Model-based optoacoustic image reconstruction of large three-dimensional tomographic datasets acquired with an array of directional detectors

Signal restoration algorithm for photoacoustic imaging systems

In a photoacoustic (PA) imaging system, the detectors are bandwidth-limited. Therefore, they capture PA signals with some unwanted ripples. This limitation degrades the resolution/contrast and induces sidelobes and artifacts in the reconstructed images along the axial direction. To compensate for the limited bandwidth effect, we present a PA signal restoration algorithm, where a mask is designed to extract the signals at the absorber positions and remove the unwanted ripples. This restoration improves the axial resolution and contrast in the reconstructed image. The restored PA signals can be considered as the input of the conventional reconstruction algorithms (e.g., Delay-and-sum (DAS) and Delay-multiply-and-sum (DMAS)). To compare the performance of the proposed method, DAS and DMAS reconstruction algorithms were performed with both the initial and restored PA signals on numerical and experimental studies (numerical targets, tungsten wires, and human forearm). The results show that, compared with the initial PA signals, the restored PA signals can improve the axial resolution and contrast by 45% and 16.1 dB, respectively, and suppress background artifacts by 80%.

Enhancing optoacoustic mesoscopy through calibration-based iterative reconstruction

Optoacoustic mesoscopy combines rich optical absorption contrast with high spatial resolution at tissue depths beyond reach for microscopic techniques employing focused light excitation. The mesoscopic imaging performance is commonly hindered by the use of inaccurate delay-and-sum reconstruction approaches and idealized modeling assumptions. In principle, image reconstruction performance could be enhanced by simulating the optoacoustic signal generation, propagation, and detection path. However, for most realistic experimental scenarios, the underlying total impulse response (TIR) cannot be accurately modelled. Here we propose to capture the TIR by scanning of a sub-resolution sized absorber. Significant improvement of spatial resolution and depth uniformity is demonstrated over 3 mm range, outperforming delay-and-sum and model-based reconstruction implementations. Reconstruction performance is validated by imaging subcutaneous murine vasculature and human skin in vivo. The proposed experimental calibration and reconstruction paradigm facilitates quantitative inversions while averting complex physics-based simulations. It can readily be applied to other imaging modalities employing TIR-based reconstructions.

Multi-angle data acquisition to compensate transducer finite size in photoacoustic tomography

In photoacoustic tomography (PAT) systems, the tangential resolution decreases due to the finite size of the transducer as the off-center distance increases. To address this problem, we propose a multi-angle detection approach in which the transducer used for data acquisition rotates around its center (with specific angles) as well as around the scanning center. The angles are calculated based on the central frequency and diameter of the transducer and the radius of the region-of-interest (ROI). Simulations with point-like absorbers (for point-spread-function evaluation) and a vasculature phantom (for quality assessment), and experiments with ten 0.5 mm-diameter pencil leads and a leaf skeleton phantom are used for evaluation of the proposed approach. The results show that a location-independent tangential resolution is achieved with 150 spatial sampling and central rotations with angles of ±8°/±16°. With further developments, the proposed detection strategy can replace the conventional detection (rotating a transducer around ROI) in PAT.

Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses

In photoacoustic tomography (PAT), conventional image reconstruction methods are generally based on the assumption of an ideal point-like ultrasonic detector. This assumption is appropriate when the receiving surface of the detector is sufficiently small and/or the distance between the imaged object and the detector is large enough. However, it does not hold in endoscopic applications of PAT. In this study, we propose a model-based image reconstruction method for endoscopic photoacoustic tomography (EPAT), considering the effect of detector responses on image quality. We construct a forward model to physically describe the imaging process of EPAT, including the generation of the initial pressure due to optical absorption and thermoelastic expansion, the propagation of photoacoustic waves in tissues, and the acoustic measurement. The model outputs the theoretical sampling voltage signal, which is the response of the ultrasonic detector to the acoustic pressure reaching its receiving surface. The images representing the distribution map of the optical absorption energy density on cross-sections of the imaged luminal structures are reconstructed from the sampling voltage signals output by the detector through iterative inversion of the forward model. Compared with the conventional approaches based on back-projection and other imaging models, our method improved the quality and spatial resolution of the resulting images.

