Breakthrough in Photonics 2013: Photoacoustic Tomography in Biomedicine

Review of bio-optical imaging systems with a high space-bandwidth product

Optical imaging has served as a primary method to collect information about biosystems across scales-from functionalities of tissues to morphological structures of cells and even at biomolecular levels. However, to adequately characterize a complex biosystem, an imaging system with a number of resolvable points, referred to as a space-bandwidth product (SBP), in excess of one billion is typically needed. Since a gigapixel-scale far exceeds the capacity of current optical imagers, compromises must be made to obtain either a low spatial resolution or a narrow field-of-view (FOV). The problem originates from constituent refractive optics-the larger the aperture, the more challenging the correction of lens aberrations. Therefore, it is impractical for a conventional optical imaging system to achieve an SBP over hundreds of millions. To address this unmet need, a variety of high-SBP imagers have emerged over the past decade, enabling an unprecedented resolution and FOV beyond the limit of conventional optics. We provide a comprehensive survey of high-SBP imaging techniques, exploring their underlying principles and applications in bioimaging.

Graphics processing unit accelerating compressed sensing photoacoustic computed tomography with total variation

Photoacoustic computed tomography with compressed sensing (CS-PACT) is a commonly used imaging strategy for sparse-sampling PACT. However, it is very time-consuming because of the iterative process involved in the image reconstruction. In this paper, we present a graphics processing unit (GPU)-based parallel computation framework for total-variation-based CS-PACT and adapted into a custom-made PACT system. Specifically, five compute-intensive operators are extracted from the iteration algorithm and are redesigned for parallel performance on a GPU. We achieved an image reconstruction speed 24-31 times faster than the CPU performance. We performed in vivo experiments on human hands to verify the feasibility of our developed method.

Image improvement in linear-array photoacoustic imaging using high resolution coherence factor weighting technique

Background

In Photoacoustic imaging (PAI), the most prevalent beamforming algorithm is delay-and-sum (DAS) due to its simple implementation. However, it results in a low quality image affected by the high level of sidelobes. Coherence factor (CF) can be used to address the sidelobes in the reconstructed images by DAS, but the resolution improvement is not good enough, compared to the high resolution beamformers such as minimum variance (MV). In this paper, it is proposed to use high-resolution-CF (HRCF) weighting technique in which MV is used instead of the existing DAS in the formula of the conventional CF.

Results

The higher performance of HRCF is proved numerically and experimentally. The quantitative results obtained with the simulations show that at the depth of 40 mm, in comparison with DAS+CF and MV+CF, HRCF improves the full-width-half-maximum of about 91% and 15% and the signal-to-noise ratio about 40% and 14%, respectively.

Conclusion

Proposed method provides a high resolution along with a low level of sidelobes for PAI.

Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

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.

Bioresponsive probes for molecular imaging: concepts and in vivo applications

Molecular imaging is a powerful tool to visualize and characterize biological processes at the cellular and molecular level in vivo. In most molecular imaging approaches, probes are used to bind to disease-specific biomarkers highlighting disease target sites. In recent years, a new subset of molecular imaging probes, known as bioresponsive molecular probes, has been developed. These probes generally benefit from signal enhancement at the site of interaction with its target. There are mainly two classes of bioresponsive imaging probes. The first class consists of probes that show direct activation of the imaging label (from "off" to "on" state) and have been applied in optical imaging and magnetic resonance imaging (MRI). The other class consists of probes that show specific retention of the imaging label at the site of target interaction and these probes have found application in all different imaging modalities, including photoacoustic imaging and nuclear imaging. In this review, we present a comprehensive overview of bioresponsive imaging probes in order to discuss the various molecular imaging strategies. The focus of the present article is the rationale behind the design of bioresponsive molecular imaging probes and their potential in vivo application for the detection of endogenous molecular targets in pathologies such as cancer and cardiovascular disease.