the amplitude of vibration of scatterers [p(r)] in the ultrasound focal volume in a diffusive object from boundary measurement of the modulation depth (M) of the amplitude autocorrelation of light [φ(r,τ)] traversing through it. Since M is dependent on the stiffness of the material, this is the precursor to elasticity imaging. The propagation of φ(r,τ) is described by a diffusion equation from which we have derived a nonlinear perturbation equation connecting p(r) and refractive index modulation [Δn(r)] in the region of interest to M measured on the boundary. The nonlinear perturbation equation and its approximate linear counterpart are solved for the recovery of p(r). The numerical results reveal regions of different stiffness, proving that the present method recovers p(r) with reasonable quantitative accuracy and spatial resolution.

Convergence analysis of the Newton algorithm and a pseudo-time marching scheme for diffuse correlation tomography.

We propose a self-regularized pseudo-time marching scheme to solve the ill-posed, nonlinear inverse problem associated with diffuse propagation of coherent light in a tissuelike object. In particular, in the context of diffuse correlation tomography (DCT), we consider the recovery of mechanical property distributions from partial and noisy boundary measurements of light intensity autocorrelation. We prove the existence of a minimizer for the Newton algorithm after establishing the existence of weak solutions for the forward equation of light amplitude autocorrelation and its Fréchet derivative and adjoint. The asymptotic stability of the solution of the ordinary differential equation obtained through the introduction of the pseudo-time is also analyzed. We show that the asymptotic solution obtained through the pseudo-time marching converges to that optimal solution provided the Hessian of the forward equation is positive definite in the neighborhood of optimal solution. The superior noise tolerance and regularization-insensitive nature of pseudo-dynamic strategy are proved through numerical simulations in the context of both DCT and diffuse optical tomography.

Study of turbid media with light: recovery of mechanical and optical properties from boundary measurement of intensity autocorrelation of light.

We discuss the inverse problem associated with the propagation of the field autocorrelation of light through a highly scattering object like tissue. In the first part of the work, we reconstruct the optical absorption coefficient mu(a) and particle diffusion coefficient D(B) from simulated measurements which are integrals of a quantity computed from the measured intensity and intensity autocorrelation g(2)(tau) at the boundary. In the second part we recover the mean square displacement (MSD) distribution of particles in an inhomogeneous object from the sampled g(2)(tau) measured on the boundary. From the MSD, we compute the storage and loss moduli distributions in the object. We have devised computationally easy methods to construct the sensitivity matrices which are used in the iterative reconstruction algorithms for recovering these parameters from the measurements. The results of the reconstruction of mu(a), D(B), MSD and the viscoelastic parameters, which are presented, show reasonably good position and quantitative accuracy.

Direct reconstruction of complex refractive index distribution from boundary measurement of intensity and normal derivative of intensity.

We present an optical tomographic reconstruction method to recover the complex refractive index distribution from boundary measurements based on intensity, which are the logarithm of intensity and normal derivative of intensity. The method, which is iterative, repeatedly implements the forward propagation equation for light amplitude, the Helmholtz equation, and computes appropriate sensitivity matrices for these measurements. The sensitivity matrices are computed by solving the forward propagation equation for light and its adjoint. The results of numerical experiments show that the data types ln(I) and partial differential I/ partial differential n reconstructed, respectively, the imaginary and the real part of the object refractive index distribution. Moreover, the imaginary part of the refractive index reconstructed from partial differential I/ partial differential n and the real part from ln(I) failed to show the object's inhomogeneity. The value of the propagation constant, k, used in our simulations was 50, and this value resulted in smoothing of the reconstructed inhomogeneities. Thus we have shown that it is possible to reconstruct the complex refractive index distribution directly from the measured intensity without having to first find the light amplitude, as is done in most of the currently available reconstruction algorithms of diffraction tomography.