Photoacoustic imaging is a promising method for visualizing biological tissues with optical absorbers. This article provides an overview of the rapidly developing field of photoacoustic imaging. Photoacoustics, the physical basis of photoacoustic imaging, is analyzed briefly. The merits of photoacoustic technology, compared with optical imaging and ultrasonic imaging, are described. Various imaging techniques are also discussed, including scanning tomography, computed tomography and original detection of photoacoustic imaging. Finally, some biomedical applications of photoacoustic imaging are summarized.

Photoacoustic imaging in biomedicine

Photoacoustic imaging is a hybrid imaging modality that offers the advantages of optical (spectroscopic contrast) and ultrasound imaging (scalable spatial resolution and imaging depth). This promising modality has shown excellent potential in a wide range of preclinical and clinical imaging and sensing applications. Even though photoacoustic imaging technology has matured in research settings, its clinical translation is not happening at the expected pace. One of the main reasons for this is the requirement of bulky and expensive pulsed lasers for excitation. To accelerate the clinical translation of photoacoustic imaging and explore its potential in resource-limited settings, it is of paramount importance to develop portable and affordable light sources that can be used as the excitation light source. In this review, we focus on the following aspects: (1) the basic theory of photoacoustic imaging; (2) inexpensive light sources and different implementations; and (3) important preclinical and clinical applications, demonstrated using affordable light source-based photoacoustics. The main focus will be on laser diodes and light-emitting diodes as they have demonstrated promise in photoacoustic tomography—the key technological developments in these areas will be thoroughly reviewed. We believe that this review will be a useful opus for both the beginners and experts in the field of biomedical photoacoustic imaging.

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Portable and Affordable Light Source-Based Photoacoustic Tomography.

Significance: Photoacoustic (PA) imaging can provide structural, functional, and molecular information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal detection deteriorates image quality, and quantitative PAI (QPAI) remains challenging due to the unknown light fluence spectra in deep tissue. In recent years, deep learning (DL) has shown outstanding performance when implemented in PAI, with applications in image reconstruction, quantification, and understanding.
Aim: We provide (i) a comprehensive overview of the DL techniques that have been applied in PAI, (ii) references for designing DL models for various PAI tasks, and (iii) a summary of the future challenges and opportunities.
Approach: Papers published before November 2020 in the area of applying DL in PAI were reviewed. We categorized them into three types: image understanding, reconstruction of the initial pressure distribution, and QPAI.
Results: When applied in PAI, DL can effectively process images, improve reconstruction quality, fuse information, and assist quantitative analysis.
Conclusion: DL has become a powerful tool in PAI. With the development of DL theory and technology, it will continue to boost the performance and facilitate the clinical translation of PAI.

https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-26/issue-4/040901/Deep-learning-in-photoacoustic-imaging-a-review/10.1117/1.JBO.26.4.040901.pdf

Deep learning in photoacoustic imaging: a review

In recent years, multimodal thermoacoustic imaging has demonstrated superior imaging quality compared to other emerging modalities. It provides functional and molecular information, arising due to electromagnetic absorption contrast, at ultrasonic resolution using inexpensive and non-ionizing imaging methods. The development of optical- as well as radio frequency (RF)-induced thermoacoustic imaging systems would benefit from reliable numerical simulations. To date, most numerical models use a combination of different software in order to model the hybrid thermoacoustic phenomenon. Here, we demonstrate the use of a single open source finite element software platform (ONELAB) for photo- and RF-acoustic computed tomography. The solutions of the optical diffusion equation, frequency domain Maxwell's equations, and time-domain wave equation are used to solve the optical, electromagnetic, and acoustic propagation problems, respectively, in ONELAB. The results on a test homogeneous phantom and an approximate breast phantom confirm that ONELAB is a very effective software for both photo- and RF-acoustic simulations, and invaluable for developing new reconstruction algorithms and hardware systems.

https://www.mdpi.com/2076-3417/8/9/1568/pdf

A Single Simulation Platform for Hybrid Photoacoustic and RF-Acoustic Computed Tomography.

As photoacoustic imaging (PAI) technology matures, computational modeling will increasingly represent a critical tool for facilitating clinical translation through predictive simulation of real-world performance under a wide range of device and biological conditions. While modeling currently offers a rapid, inexpensive tool for device development and prediction of fundamental image quality metrics (e.g., spatial resolution and contrast ratio), rigorous verification and validation will be required of models used to provide regulatory-grade data that effectively complements and/or replaces in vivo testing. To address methods for establishing model credibility, we developed an integrated computational model of PAI by coupling a previously developed three-dimensional Monte Carlo model of tissue light transport with a two-dimensional (2D) acoustic wave propagation model implemented in the well-known k-Wave toolbox. We then evaluated ability of the model to predict basic image quality metrics by applying standardized verification and validation principles for computational models. The model was verified against published simulation data and validated against phantom experiments using a custom PAI system. Furthermore, we used the model to conduct a parametric study of optical and acoustic design parameters. Results suggest that computationally economical 2D acoustic models can adequately predict spatial resolution, but metrics such as signal-to-noise ratio and penetration depth were difficult to replicate due to challenges in modeling strong clutter observed in experimental images. Parametric studies provided quantitative insight into complex relationships between transducer characteristics and image quality as well as optimal selection of optical beam geometry to ensure adequate image uniformity. Multidomain PAI simulation tools provide high-quality tools to aid device development and prediction of real-world performance, but further work is needed to improve model fidelity, especially in reproducing image noise and clutter.

https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-24/issue-12/121910/Multidomain-computational-modeling-of-photoacoustic-imaging--verification-validation-and/10.1117/1.JBO.24.12.121910.pdf

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction.