Computationally Efficient Forward Operator for Photoacoustic Tomography Based on Coordinate Transformations

Photoacoustic tomography (PAT) is an imaging modality that utilizes the photoacoustic effect. In PAT, a photoacoustic image is computed from measured data by modeling ultrasound propagation in the imaged domain and solving an inverse problem utilizing a discrete forward operator. However, in realistic measurement geometries with several ultrasound transducers and relatively large imaging volume, an explicit formation and use of the forward operator can be computationally prohibitively expensive. In this work, we propose a transformation-based approach for efficient modeling of photoacoustic signals and reconstruction of photoacoustic images. In the approach, the forward operator is constructed for a reference ultrasound transducer and expanded into a general measurement geometry using transformations that map the formulated forward operator in local coordinates to the global coordinates of the measurement geometry. The inverse problem is solved using a Bayesian framework. The approach is evaluated with numerical simulations and experimental data. The results show that the proposed approach produces accurate 3-D photoacoustic images with a significantly reduced computational cost both in memory requirements and time. In the studied cases, depending on the computational factors, such as discretization, over the 30-fold reduction in memory consumption was achieved without a reduction in image quality compared to a conventional approach.

A method for the calibration of wideband ultrasonic sensors for optoacoustics

A method for calibration of ultrasonic sensors for optoacoustics that provides both frequency response and sensitivity is presented. In order to obtain the bandwidth and the frequency response of an uncalibrated sensor, a point source with broadband spectra generated by a laser-induced bubble on a copper wire submerged in water is employed. On the other hand, the sensitivity measurement relies on the spatial symmetry of the pressure pulse and on a calibrated transducer. Therefore, two sensors are employed to detect the pressure pulse at the same distance from the source. The symmetry of the acoustic field that arrives at both transducers is adjusted and verified by means of an optical interferometer that provides a null signal when the copper wire is placed at the right position. The method is tested on the characterization of a thin-film polymeric piezoelectric transducer with a cylindrical focused shape.

Non-local means improves total-variation constrained photoacoustic image reconstruction

Photoacoustic/Optoacoustic tomography aims to reconstruct maps of the initial pressure rise induced by the absorption of light pulses in tissue. This reconstruction is an ill-conditioned and under-determined problem, when the data acquisition protocol involves limited detection positions. The aim of the work is to develop an inversion method which integrates denoising procedure within the iterative model-based reconstruction to improve quantitative performance of optoacoustic imaging. Among the model-based schemes, total-variation (TV) constrained reconstruction scheme is a popular approach. In this work, a two-step approach was proposed for improving the TV constrained optoacoustic inversion by adding a non-local means based filtering step within each TV iteration. Compared to TV-based reconstruction, inclusion of this non-local means step resulted in signal-to-noise ratio improvement of 2.5 dB in the reconstructed optoacoustic images.

Full-frequency correction of spatial impulse response in back-projection scheme using space-variant filtering for optoacoustic mesoscopy

The fidelity and quality of reconstructed images in optoacoustic mesoscopy (OPAM) can be significantly improved by considering the spatial impulse response (SIR) of the employed focused transducer into reconstruction. However, the traditional method fully taking the SIR into account can hardly meet the data-intensive requirements of high resolution OPAM because of excessive memory and time consumption. Herein, a modified back-projection method using a space-variant filter for full-frequency correction of the SIR is presented, and applied to the OPAM system with a sphere-focused transducer. The proposed method can readily manage the large datasets of the OPAM and effectively reduce the extra time consumption. The performance of the proposed method is showcased by simulations and experiments of phantoms and biological tissue. The results demonstrate that the modified back-projection method exhibits better image fidelity, resolution and contrast compared to the common and weighted back-projection methods that are not or not fully accounting for the SIR.

Fan-shaped scanning approach for miniaturized photoacoustic tomography

We describe a novel scanning approach for miniaturized photoacoustic tomography (PAT), based on fan-shaped scanning of a single transducer at one or two discrete positions. This approach is tested and evaluated using several phantom and animal experiments. The results obtained show that this new scanning approach provides high image quality in the configuration of miniaturized handheld or endoscopic PAT with improved effective field of view and penetration depth.

