3D Optoacoustic Tomography Research Articles

Single-detector 3D optoacoustic tomography via coded spatial acoustic modulation

Optoacoustic tomography (OAT) is a hybrid imaging modality that combines optical excitation with ultrasound detection and enables high-resolution visualization of optical contrasts at tissue depths in which light is completely diffused. Despite its promise in numerous research and clinical applications, OAT is limited by the technological immaturity of ultrasound detection systems. It suffers from limited element count, narrow field of view and lack of technology for spatial modulation of acoustic signals. Here we report single-detector OAT capable of high-fidelity imaging using an amplitude mask in planar geometry coded with cyclic patterns for structured spatial acoustic modulation. Our image reconstruction method maximises sensitivity, is compatible with planar signal detection, and uses only linear operations, thus avoiding artefacts associated with the nonlinear compressed-sensing inversion. We demonstrate our method for 3D OAT of complex objects and living tissue performed with only a single ultrasound detector, effectively coded into a 2D array with 1763 elements. Our method paves the way for a new generation of high-fidelity, low-cost OAT systems.

Normalization of optical fluence distribution for three-dimensional functional optoacoustic tomography of the breast.

.Significance: In three-dimensional (3D) functional optoacoustic tomography (OAT), wavelength-dependent optical attenuation and nonuniform incident optical fluence limit imaging depth and field of view and can hinder accurate estimation of functional quantities, such as the vascular blood oxygenation. These limitations hinder OAT of large objects, such as a human female breast.Aim: We aim to develop a measurement-data-driven method for normalization of the optical fluence distribution and to investigate blood vasculature detectability and accuracy for estimating vascular blood oxygenation.Approach: The proposed method is based on reasonable assumptions regarding breast anatomy and optical properties. The nonuniform incident optical fluence is estimated based on the illumination geometry in the OAT system, and the depth-dependent optical attenuation is approximated using Beer–Lambert law.Results: Numerical studies demonstrated that the proposed method significantly enhanced blood vessel detectability and improved estimation accuracy of the vascular blood oxygenation from multiwavelength OAT measurements, compared with direct application of spectral linear unmixing without optical fluence compensation. Experimental results showed that the proposed method revealed previously invisible structures in regions deeper than 15 mm and/or near the chest wall.Conclusions: The proposed method provides a straightforward and computationally inexpensive approximation of wavelength-dependent effective optical attenuation and, thus, enables mitigation of the spectral coloring effect in functional 3D OAT imaging.

In situ characterization of microparticulate optoacoustic contrast agents in an intracardiac perfusion mouse model

Extrinsically administered light-absorbing agents may greatly enhance the sensitivity and imaging performance of optoacoustic tomography (OAT). Beyond the use of targeted contrast agents in functional and molecular imaging applications, tracking of highly absorbing microparticles has recently been shown to facilitate super-resolution volumetric angiography and mapping of blood flow. However, in vivo characterization of new types of microparticulate absorbing agents is often hindered due to their potential toxicity, incompatible dimensions, or sub-optimal extinction spectrum shadowed by strong background absorption of hemoglobin. Herein, we used an intracardiac perfusion mouse model to individually track the perfusion of absorbing particles through the cerebral vasculature by acquiring a sequence of high-frame-rate 3D OAT images. The particles were injected in the left ventricle of the heart after substitution of blood by an artificial cerebrospinal fluid post mortem, which has further contributed to minimizing the background OAT signals induced by hemoglobin absorption. The presented approach can greatly aid the development of new microparticulate contrast agents with optimized performance for various OAT imaging applications.

Accelerating image reconstruction in three-dimensional optoacoustic tomography on graphics processing units

Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming techniques. Parallelization strategies are proposed to accelerate a filtered backprojection (FBP) algorithm and two different pairs of projection/backprojection operations that correspond to two different numerical imaging models. The algorithms are designed to fully exploit the parallel computing power of graphics processing units (GPUs). In order to evaluate the parallelization strategies for the projection/backprojection pairs, an iterative image reconstruction algorithm is implemented. Computer simulation and experimental studies are conducted to investigate the computational efficiency and numerical accuracy of the developed algorithms. The GPU implementations improve the computational efficiency by factors of 1000, 125, and 250 for the FBP algorithm and the two pairs of projection/backprojection operators, respectively. Accurate images are reconstructed by use of the FBP and iterative image reconstruction algorithms from both computer-simulated and experimental data. Parallelization strategies for 3D OAT image reconstruction are proposed for the first time. These GPU-based implementations significantly reduce the computational time for 3D image reconstruction, complementing our earlier work on 3D OAT iterative image reconstruction.

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By the use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications.