Photoacoustic computed tomography correcting for heterogeneity and attenuation

Removing Artifacts in Transcranial Photoacoustic Imaging With Polarized Self-Attention Dense-UNet

OBJECTIVE

Photoacoustic imaging (PAI) is a promising transcranial imaging technique. However, the distortion of photoacoustic signals induced by the skull significantly influences its imaging quality. We aimed to use deep learning for removing artifacts in PAI.

METHODS

In this study, we propose a polarized self-attention dense U-Net, termed PSAD-UNet, to correct the distortion and accurately recover imaged objects beneath bone plates. To evaluate the performance of the proposed method, a series of experiments was performed using a custom-built PAI system.

RESULTS

The experimental results showed that the proposed PSAD-UNet method could effectively implement transcranial PAI through a one- or two-layer bone plate. Compared with the conventional delay-and-sum and classical U-Net methods, PSAD-UNet can diminish the influence of bone plates and provide high-quality PAI results in terms of structural similarity and peak signal-to-noise ratio. The 3-D experimental results further confirm the feasibility of PSAD-UNet in 3-D transcranial imaging.

CONCLUSION

PSAD-UNet paves the way for implementing transcranial PAI with high imaging accuracy, which reveals broad application prospects in preclinical and clinical fields.

Recent Advances in Photoacoustic Imaging: Current Status and Future Perspectives

Photoacoustic imaging (PAI) is an emerging hybrid imaging modality that combines high-contrast optical imaging with high-spatial-resolution ultrasound imaging. PAI can provide a high spatial resolution and significant imaging depth by utilizing the distinctive spectroscopic characteristics of tissue, which gives it a wide variety of applications in biomedicine and preclinical research. In addition, it is non-ionizing and non-invasive, and photoacoustic (PA) signals are generated by a short-pulse laser under thermal expansion. In this study, we describe the basic principles of PAI, recent advances in research in human and animal tissues, and future perspectives.

Quantitative photoacoustic tomography: modeling and inverse problems

Significance

Quantitative photoacoustic tomography (QPAT) exploits the photoacoustic effect with the aim of estimating images of clinically relevant quantities related to the tissue's optical absorption. The technique has two aspects: an acoustic part, where the initial acoustic pressure distribution is estimated from measured photoacoustic time-series, and an optical part, where the distributions of the optical parameters are estimated from the initial pressure.

Aim

Our study is focused on the optical part. In particular, computational modeling of light propagation (forward problem) and numerical solution methodologies of the image reconstruction (inverse problem) are discussed.

Approach

The commonly used mathematical models of how light and sound propagate in biological tissue are reviewed. A short overview of how the acoustic inverse problem is usually treated is given. The optical inverse problem and methods for its solution are reviewed. In addition, some limitations of real-life measurements and their effect on the inverse problems are discussed.

Results

An overview of QPAT with a focus on the optical part was given. Computational modeling and inverse problems of QPAT were addressed, and some key challenges were discussed. Furthermore, the developments for tackling these problems were reviewed. Although modeling of light transport is well-understood and there is a well-developed framework of inverse mathematics for approaching the inverse problem of QPAT, there are still challenges in taking these methodologies to practice.

Conclusions

Modeling and inverse problems of QPAT together were discussed. The scope was limited to the optical part, and the acoustic aspects were discussed only to the extent that they relate to the optical aspect.

Photoacoustic Imaging and Characterization of Bone in Medicine: Overview, Applications, and Outlook

Photoacoustic techniques have shown promise in identifying molecular changes in bone tissue and visualizing tissue microstructure. This capability represents significant advantages over gold standards (i.e., dual-energy X-ray absorptiometry) for bone evaluation without requiring ionizing radiation. Instead, photoacoustic imaging uses light to penetrate through bone, followed by acoustic pressure generation, resulting in highly sensitive optical absorption contrast in deep biological tissues. This review covers multiple bone-related photoacoustic imaging contributions to clinical applications, spanning bone cancer, joint pathologies, spinal disorders, osteoporosis, bone-related surgical guidance, consolidation monitoring, and transsphenoidal and transcranial imaging. We also present a summary of photoacoustic-based techniques for characterizing biomechanical properties of bone, including temperature, guided waves, spectral parameters, and spectroscopy. We conclude with a future outlook based on the current state of technological developments, recent achievements, and possible new directions.

Optoacoustic imaging of the skin

Optoacoustic (OA, photoacoustic) imaging capitalizes on the synergistic combination of light excitation and ultrasound detection to empower biological and clinical investigations with rich optical contrast while effectively bridging the gap between micro and macroscopic imaging realms. State-of-the-art OA embodiments consistently provide images at micron-scale resolution through superficial tissue layers by means of focused illumination that can be smoothly exchanged for acoustic-resolution images at diffuse light depths of several millimetres to centimetres via ultrasound beamforming or tomographic reconstruction. Taken together, this unique multi-scale imaging capacity opens unprecedented capabilities for high-resolution in vivo interrogations of the skin at scalable depths. Moreover, diverse anatomical and functional information is retrieved via dynamic mapping of endogenous chromophores such as haemoglobin, melanin, lipids, collagen, water and others. This, along with the use of non-ionizing radiation, facilitates a clinical translation of the OA modalities. We review recent progress in OA imaging of the skin in preclinical and clinical studies exploiting the rich contrast provided by endogenous substances in tissues. The imaging capabilities of existing approaches are discussed in the context of initial translational studies on skin cancer, inflammatory skin diseases, wounds and other conditions.

Photoacoustic imaging as a highly efficient and precise imaging strategy for the evaluation of brain diseases

Photoacoustic imaging (PAI) is an emerging imaging strategy with a unique combination of rich optical contrasts, high ultrasound spatial resolution, and deep penetration depth without ionizing radiation. Taking advantage of the features mentioned above, PAI has been widely applied to preclinical studies in diverse fields, such as vascular biology, cardiology, neurology, ophthalmology, dermatology, gastroenterology, and oncology. Among various biomedical applications, photoacoustic brain imaging has great importance due to the brain's complex anatomy and the variability of brain disease. In this review, we aimed to introduce a novel and effective imaging modality for diagnosing brain diseases. Firstly, a brief overview of two major types of PAI system was provided. Then, PAI's major preclinical applications in brain diseases were introduced, including early diagnosis of brain tumors, subtle changes in the chemotherapy response, epileptic activity and brain injury, foreign body, and brain plaque. Finally, a perspective of the remaining challenges of PAI was given for future advancements.

Acoustic impact of the human skull on transcranial photoacoustic imaging

With balanced spatial resolution, imaging depth, and functional sensitivity, photoacoustic tomography (PAT) hold great promise for human brain imaging. However, the strong acoustic attenuation and aberration of the human skull (∼8 mm thick) are longstanding technical challenges for PAT of the human brain. In this work, we numerically investigated the impacts of the stratified human skull on photoacoustic wave propagation (i.e., the forward model) and PAT image formation (i.e., the inverse model). We simulated two representative transcranial PAT implementations: photoacoustic computed tomography (PACT) and photoacoustic macroscopy (PAMac). In the forward model, we simulated the detailed photoacoustic wave propagation from a point or line source through a digital human skull. The wave attenuation, refraction, mode conversation, and reverberation were thoroughly investigated. In the inverse model, we reconstructed the transcranial PACT and PAMac images of a point or line target enclosed by the human skull. Our results demonstrate that transcranial PAMac suffers mainly from wave reverberation within the skull, leading to prolonged signal duration and reduced axial resolution. Transcranial PACT is more susceptible to the skull's acoustic distortion, mode conversion, and reverberation, which collectively lead to strong image artifacts and deteriorated spatial resolutions. We also found that PACT with a ring-shaped transducer array shows more tolerance of the skull's adverse impacts and can provide more accurate image reconstruction. Our results suggest that incorporating the skull's geometry and acoustic properties can improve transcranial PAT image reconstruction. We expect that our results have provided a more comprehensive understanding of the acoustic impact of the human skull on transcranial PAT.

Zone-Shrinking Fresnel Zone Travel-Time Tomography for Sound Speed Reconstruction in Breast USCT

Many studies have been carried out on ultrasound computed tomography (USCT) for its potential application in breast imaging. The sound speed (SS) image modality in USCT can help doctors diagnose the breast cancer, as the tumor usually has a higher sound speed than normal tissues. Travel time is commonly used to reconstruct SS image. Raypath travel-time tomography (RTT) assumes that the sound wave travels through a raypath. RTT is computationally efficient but with low contrast to noise ratio (CNR). Fresnel zone travel-time tomography (FZTT) is based on the assumption that the sound wave travels through an area called the Fresnel zone. FZTT can provide SS image with high CNR but low accuracy due to the wide Fresnel zone. Here, we propose a zone-shrinking Fresnel zone travel-time tomography (ZSFZTT), where a weighting factor is adopted to shrink the Fresnel zone during the inversion process. Numerical phantom and in vivo breast experiments were performed with ZSFZTT, FZTT, and RTT. In the numerical experiment, the reconstruction biases of size by ZSFZTT, FZTT, and RTT were 0.2%~8.3%, 2.3%~31.7%, and 1.8%~25%; the reconstruction biases of relative SS value by ZSFZTT, FZTT, and RTT were 24.7%~42%, 53%~60.8%, and 30.3%~47.8%; and the CNR by ZSFZTT, FZTT, and RTT were 67.7~96.6, 68.5~98, and 1.7~2.7. In the in vivo breast experiment, ZSFZTT provided the highest CNR of 8.6 compared to 8.1 by FZTT and 1.9 by RTT. ZSFZTT improved the reconstruction accuracy of size and the relative reconstruction accuracy of SS value compared to FZTT and RTT while maintaining a high CNR similar to that of FZTT.

X-ray induced acoustic computed tomography

X-ray imaging has proved invaluable in medical diagnoses and non-destructive testing (NDT) in the past century. However, there remain two major limitations: radiation harm and inaccessibility to the sample. A recent imaging modality, X-ray induced acoustic computed tomography (XACT), allows a novel solution. In XACT, x-ray induced excitation causes localized heating (<mK) and thermoelastic expansion. This induces a detectable ultrasonic emission, thereby enabling imaging. XACT has the potential to enable low-dose, fast, 3D imaging requiring only single side access. We discuss the fundamentals of XACT and summarize milestones in its evolution over the past several years since its first demonstration using a Medical Linear Accelerator. We highlight XACT's potential applications in biomedical imaging and NDT, and discuss the latest advanced concepts and future directions.

Enhancement of photoacoustic tomography of acoustically inhomogeneous tissue by utilizing a memory effect

One of the major challenges for photoacoustic tomography is the variance of the speed of sound (SOS) in realistic tissue, which could lead to defocusing in image reconstruction and degrade the reconstructed image. In this study, we propose a method to optimize the SOS used for image reconstruction based on a memory effect of photoacoustic signal. We reveal that the photoacoustic signals received by two adjacent transducers have a high degree of similarity in waveform, while a time delay exists between them. The time delay is related to the SOS. Based on this physical phenomenon, an iterative operation is implemented to estimate the SOS used for image reconstruction. Both simulations and experiments confirm that the method significantly enhances the reconstructed image in inhomogeneous tissue. This study may have potential value in improving the performance of photoacoustic tomography in biomedical applications.

Dry Coupling of Ultrasonic Transducer Components for High Temperature Applications

The viability for dry coupling of piezoelectric ultrasonic transducer components was investigated, using a thin foil of annealed silver as a filler material/coupling agent at each component interface. Criteria used for room temperature evaluation were centered on signal-to-noise ratio (SNR) and echo bandwidth, for a Li-Nb based transducer operating in pulse-echo mode. A normal clamping stress of only 25 MPa, applied repeatedly over three loading cycles on a precisely-aligned transducer stack, was sufficient to yield backwall echoes with a SNR greater than 25 dB, and a 3 dB bandwidth of approximately 65%. This compares to a SNR of 32 dB and a 3 dB bandwidth of 65%, achievable when all transducer interfaces were coupled with ultrasonic gel. The respective roles of a soft filler material, alignment of transducer components, cyclic clamping, component roughness, and component flatness were evaluated in achieving this high efficiency dry coupling, with transducer clamping forces far lower than previously reported. Preliminary high temperature tests indicate that this coupling method is suitable for high temperature and achieves signal quality comparable to that at room temperature with ultrasonic gel.

Skull's Photoacoustic Attenuation and Dispersion Modeling with Deterministic Ray-Tracing: Towards Real-Time Aberration Correction

Although transcranial photoacoustic imaging has been previously investigated by several groups, there are many unknowns about the distorting effects of the skull due to the impedance mismatch between the skull and underlying layers. The current computational methods based on finite-element modeling are slow, especially in the cases where fine grids are defined for a large 3-D volume. We develop a very fast modeling/simulation framework based on deterministic ray-tracing. The framework considers a multilayer model of the medium, taking into account the frequency-dependent attenuation and dispersion effects that occur in wave reflection, refraction, and mode conversion at the skull surface. The speed of the proposed framework is evaluated. We validate the accuracy of the framework using numerical phantoms and compare its results to k-Wave simulation results. Analytical validation is also performed based on the longitudinal and shear wave transmission coefficients. We then simulated, using our method, the major skull-distorting effects including amplitude attenuation, time-domain signal broadening, and time shift, and confirmed the findings by comparing them to several ex vivo experimental results. It is expected that the proposed method speeds up modeling and quantification of skull tissue and allows the development of transcranial photoacoustic brain imaging.

Matrix Analysis of Warped Stretch Imaging

Sensitive and fast optical imaging is needed for scientific instruments, machine vision, and biomedical diagnostics. Many of the fundamental challenges are addressed with time stretch imaging, which has been used for ultrafast continuous imaging for a diverse range of applications, such as biomarker-free cell classification, the monitoring of laser ablation, and the inspection of flat panel displays. With frame rates exceeding a million scans per second, the firehose of data generated by the time stretch camera requires optical data compression. Warped stretch imaging technology utilizes nonuniform spectrotemporal optical operations to compress the image in a single-shot real-time fashion. Here, we present a matrix analysis method for the evaluation of these systems and quantify important design parameters and the spatial resolution. The key principles of the system include (1) time/warped stretch transformation and (2) the spatial dispersion of ultrashort optical pulse, which are traced with simple computation of ray-pulse matrix. Furthermore, a mathematical model is constructed for the simulation of imaging operations while considering the optical and electrical response of the system. The proposed analysis method was applied to an example time stretch imaging system via simulation and validated with experimental data.

Efficient 3-D Model-Based Reconstruction Scheme for Arbitrary Optoacoustic Acquisition Geometries

Optimal optoacoustic tomographic sampling is often hindered by the frequency-dependent directivity of ultrasound sensors, which can only be accounted for with an accurate 3-D model. Herein, we introduce a 3-D model-based reconstruction method applicable to optoacoustic imaging systems employing detection elements with arbitrary size and shape. The computational complexity and memory requirements are mitigated by introducing an efficient graphic processing unit (GPU)-based implementation of the iterative inversion. On-the-fly calculation of the entries of the model-matrix via a small look-up table avoids otherwise unfeasible storage of matrices typically occupying more than 300GB of memory. Superior imaging performance of the suggested method with respect to standard optoacoustic image reconstruction methods is first validated quantitatively using tissue-mimicking phantoms. Significant improvements in the spatial resolution, contrast to noise ratio and overall 3-D image quality are also reported in real tissues by imaging the finger of a healthy volunteer with a hand-held volumetric optoacoustic imaging system.

Constrained Inversion and Spectral Unmixing in Multispectral Optoacoustic Tomography

Accurate extraction of physical and biochemical parameters from optoacoustic images is often impeded due to the use of unrigorous inversion schemes, incomplete tomographic detection coverage, or other experimental factors that cannot be readily accounted for during the image acquisition and reconstruction process. For instance, inaccurate assumptions in the physical forward model may lead to negative optical absorption values in the reconstructed images. Any artifacts present in the single wavelength optoacoustic images can be significantly aggravated when performing a two-step reconstruction consisting in acoustic inversion and spectral unmixing aimed at rendering the distributions of spectrally distinct absorbers. We investigate a number of algorithmic strategies with non-negativity constraints imposed at the different phases of the reconstruction process. Performance is evaluated in cross-sectional multispectral optoacoustic tomography recordings from tissue-mimicking phantoms and in vivo mice embedded with varying concentrations of contrast agents. Additional in vivo validation is subsequently performed with molecular imaging data involving subcutaneous tumors labeled with genetically expressed iRFP proteins and organ perfusion by optical contrast agents. It is shown that constrained reconstruction is essential for reducing the critical image artifacts associated with inaccurate modeling assumptions. Furthermore, imposing the non-negativity constraint directly on the unmixed distribution of the probe of interest was found to maintain the most robust and accurate reconstruction performance in all experiments.

