We present a photoacoustic computed tomography investigation on a healthy human finger, to image blood vessels with a focus on vascularity across the interphalangeal joints. The cross-sectional images were acquired using an imager specifically developed for this purpose. The images show rich detail of the digital blood vessels with diameters between 100 µm and 1.5 mm in various orientations and at various depths. Different vascular layers in the skin including the subpapillary plexus could also be visualized.Acoustic reflections on the finger bone of photoacoustic signals from skin were visible in sequential slice images along the finger except at the location of the joint gaps. Not unexpectedly, the healthy synovial membrane at the joint gaps was not detected due to its small size and normal vascularization. Future research will concentrate on studying digits afflicted with rheumatoid arthritis to detect the inflamed synovium with its heightened vascularization, whose characteristics are potential markers for disease activity.
Photoacoustic (PA) imaging of interphalangeal peripheral joints is of interest in the context of using the synovial membrane as a surrogate marker of rheumatoid arthritis. Previous work has shown that ultrasound (US) produced by absorption of light at the epidermis reflects on the bone surfaces within the finger. When the reflected signals are backprojected in the region of interest, artifacts are produced, confounding interpretation of the images. In this work, we present an approach where the PA signals known to originate from the epidermis are treated as virtual US transmitters, and a separate reconstruction is performed as in US reflection imaging. This allows us to identify the bone surfaces. Furthermore, the identification of the joint space is important as this provides a landmark to localize a region-of-interest in seeking the inflamed synovial membrane. The ability to delineate bone surfaces allows us to identify not only the artifacts but also the interphalangeal joint space without recourse to new US hardware or a new measurement. We test the approach on phantoms and on a healthy human finger.
This study examines one of the open problems yet to solve in photoacoustic tomography: How to prepare photoacoustic signals to ensure interpretation as projection data? The main part of this difficulty is related to the setting of the linear photoacoustic transport model. Notably errors are due to the discrepancy between the mathematical reconstruction and the physical realization: Tomographic image reconstruction from projections require a linear acquisition system. However in practice, the physical reality presents different non-linear phenomena. In account of this incompatibility, it was our purpose to provide some advancement in signal processing for dealing the projection issue while considering different perspectives in the interpretation of the transport model to be applied in a broader manner. Numerical examples are analyzed in detail and unveil the foundations for photoacoustic signal processing methodologies focused on the task of tomographic image reconstruction from projections.
SummaryGold nanoparticles are rapidly emerging for use in biomedical applications. Characterization of the interaction and delivery of nanoparticles to cells through microscopy is important. Scanning electron microscopes have the intrinsic resolution to visualize gold nanoparticles on cells. A novel sample preparation protocol was developed to enable imaging of cells and gold nanoparticles with a conventional below lens scanning electron microscopes. The negative influence of 'charging' on the quality of scanning electron microscopes' images could be limited by deposition of biological cells on a conductive (gold) surface. The novel protocol enabled highresolution scanning electron microscopes' imaging of small clusters and individual gold nanoparticles on uncoated cell surfaces. Gold nanoparticles could be counted on cancer cells with automated routines.
We present, perhaps for the first time, a stochastic search algorithm in quantitative photoacoustic tomography (QPAT) for a one-step recovery of the optical absorption map from time-resolved photoacoustic signals. Such a direct recovery is free of the numerical inaccuracies inherent in conventional two-step approaches that depend on an accurate estimation of the absorbed energy distribution. The absorption profile parameterized as a vector stochastic process is additively updated over time recursions so as to drive the measurement-prediction misfit to a zero-mean white noise. The derivative-free additive update is a welcome departure from the conventional gradient-based methods requiring evaluation of Jacobians at every recursion. The quantitative accuracy of the recovered absorption map from both numerical and experimental data is good with an overall error of less than 10%.
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