Near-infrared Tomographic Imaging Research Articles

Wavelength optimization using available laser diodes in spectral near-infrared optical tomography.

For employing optimized wavelengths, a near-infrared (NIR) tomographic imaging system with multiwavelengths in a continuous wave (CW) enables us to provide accurate information of chromophores. In this paper, we discuss wavelength optimization with a selection from commercial laser diodes. Through theoretical analysis, the residual norm (R) and the condition number (κ) represent the uniqueness of a matrix problem and the smooth singular-value distribution of each chromophore, respectively. The optimum wavelengths take place for large R and small κ. We considered a total of 38wavelengths of laser diodes in the range of 633-980nm commercially available to discover optimum sets for a broad range of chromophore combinations. In the 38wavelengths, there exists 501,942 (C538), 2,760,681 (C638), and 12,620,256 (C738) combinations of five, six, and seven wavelength sets, respectively, for accurately estimating chromophores (HbO2, HbR, H2O, and lipids), water, lipids, and the scattering prefactor A. With the numerical calculation, the top 10wavelength sets were selected based on the principle of large R and small κ. In the study, the chromophore concentration for young and elderly women are investigated; finally, choosing the laser diodes with a wavelength of 650, 690, 705, 730, 870/880, 915, and 937nm is recommended either for young or elderly women to construct a spectral NIR tomographic imaging system in the CW domain. Simulated data were used to validate the claims.

Statistical analysis of nonlinearly reconstructed near-infrared tomographic images: Part I--Theory and simulations.

Near-infrared (NIR) diffuse tomography is an emerging method for imaging the interior of tissues to quantify concentrations of hemoglobin and exogenous chromophores non-invasively in vivo. It often exploits an optical diffusion model-based image reconstruction algorithm to estimate spatial property values from measurements of the light flux at the surface of the tissue. In this study, mean-squared error (MSE) over the image is used to evaluate methods for regularizing the ill-posed inverse image reconstruction problem in NIR tomography. Estimates of image bias and image standard deviation were calculated based upon 100 repeated reconstructions of a test image with randomly distributed noise added to the light flux measurements. It was observed that the bias error dominates at high regularization parameter values while variance dominates as the algorithm is allowed to approach the optimal solution. This optimum does not necessarily correspond to the minimum projection error solution, but typically requires further iteration with a decreasing regularization parameter to reach the lowest image error. Increasing measurement noise causes a need to constrain the minimum regularization parameter to higher values in order to achieve a minimum in the overall image MSE.

In vivo imaging of proteolytic activity in atherosclerosis.

Atherosclerotic plaque rupture, the most important cause of acute cardiovascular incidents, has been strongly associated with vascular inflammation. On the basis of the hypothesis that the inflammatory response and proteolysis lead to plaque rupture, we have examined the role of cathepsin B as a model proteolytic enzyme. Using western-type diet-fed apoE and apoE/endothelial NO synthase double knockout mice as models of atherosclerosis, we show (1) that cathepsin B is upregulated in atherosclerotic lesions characterized by high degrees of inflammation compared with normal aorta or silent lesions, (2) that intravenously injectable novel cathepsin B imaging beacons are highly activated within active atherosclerotic lesions and colocalize with cathepsin B immunoreactivity, and (3) that cathepsin B activity in atherosclerotic lesions can be imaged in whole animals by using a novel near-infrared tomographic imaging system. These studies indicate that cathepsin B, and potentially other proteases, may serve as a biomarker for vulnerable plaques when probed with beacons. The tomographic in vivo imaging method as well as catheter-based optical sensing methods could be readily adapted to screening and potentially to the molecular profiling of a number of proteases in vulnerable plaque in vivo.

High-resolution near-infrared tomographic imaging simulations of the rat cranium by use of a priori magnetic resonance imaging structural information

Near-infrared (NIR) optical image reconstruction that incorporates magnetic resonance image (MRI) structural data was tested in a series of simulated reconstructions. NIR diffuse tomography generally suffers from comparatively low spatial resolution. By using the fine structural detail that is available with MRI, combined with the functional information of NIR spectroscopy, it is possible to design a new image-reconstruction methodology that provides high-resolution images that are correlated with hemoglobin concentration and oxygen saturation. To test this concept a MRI spin-echo image of a rat cranium was used to obtain an outline of the bone, brain, and muscle tissues, and this information was incorporated into an iterative-based diffuse tomography reconstruction. These simulations represent what is believed to be the first attempt at evaluating a spatially constrained iterative-reconstruction MRI-NIR imaging modality for brain tissue.