Spiral volumetric optoacoustic tomography visualizes multi-scale dynamics in mice

Imaging dynamics at different temporal and spatial scales is essential for understanding the biological complexity of living organisms, disease state and progression. Optoacoustic imaging has been shown to offer exclusive applicability across multiple scales with excellent optical contrast and high resolution in deep-tissue observations. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition time and effective field of view. Herein, we introduce the spiral volumetric optoacoustic tomography technique that provides spectrally enriched high-resolution contrast across multiple spatiotemporal scales. In vivo experiments in mice demonstrate a wide range of dynamic imaging capabilities, from three-dimensional high-frame-rate visualization of moving organs and contrast agent kinetics in selected areas to whole-body longitudinal studies with unprecedented image quality. The newly introduced paradigm shift in imaging of multi-scale dynamics adds to the multifarious advantages provided by the optoacoustic technology for structural, functional and molecular imaging.

An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging

Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an ℓ1-regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable.

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.

Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distributions in Photoacoustic Computed Tomography: A Numerical Investigation

Photoacoustic computed tomography (PACT) is a rapidly emerging bioimaging modality that seeks to reconstruct an estimate of the absorbed optical energy density within an object. Conventional PACT image reconstruction methods assume a constant speed-of-sound (SOS), which can result in image artifacts when acoustic aberrations are significant. It has been demonstrated that incorporating knowledge of an object's SOS distribution into a PACT image reconstruction method can improve image quality. However, in many cases, the SOS distribution cannot be accurately and/or conveniently estimated prior to the PACT experiment. Because variations in the SOS distribution induce aberrations in the measured photoacoustic wavefields, certain information regarding an object's SOS distribution is encoded in the PACT measurement data. Based on this observation, a joint reconstruction (JR) problem has been proposed in which the SOS distribution is concurrently estimated along with the sought-after absorbed optical energy density from the photoacoustic measurement data. A broad understanding of the extent to which the JR problem can be accurately and reliably solved has not been reported. In this work, a series of numerical experiments is described that elucidate some important properties of the JR problem that pertain to its practical feasibility. To accomplish this, an optimization-based formulation of the JR problem is developed that yields a non-linear iterative algorithm that alternatively updates the two image estimates. Heuristic analytic insights into the reconstruction problem are also provided. These results confirm the ill-conditioned nature of the joint reconstruction problem that will present significant challenges for practical applications.

Photoacoustic Molecular Imaging: From Multiscale Biomedical Applications Towards Early-Stage Theranostics

Photoacoustic imaging (PAI) has ushered in a new era of observational biotechnology and has facilitated the exploration of fundamental biological mechanisms and clinical translational applications, which has attracted tremendous attention in recent years. By converting laser into ultrasound emission, PAI combines rich optical contrast, high ultrasonic spatial resolution, and deep penetration depth in a single modality. This evolutional technique enables multiscale and multicontrast visualization from cells to organs, anatomy to function, and molecules to metabolism with high sensitivity and specificity. The state-of-the-art developments and applications of PAI are described in this review. Future prospects for clinical use are also highlighted. Collectively, PAI holds great promise to drive biomedical applications towards early-stage theranostics.

Three-Dimensional Optoacoustic and Laser-Induced Ultrasound Tomography System for Preclinical Research in Mice: Design and Phantom Validation

In this work, we introduce a novel three-dimensional imaging system for in vivo high-resolution anatomical and functional whole-body visualization of small animal models developed for preclinical and other type of biomedical research. The system (LOUIS-3DM) combines a multiwavelength optoacoustic tomography (OAT) and laser-induced ultrasound tomography (LUT) to obtain coregistered maps of tissue optical absorption and speed of sound, displayed within the skin outline of the studied animal. The most promising applications of the LOUIS-3DM include 3D angiography, cancer research, and longitudinal studies of biological distributions of optoacoustic contrast agents.

Label-free optical-resolution photoacoustic microscopy of superficial microvasculature using a compact visible laser diode excitation

We have developed laser-diode-based optical-resolution photoacoustic microscopy (LD-OR-PAM) of superficial microvasculature which has the desirable properties of being compact, low-cost, and label-free. A 300-mW visible pulsed laser diode was operated at a 405 ± 5 nm wavelength with a pulse energy as low as 52 nJ. By using a 3.6 MHz ultrasound transducer, the system was tested on carbon fibers with a lateral resolution of 0.95 µm and an SNR of 38 dB. The subcutaneous microvasculature on a mouse back was imaged without an exogenous contrast agent which demonstrates the potential of the proposed prototype for skin chromophores. Our eventual goal is to offer a practical and affordable multi-wavelength functional LD-OR-PAM instrument suitable for clinical applications.

Photoacoustic elastic oscillation and characterization

Photoacoustic imaging and sensing have been studied extensively to probe the optical absorption of biological tissue in multiple scales ranging from large organs to small molecules. However, its elastic oscillation characterization is rarely studied and has been an untapped area to be explored. In literature, photoacoustic signal induced by pulsed laser is commonly modelled as a bipolar "N-shape" pulse from an optical absorber. In this paper, the photoacoustic damped oscillation is predicted and modelled by an equivalent mass-spring system by treating the optical absorber as an elastic oscillator. The photoacoustic simulation incorporating the proposed oscillation model shows better agreement with the measured signal from an elastic phantom, than conventional photoacoustic simulation model. More interestingly, the photoacoustic damping oscillation effect could potentially be a useful characterization approach to evaluate biological tissue's mechanical properties in terms of relaxation time, peak number and ratio beyond optical absorption only, which is experimentally demonstrated in this paper.

Quantitative photoacoustic tomography using illuminations from a single direction

Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating optical parameters inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. This optical parameter estimation problem is ill-posed and needs to be approached within the framework of inverse problems. It has been shown that, in general, estimating the spatial distribution of more than one optical parameter is a nonunique problem unless more than one illumination pattern is used. Generally, this is overcome by illuminating the target from various directions. However, in some cases, for example when thick samples are investigated, illuminating the target from different directions may not be possible. In this work, the use of spatially modulated illumination patterns at one side of the target is investigated with simulations. The results show that the spatially modulated illumination patterns from a single direction could be used to provide multiple illuminations for quantitative photoacoustic tomography. Furthermore, the results show that the approach can be used to distinguish absorption and scattering inclusions located near the surface of the target. However, when compared to a full multidirection illumination setup, the approach cannot be used to image as deep inside tissues.

Effects of small variations of speed of sound in optoacoustic tomographic imaging

PURPOSE

Speed of sound difference in the imaged object and surrounding coupling medium may reduce the resolution and overall quality of optoacoustic tomographic reconstructions obtained by assuming a uniform acoustic medium. In this work, the authors investigate the effects of acoustic heterogeneities and discuss potential benefits of accounting for those during the reconstruction procedure.

METHODS

The time shift of optoacoustic signals in an acoustically heterogeneous medium is studied theoretically by comparing different continuous and discrete wave propagation models. A modification of filtered back-projection reconstruction is subsequently implemented by considering a straight acoustic rays model for ultrasound propagation. The results obtained with this reconstruction procedure are compared numerically and experimentally to those obtained assuming a heuristically fitted uniform speed of sound in both full-view and limited-view optoacoustic tomography scenarios.

RESULTS

The theoretical analysis showcases that the errors in the time-of-flight of the signals predicted by considering the straight acoustic rays model tend to be generally small. When using this model for reconstructing simulated data, the resulting images accurately represent the theoretical ones. On the other hand, significant deviations in the location of the absorbing structures are found when using a uniform speed of sound assumption. The experimental results obtained with tissue-mimicking phantoms and a mouse postmortem are found to be consistent with the numerical simulations.

CONCLUSIONS

Accurate analysis of effects of small speed of sound variations demonstrates that accounting for differences in the speed of sound allows improving optoacoustic reconstruction results in realistic imaging scenarios involving acoustic heterogeneities in tissues and surrounding media.

Photoacoustic microscopy and computed tomography: from bench to bedside

Photoacoustic imaging (PAI) of biological tissue has seen immense growth in the past decade, providing unprecedented spatial resolution and functional information at depths in the optical diffusive regime. PAI uniquely combines the advantages of optical excitation and those of acoustic detection. The hybrid imaging modality features high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth. Here we first summarize the fundamental principles underpinning the technology, then highlight its practical implementation, and finally discuss recent advances toward clinical translation.

