Smart-Dust-Nanorice for Enhancement of Endogenous Raman Signal, Contrast in Photoacoustic Imaging, and T2-Shortening in Magnetic Resonance Imaging.

Raman microspectroscopy provides chemo-selective image contrast, sub-micrometer resolution, and multiplexing capabilities. However, it suffers from weak signals resulting in image-acquisition times of up to several hours. Surface-enhanced Raman scattering (SERS) can dramatically enhance signals of molecules in close vicinity of metallic surfaces and overcome this limitation.

Comparison of Deconvolution Filters for Photoacoustic Tomography.

In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain.

Cellulose Nanoparticles are a Biodegradable Photoacoustic Contrast Agent for Use in Living Mice.

Molecular imaging with photoacoustic ultrasound is an emerging field that combines the spatial and temporal resolution of ultrasound with the contrast of optical imaging. However, there are few imaging agents that offer both high signal intensity and biodegradation into small molecules. Here we describe a cellulose-based nanoparticle with peak photoacoustic signal at 700 nm and an limit of detection of 6 pM (0.

Development and application of stable phantoms for the evaluation of photoacoustic imaging instruments.

Photoacoustic imaging combines the high contrast of optical imaging with the spatial resolution and penetration depth of ultrasound. This technique holds tremendous potential for imaging in small animals and importantly, is clinically translatable. At present, there is no accepted standard physical phantom that can be used to provide routine quality control and performance evaluation of photoacoustic imaging instruments.

High-sensitivity, real-time, ratiometric imaging of surface-enhanced Raman scattering nanoparticles with a clinically translatable Raman endoscope device.

Topical application and quantification of targeted, surface-enhanced Raman scattering (SERS) nanoparticles offer a new technique that has the potential for early detection of epithelial cancers of hollow organs. Although less toxic than intravenous delivery, the additional washing required to remove unbound nanoparticles cannot necessarily eliminate nonspecific pooling. Therefore, we developed a real-time, ratiometric imaging technique to determine the relative concentrations of at least two spectrally unique nanoparticle types, where one serves as a nontargeted control.

A small animal Raman instrument for rapid, wide-area, spectroscopic imaging.

Raman spectroscopy, amplified by surface enhanced Raman scattering (SERS) nanoparticles, is a molecular imaging modality with ultra-high sensitivity and the unique ability to multiplex readouts from different molecular targets using a single wavelength of excitation. This approach holds exciting prospects for a range of applications in medicine, including identification and characterization of malignancy during endoscopy and intraoperative image guidance of surgical resection. The development of Raman molecular imaging with SERS nanoparticles is presently limited by long acquisition times, poor spatial resolution, small field of view, and difficulty in animal handling with existing Raman spectroscopy instruments.

A Raman-based endoscopic strategy for multiplexed molecular imaging.

Endoscopic imaging is an invaluable diagnostic tool allowing minimally invasive access to tissues deep within the body. It has played a key role in screening colon cancer and is credited with preventing deaths through the detection and removal of precancerous polyps. However, conventional white-light endoscopy offers physicians structural information without the biochemical information that would be advantageous for early detection and is essential for molecular typing.

Gold nanorods for ovarian cancer detection with photoacoustic imaging and resection guidance via Raman imaging in living mice.

Improved imaging approaches are needed for ovarian cancer screening, diagnosis, staging, and resection guidance. Here, we propose a combined photoacoustic (PA)/Raman approach using gold nanorods (GNRs) as a passively targeted molecular imaging agent. GNRs with three different aspect ratios were studied.

Improving image quality by accounting for changes in water temperature during a photoacoustic tomography scan.

The emerging field of photoacoustic tomography is rapidly evolving with many new system designs and reconstruction algorithms being published. Many systems use water as a coupling medium between the scanned object and the ultrasound transducers. Prior to a scan, the water is heated to body temperature to enable small animal imaging.

A hybrid least squares and principal component analysis algorithm for Raman spectroscopy.