Photoacoustic imaging is a molecular cum functional imaging modality based on differential optical absorption of the incident laser pulse by the endogeneous tissue chromophores. Several numerical simulations and finite element models have been developed in the past to describe and study Photoacoustic (PA) signal generation principles and study the effect of variation in PA parameters. Most of these simulation work concentrate on analyzing extracted 1D PA signals and each of them mostly describe only few of the building blocks of a Photoacoustic Tomography (PAT) imaging system. Papers describing simulation of the entire PAT system in one simulation platform, along with reconstruction is seemingly rare. This study attempts to describe how a commercially available Finite Element software (COMSOL(R)), can serve as a single platform for simulating PAT that couples the electromagnetic, thermodynamic and acoustic pressure physics involved in PA phenomena. Further, an array of detector elements placed at the boundary in the FE model can provide acoustic pressure data that can be exported to Matlab(R) to perform tomographic image reconstruction. The performance of two most commonly used image reconstruction techniques; namely, Filtered Backprojection (FBP) and Synthetic Aperture (SA) beamforming are compared. Results obtained showed that the lateral resolution obtained using FBP vs. SA largely depends on the aperture parameters. FBP reconstruction was able to provide a slightly better lateral resolution for smaller aperture while SA worked better for larger aperture. This interesting effect is currently being investigated further. Computationally FBP was faster, but it had artifacts along the spherical shell on which the data is projected.

Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques

During manual palpation of breast masses, the perception of its stiffness and slipperiness are the two commonly used information by the physician. In order to reliably and quantitatively obtain this information several non-invasive elastography techniques have been developed that seek to provide an image of the underlying mechanical properties, mostly stiffness-related. Very few approaches have visualized the "slip" at the lesion-background boundary that only occurs for a loosely-bonded benign lesion. It has been shown that axial-shear strain distribution provides information about underlying slip. One such feature, referred to as "fill-in" was interpreted as a surrogate of the rotation undergone by an asymmetrically-oriented-loosely bonded-benign-lesion under quasi-static compression. However, imaging and direct visualization of the rotation itself has not been addressed yet. In order to accomplish this, the quality of lateral displacement estimation needs to be improved. In this simulation study, we utilize spatial compounding approach and assess the feasibility to obtain good quality rotation elastogram. The angular axial and lateral displacement estimates were obtained at different insonification angles from a phantom containing an elliptical inclusion oriented at 45°, subjected to 1% compression from the top. A multilevel 2D-block matching algorithm was used for displacement tracking and 2D-least square compounding of angular axial and lateral displacement estimates was employed. By varying the maximum steering angle and incremental angle, the improvement in the lateral motion tracking accuracy and its effects on the quality of rotational elastogram were evaluated. Results demonstrate significantly-improved rotation elastogram using this technique.

Rotation elastogram: a novel method to visualize local rigid body rotation under quasi-static compression

High energy solid state lasers such as Nd:YAG are most commonly used as source of illumination in Photoacoustic (PA) imaging. However, recently, pulsed laser diodes (PLD)are being increasingly explored as a potential alternative to solid state sources due to its advantages such as portability, high pulse repetition rate and affordability. However, PLD has low energy per pulse which results in weaker signal, especially, from deep-seated photoacoustic targets. Hence, additional noise from external sources, such as, electronic noise, jitter, etc. have more pronounced detrimental effect on the quality of the reconstructed PA images resulting in low Signal-to-Ratio (SNR) values. Recently, several works have been reported to reduce the effect of noise by taking advantage of the high pulse-repetition rate offered by PLD and performing averaging. In this work we demonstrate that by strategically employing noise-reduction filter on the raw data prior to reconstruction stage yields significant improvement in SNR compared to mere averaging (∼61%) in PLD-based PAT systems.

Noise Reduction in Inherently low-SNR PLD-based PAT images

In most cases, high energy solid state lasers such as Nd:YAG are used as source of illumination for Photoacoustic Tomography (PAT). However the bulkiness, high cost and low pulse repetition frequency (PRF) poses a challenge in translating this technology to an affordable clinical imaging option at bed-side. Pulsed Laser Diodes (PLD) on the other hand is portable, inexpensive and offers high PRF. However, the achievable depth of penetration using PLD is much lower than the solid state lasers. In this work, we demonstrate the feasibility of using sub-pitch translation approach on the receive-side ultrasound transducer to increase the depth sensitivity in PAT imaging system while using PLD as a source of illumination. The preliminary results obtained from experiments suggest that the higher density data obtained by augmenting raw RF lines from λ/2 positions of a linear array transducer provides better signal strength from deeper located targets and thereby increasing the depth of penetration by about 15% that reaches up to a depth of 14.3 mm.

C Sowmiya

Papers

Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques

Rotation elastogram: a novel method to visualize local rigid body rotation under quasi-static compression

Noise Reduction in Inherently low-SNR PLD-based PAT images

Enhancing Depth of Penetration in PLD-Based Photoacoustic Imaging: Preliminary Results