Small-animal whole-body photoacoustic tomography: a review

With the wide use of small animals for biomedical studies, in vivo small-animal whole-body imaging plays an increasingly important role. Photoacoustic tomography (PAT) is an emerging whole-body imaging modality that shows great potential for preclinical research. As a hybrid technique, PAT is based on the acoustic detection of optical absorption from either endogenous tissue chromophores, such as oxyhemoglobin and deoxyhemoglobin, or exogenous contrast agents. Because ultrasound scatters much less than light in tissue, PAT generates high-resolution images in both the optical ballistic and diffusive regimes. Using near-infrared light, which has relatively low blood absorption, PAT can image through the whole body of small animals with acoustically defined spatial resolution. Anatomical and vascular structures are imaged with endogenous hemoglobin contrast, while functional and molecular images are enabled by the wide choice of exogenous optical contrasts. This paper reviews the rapidly growing field of small-animal whole-body PAT and highlights studies done in the past decade.

Bayesian Image Reconstruction in Quantitative Photoacoustic Tomography

Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating chromophore concentrations inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. This is a hybrid imaging problem in which the solution of one inverse problem acts as the data for another ill-posed inverse problem. In the optical reconstruction of quantitative photoacoustic tomography, the data is obtained as a solution of an acoustic inverse initial value problem. Thus, both the data and the noise are affected by the method applied to solve the acoustic inverse problem. In this paper, the noise of optical data is modelled as Gaussian distributed with mean and covariance approximated by solving several acoustic inverse initial value problems using acoustic noise samples as data. Furthermore, Bayesian approximation error modelling is applied to compensate for the modelling errors in the optical data caused by the acoustic solver. The results show that modelling of the noise statistics and the approximation errors can improve the optical reconstructions.

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

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Enhancement of photoacoustic tomography by ultrasonic computed tomography based on optical excitation of elements of a full-ring transducer array

Photoacoustic computed tomography (PACT) is a hybrid technique that combines optical excitation and ultrasonic detection to provide high-resolution images in deep tissues. In the image reconstruction, a constant speed of sound (SOS) is normally assumed. This assumption, however, is often not strictly satisfied in deep tissue imaging, due to acoustic heterogeneities within the object and between the object and the coupling medium. If these heterogeneities are not accounted for, they will cause distortions and artifacts in the reconstructed images. In this Letter, we incorporated ultrasonic computed tomography (USCT), which measures the SOS distribution within the object, into our full-ring array PACT system. Without the need for ultrasonic transmitting electronics, USCT was performed using the same laser beam as for PACT measurement. By scanning the laser beam on the array surface, we can sequentially fire different elements. As a first demonstration of the system, we studied the effect of acoustic heterogeneities on photoacoustic vascular imaging. We verified that constant SOS is a reasonable approximation when the SOS variation is small. When the variation is large, distortion will be observed in the periphery of the object, especially in the tangential direction.

Full-wave iterative image reconstruction in photoacoustic tomography with acoustically inhomogeneous media

Existing approaches to image reconstruction in photoacoustic computed tomography (PACT) with acoustically heterogeneous media are limited to weakly varying media, are computationally burdensome, and/or cannot effectively mitigate the effects of measurement data incompleteness and noise. In this work, we develop and investigate a discrete imaging model for PACT that is based on the exact photoacoustic (PA) wave equation and facilitates the circumvention of these limitations. A key contribution of the work is the establishment of a procedure to implement a matched forward and backprojection operator pair associated with the discrete imaging model, which permits application of a wide-range of modern image reconstruction algorithms that can mitigate the effects of data incompleteness and noise. The forward and backprojection operators are based on the k-space pseudospectral method for computing numerical solutions to the PA wave equation in the time domain. The developed reconstruction methodology is investigated by use of both computer-simulated and experimental PACT measurement data.

Photoacoustic tomography through a whole adult human skull with a photon recycler

ABSTRACT. Photoacoustic tomography (PAT) of the human brain is challenging due to the fact that the skull strongly absorbs and scatters light, and attenuates and distorts ultrasound as well. For the first time, we demonstrated the feasibility of PAT through a whole adult human skull. A photon recycler (PR) was built to increase light transmittance through the skull. Both a graphite target and a canine brain were imaged through the skull. Use of the PR was found to improve the photoacoustic signal-to-noise ratio by a factor of 2.4. In addition, subtraction of photoacoustic signals that arise from light absorption within the skull significantly improved the contrast of the target. Our results indicate that PAT can potentially be applied to in vivo human brain imaging.

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.