Wave front analysis for enhanced time-domain beamforming of point-like targets in optoacoustic imaging using a linear array

Using linear array transducers in combination with state-of-the-art multichannel electronics allows to perform optoacoustic imaging with frame rates only limited by the laser pulse repetition frequency and the acoustic time of flight. However, characteristic image artefacts resulting from the limited view and a lower SNR when compared to systems based on single-element focused transducers represent a burden for the clinical acceptance of the technology. In this paper, we present a new method for the improvement of image quality based on the analysis of the signal amplitudes along summation curves during the delay-and-sum beamforming process (DAS). The algorithm compares amplitude distributions along wave fronts with theoretical patterns from optoacoustic point sources. The method was validated on simulated and experimental phantom as well as in-vivo data. An improvement of the lateral resolution by more than a factor of two when comparing conventional DAS and our approach could be shown (numeric and experimental phantom data). For instance, on experimental data from a wire phantom, a PSF in the range of 0.18-0.22 mm was obtained with our approach against 0.48 mm for standard DAS. Furthermore, the SNR of a subcutaneous vessel 2.5 mm below the skin surface was improved by about 30 dB when compared to standard DAS.

Modeling photoacoustic imaging with a scanning focused detector using Monte Carlo simulation of energy deposition

Photoacoustic imaging using a focused, scanning detector in combination with a pulsed light source is a common technique to visualize light-absorbing structures in biological tissue. In the acoustic resolution mode, where the imaging resolution is given by the properties of the transducer, there are various challenges related to the choice of sensors and the optimization of the illumination. These are addressed by linking a Monte Carlo simulation of energy deposition to a time-domain model of acoustic propagation and detection. In this model, the spatial and electrical impulse responses of the focused transducer are combined with a model of acoustic attenuation in a single response matrix, which is used to calculate detector signals from a volumetric distribution of absorbed energy density. Using the radial symmetry of the detector, the calculation yields a single signal in less than a second on a standard personal computer. Various simulation results are shown, comparing different illumination geometries and demonstrating spectral imaging. Finally, simulation results and experimental images of an optically characterized phantom are compared, validating the accuracy of the model. The proposed method will facilitate the design of photoacoustic imaging devices and will be used as an accurate forward model for iterative reconstruction techniques.

Diffraction Effects and Compensation in Passive Acoustic Mapping

Over the last decade, a variety of noninvasive techniques have been developed to monitor therapeutic ultrasound procedures in support of safety or efficacy assessments. One class of methods employs diagnostic ultrasound arrays to sense acoustic emissions, thereby providing a means to passively detect, localize, and quantify the strength of nonlinear sources, including cavitation. Real array element diffraction patterns may differ substantially from those presumed in existing beamforming algorithms. However, diffraction compensation has received limited treatment in passive and active imaging, and measured diffraction data have yet to be used for array response correction. The objectives of this paper were to identify differences between ideal and real element diffraction patterns, and to quantify the impact of diffraction correction on cavitation mapping beamformer performance. These objectives were addressed by performing calibration measurements on a diagnostic linear array, using the results to calculate diffraction correction terms, and applying the corrections to cavitation emission data collected from soft tissue phantom experiments. Measured diffraction patterns were found to differ significantly from those of ideal element forms, particularly at higher frequencies and shorter distances from the array. Diffraction compensation of array data resulted in cavitation energy estimates elevated by as much as a factor of 5, accompanied by the elimination of a substantial bias between two established beamforming algorithms. These results illustrate the importance of using measured array responses to validate analytical field models and to minimize observation biases in imaging applications where quantitative analyses are critical for assessment of therapeutic safety and efficacy.

Parametric modeling of wideband piezoelectric polymer sensors: Design for optoacoustic applications

In this work, we present a three-dimensional model for the design of wideband piezoelectric polymer sensors which includes the geometry and the properties of the transducer materials. The model uses FFT and numerical integration techniques in an explicit, semi-analytical approach. To validate the model, we made electrical and mechanical measurements on homemade sensors for optoacoustic applications. Each device was implemented using a polyvinylidene fluoride thin film piezoelectric polymer with a thickness of 25 μm. The sensors had detection areas in the range between 0.5 mm² and 35 mm² and were excited by acoustic pressure pulses of 5 ns (FWHM) from a source with a diameter around 10 μm. The experimental data obtained from the measurements agree well with the model results. We discuss the relative importance of the sensor design parameters for optoacoustic applications and we provide guidelines for the optimization of devices.

