Photoacoustic tomography of ex vivo mouse hearts with myocardial infarction

Application of photoacoustic computed tomography in biomedical imaging: A literature review

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

Deep-E: A Fully-Dense Neural Network for Improving the Elevation Resolution in Linear-Array-Based Photoacoustic Tomography

Linear-array-based photoacoustic tomography has shown broad applications in biomedical research and preclinical imaging. However, the elevational resolution of a linear array is fundamentally limited due to the weak cylindrical focus of the transducer element. While several methods have been proposed to address this issue, they have all handled the problem in a less time-efficient way. In this work, we propose to improve the elevational resolution of a linear array through Deep-E, a fully dense neural network based on U-net. Deep-E exhibits high computational efficiency by converting the three-dimensional problem into a two-dimension problem: it focused on training a model to enhance the resolution along elevational direction by only using the 2D slices in the axial and elevational plane and thereby reducing the computational burden in simulation and training. We demonstrated the efficacy of Deep-E using various datasets, including simulation, phantom, and human subject results. We found that Deep-E could improve elevational resolution by at least four times and recover the object's true size. We envision that Deep-E will have a significant impact in linear-array-based photoacoustic imaging studies by providing high-speed and high-resolution image enhancement.

Breakthroughs in modern cancer therapy and elusive cardiotoxicity: Critical research-practice gaps, challenges, and insights

To date, five cancer treatment modalities have been defined. The three traditional modalities of cancer treatment are surgery, radiotherapy, and conventional chemotherapy, and the two modern modalities include molecularly targeted therapy (the fourth modality) and immunotherapy (the fifth modality). The cardiotoxicity associated with conventional chemotherapy and radiotherapy is well known. Similar adverse cardiac events are resurging with the fourth modality. Aside from the conventional and newer targeted agents, even the most newly developed, immune‐based therapeutic modalities of anticancer treatment (the fifth modality), e.g., immune checkpoint inhibitors and chimeric antigen receptor (CAR) T‐cell therapy, have unfortunately led to potentially lethal cardiotoxicity in patients. Cardiac complications represent unresolved and potentially life‐threatening conditions in cancer survivors, while effective clinical management remains quite challenging. As a consequence, morbidity and mortality related to cardiac complications now threaten to offset some favorable benefits of modern cancer treatments in cancer‐related survival, regardless of the oncologic prognosis. This review focuses on identifying critical research‐practice gaps, addressing real‐world challenges and pinpointing real‐time insights in general terms under the context of clinical cardiotoxicity induced by the fourth and fifth modalities of cancer treatment. The information ranges from basic science to clinical management in the field of cardio‐oncology and crosses the interface between oncology and onco‐pharmacology. The complexity of the ongoing clinical problem is addressed at different levels. A better understanding of these research‐practice gaps may advance research initiatives on the development of mechanism‐based diagnoses and treatments for the effective clinical management of cardiotoxicity.

Structural and functional photoacoustic molecular tomography aided by emerging contrast agents

Photoacoustic tomography (PAT) can offer structural, functional and molecular contrasts at scalable observation level. By ultrasonically overcoming the strong optical scattering, this imaging technology can reach centimeters penetration depth while retaining high spatial resolution in biological tissue. Recent extensive research has been focused on developing new contrast agents to improve the imaging sensitivity, specificity and efficiency. These emerging materials have substantially accelerated PAT applications in signal sensing, functional imaging, biomarker labeling and therapy monitoring etc. Here, the potentials of different optical probes as PAT contrast agents were elucidated. We first describe the instrumental embodiments and the measured functional parameters, then focus on emerging contrast agent-based PAT applications, and finally discuss the challenges and prospects.

Multispectral optoacoustic tomography of myocardial infarction

OBJECTIVES

To investigate the feasibility of a high resolution optical imaging strategy for myocardial infarction.

BACKGROUND

Near-infrared approaches to imaging cardiovascular disease enable visualization of disease-associated biological processes in vivo. However, even at the scale of small animals, the strong scattering of light prevents high resolution imaging after the first 1-2 mm of tissue, leading to degraded signal localization.

METHODS

Multispectral optoacoustic tomography (MSOT) was used to non-invasively image myocardial infarction (MI) in a murine model of coronary artery ligation at resolutions not possible with current deep-tissue optical imaging methods. Post-MI imaging was based on resolving the spectral absorption signature of a dendritic polyglycerol sulfate-based (dPGS) near-infrared imaging agent targeted to P- and L-selectin.

RESULTS

In vivo imaging succeeded in detection of the agent in the injured myocardium after intravenous injection. The high anatomic resolution (<200 μm) achieved by the described method allowed signals originating in the infarcted heart to be distinguished from uptake in adjacent regions. Histological analysis found dPGS signal in infarcted areas, originating from leukocytes and endothelial cells.

CONCLUSIONS

MSOT imaging of myocardial infarction provides non-invasive visualization of optical contrast with a high spatial resolution that is not degraded by the scattering of light.

On the use of frequency-domain reconstruction algorithms for photoacoustic imaging

We investigate the use of a frequency-domain reconstruction algorithm based on the nonuniform fast Fourier transform (NUFFT) for photoacoustic imaging (PAI). Standard algorithms based on the fast Fourier transform (FFT) are computationally efficient, but compromise the image quality by artifacts. In our previous work we have developed an algorithm for PAI based on the NUFFT which is computationally efficient and can reconstruct images with the quality known from temporal backprojection algorithms. In this paper we review imaging qualities, such as resolution, signal-to-noise ratio, and the effects of artifacts in real-world situations. Reconstruction examples show that artifacts are reduced significantly. In particular, image details with a larger distance from the detectors can be resolved more accurately than with standard FFT algorithms.