Raman spectroscopy is a powerful technique for detecting and quantifying analytes in chemical mixtures. A critical part of Raman spectroscopy is the use of a computer algorithm to analyze the measured Raman spectra. The most commonly used algorithm is the classical least squares method, which is popular due to its speed and ease of implementation.

A hybrid least squares and principal component analysis algorithm for Raman spectroscopy.

The least squares fitting algorithm is the most commonly used algorithm in Raman spectroscopy. In this paper, however, we show that it is sensitive to variations in the background signal when the signal of interest is weak. To address this problem, we propose a novel algorithm to analyze measured spectra in Raman spectroscopy.

Regularising limited view tomography using anatomical reference images and information theoretic similarity metrics.

This paper is concerned with limited view tomography. Inspired by the application of digital breast tomosynthesis (DBT), which is but one of an increasing number of applications of limited view tomography, we concentrate primarily on cases where the angular range is restricted to a narrow wedge of approximately ±30°, and the number of views is restricted to 10-30. The main challenge posed by these conditions is undersampling, also known as the null space problem.

Avoiding local optima of the joint entropy prior in limited view tomography using a multiresolution scheme.

The incorporation of anatomical reference images into limited view transmission tomography has been attempted previously by using the joint entropy prior. However, this prior has been found to be sensitive to local optima. Here, we propose to increase robustness to local optima by using a multiresolution optimisation scheme.

Model of accommodation: contributions of lens geometry and mechanical properties to the development of presbyopia.

Purpose: To determine the relative importance of lens geometry and mechanical properties for the mechanics of accommodation and the role of these elements in the causes and potential correction of presbyopia.

Setting: Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey, USA.

Design: Experimental study.

Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers.

We assess the performance of filtered backprojection (FBP), the simultaneous algebraic reconstruction technique (SART) and the maximum likelihood (ML) algorithm for digital breast tomosynthesis (DBT) under variations in key imaging parameters, including the number of iterations, number of projections, angular range, initial guess, and radiation dose. This is the first study to compare these algorithms for the application of DBT. We present a methodology for the evaluation of DBT reconstructions, and use it to conduct preliminary experiments investigating trade-offs between the selected imaging parameters.

Simultaneous reconstruction and registration algorithm for limited view transmission tomography using a multiple cluster approximation to the joint histogram with an anatomical prior.

We develop a novel simultaneous reconstruction and registration algorithm for limited view transmission tomography. We derive a cost function using Bayesian probability theory, and propose a similarity metric based on the explicit modeling of the joint histogram as a sum of bivariate clusters. The resulting algorithm shows a robust mitigation of the data insufficiency problem in limited view tomography.

Robust joint entropy regularization of limited view transmission tomography using Gaussian approximations to the joint histogram.

Information theoretic measures to incorporate anatomical priors have been explored in the field of emission tomography, but not in transmission tomography. In this work, we apply the joint entropy prior to the case of limited angle transmission tomography. Due to the data insufficiency problem, the joint entropy prior is found to be very sensitive to local optima.

A systematic performance analysis of the simultaneous algebraic reconstruction technique (SART) for limited angle tomography.

The design of limited angle tomography systems requires the optimization of various imaging parameters in order to achieve useful as well as reliable results. Algebraic reconstruction techniques, specifically the SART algorithm, have given excellent results in CT and are being actively considered for limited angle commercial applications such as tomosynthesis. In this study, we simulate a range of limited angle scenarios by systematically varying a number of key imaging parameters, and examine the performance of the SART algorithm under these variations.

Modelling of experimentally created partial-thickness human skin burns and subsequent therapeutic cooling: a new measure for cooling effectiveness.

Rapid post-injury cooling of a skin burn has been shown to have both symptomatic and therapeutic benefits. However, the latter cannot be explained by temperature reduction alone, and must thus be secondary to an altered biological response. In this study, we construct a computational model to calculate the heat transfer and damage accumulation in human skin during and after a burn.