All-optical photoacoustic projection imaging

We introduce all-optical photoacoustic projection imaging. An array of fiber-optic interferometers is used to measure photoacoustic signals. The obtained images represent the projection of the three-dimensional spatial light absorbance within a sample onto a two-dimensional plane. We assess the performance of the system by phantom measurements and show that the fiber-optic detectors achieve a noise-equivalent pressure of 24 Pascal at a 10 MHz bandwidth. Furthermore, we demonstrate the ability to acquire high-resolution projection images of large volumes within a short period of time.

Advanced optoacoustic methods for multiscale imaging of in vivo dynamics

Visualization of dynamic functional and molecular events in an unperturbed in vivo environment is essential for understanding the complex biology of living organisms and of disease state and progression. To this end, optoacoustic (photoacoustic) sensing and imaging have demonstrated the exclusive capacity to maintain excellent optical contrast and high resolution in deep-tissue observations, far beyond the penetration limits of modern microscopy. Yet, the time domain is paramount for the observation and study of complex biological interactions that may be invisible in single snapshots of living systems. This review focuses on the recent advances in optoacoustic imaging assisted by smart molecular labeling and dynamic contrast enhancement approaches that enable new types of multiscale dynamic observations not attainable with other bio-imaging modalities. A wealth of investigated new research topics and clinical applications is further discussed, including imaging of large-scale brain activity patterns, volumetric visualization of moving organs and contrast agent kinetics, molecular imaging using targeted and genetically expressed labels, as well as three-dimensional handheld diagnostics of human subjects.

A 3D reconstruction algorithm for magneto-acoustic tomography with magnetic induction based on ultrasound transducer characteristics

In this study we present a three-dimensional (3D) reconstruction algorithm for magneto-acoustic tomography with magnetic induction (MAT-MI) based on the characteristics of the ultrasound transducer. The algorithm is investigated to solve the blur problem of the MAT-MI acoustic source image, which is caused by the ultrasound transducer and the scanning geometry. First, we established a transducer model matrix using measured data from the real transducer. With reference to the S-L model used in the computed tomography algorithm, a 3D phantom model of electrical conductivity is set up. Both sphere scanning and cylinder scanning geometries are adopted in the computer simulation. Then, using finite element analysis, the distribution of the eddy current and the acoustic source as well as the acoustic pressure can be obtained with the transducer model matrix. Next, using singular value decomposition, the inverse transducer model matrix together with the reconstruction algorithm are worked out. The acoustic source and the conductivity images are reconstructed using the proposed algorithm. Comparisons between an ideal point transducer and the realistic transducer are made to evaluate the algorithms. Finally, an experiment is performed using a graphite phantom. We found that images of the acoustic source reconstructed using the proposed algorithm are a better match than those using the previous one, the correlation coefficient of sphere scanning geometry is 98.49% and that of cylinder scanning geometry is 94.96%. Comparison between the ideal point transducer and the realistic transducer shows that the correlation coefficients are 90.2% in sphere scanning geometry and 86.35% in cylinder scanning geometry. The reconstruction of the graphite phantom experiment also shows a higher resolution using the proposed algorithm. We conclude that the proposed reconstruction algorithm, which considers the characteristics of the transducer, can obviously improve the resolution of the reconstructed image. This study can be applied to analyse the effect of the position of the transducer and the scanning geometry on imaging. It may provide a more precise method to reconstruct the conductivity distribution in MAT-MI.

Real-Time Model-Based Inversion in Cross-Sectional Optoacoustic Tomography

Analytical (closed-form) inversion schemes have been the standard approach for image reconstruction in optoacoustic tomography due to their fast reconstruction abilities and low memory requirements. Yet, the need for quantitative imaging and artifact reduction has led to the development of more accurate inversion approaches, which rely on accurate forward modeling of the optoacoustic wave generation and propagation. In this way, multiple experimental factors can be incorporated, such as the exact detection geometry, spatio-temporal response of the transducers, and acoustic heterogeneities. The model-based inversion commonly results in very large sparse matrix formulations that require computationally extensive and memory demanding regularization schemes for image reconstruction, hindering their effective implementation in real-time imaging applications. Herein, we introduce a new discretization procedure for efficient model-based reconstructions in two-dimensional optoacoustic tomography that allows for parallel implementation on a graphics processing unit (GPU) with a relatively low numerical complexity. By on-the-fly calculation of the model matrix in each iteration of the inversion procedure, the new approach results in imaging frame rates exceeding 10 Hz, thus enabling real-time image rendering using the model-based approach.

Dimensionality Reduction Based Optimization Algorithm for Sparse 3-D Image Reconstruction in Diffuse Optical Tomography

Diffuse optical tomography (DOT) is a relatively low cost and portable imaging modality for reconstruction of optical properties in a highly scattering medium, such as human tissue. The inverse problem in DOT is highly ill-posed, making reconstruction of high-quality image a critical challenge. Because of the nature of sparsity in DOT, sparsity regularization has been utilized to achieve high-quality DOT reconstruction. However, conventional approaches using sparse optimization are computationally expensive and have no selection criteria to optimize the regularization parameter. In this paper, a novel algorithm, Dimensionality Reduction based Optimization for DOT (DRO-DOT), is proposed. It reduces the dimensionality of the inverse DOT problem by reducing the number of unknowns in two steps and thereby makes the overall process fast. First, it constructs a low resolution voxel basis based on the sensing-matrix properties to find an image support. Second, it reconstructs the sparse image inside this support. To compensate for the reduced sensitivity with increasing depth, depth compensation is incorporated in DRO-DOT. An efficient method to optimally select the regularization parameter is proposed for obtaining a high-quality DOT image. DRO-DOT is also able to reconstruct high-resolution images even with a limited number of optodes in a spatially limited imaging set-up.

Optical mesoscopy without the scatter: broadband multispectral optoacoustic mesoscopy

Optical mesoscopy extends the capabilities of biological visualization beyond the limited penetration depth achieved by microscopy. However, imaging of opaque organisms or tissues larger than a few hundred micrometers requires invasive tissue sectioning or chemical treatment of the specimen for clearing photon scattering, an invasive process that is regardless limited with depth. We developed previously unreported broadband optoacoustic mesoscopy as a tomographic modality to enable imaging of optical contrast through several millimeters of tissue, without the need for chemical treatment of tissues. We show that the unique combination of three-dimensional projections over a broad 500 kHz-40 MHz frequency range combined with multi-wavelength illumination is necessary to render broadband multispectral optoacoustic mesoscopy (2B-MSOM) superior to previous optical or optoacoustic mesoscopy implementations.

Single-side access, isotropic resolution, and multispectral three-dimensional photoacoustic imaging with rotate-translate scanning of ultrasonic detector array

Photoacoustic imaging can achieve high-resolution three-dimensional (3-D) visualization of optical absorbers at penetration depths of ∼1 cm in biological tissues by detecting optically induced high ultrasound frequencies. Tomographic acquisition with ultrasound linear arrays offers an easy implementation of single-side access, parallelized, and high-frequency detection, but usually comes with an image quality impaired by the directionality of the detectors. Indeed, a simple translation of the array perpendicular to its median imaging plane is often used, but results both in a poor resolution in the translation direction and strong limited-view artifacts.To improve the spatial resolution and the visibility of complex structures while retaining a planar detection geometry, we introduce, in this paper, a rotate-translate scanning scheme and investigate the performance ofa scanner implemented at 15 MHz center frequency. The developed system achieved a quasi-isotropic uniform 3-D resolution of ∼170 μm over a cubic volume of side length 8.5 mm, i.e., an improvement in the resolution in the translation direction by almost one order of magnitude. Dual-wavelength imaging was also demonstrated with ultrafast wavelength shifting. The validity of our approach was shown in vitro. We discuss the ability to enable in vivo imaging for preclinical and clinical studies.