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Photonics
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Photoacoustic Imaging for Biomedical Applications
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Photoacoustic Imaging for Biomedical Applications

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Biophotonics and Biomedical Optics".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 17104

Special Issue Editors

Dr. Yao Sun

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Guest Editor
Department of Radiology, Wake Forest University School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA
Interests: photoacoustic imaging; ultrasound imaging; high-intensity focused ultrasound; deep learning algorithms
Special Issues, Collections and Topics in MDPI journals
Dr. Liliya Yamaleyeva

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Guest Editor
Hypertension and Vascular Research Center, Wake Forest University School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA
Interests: photoacoustic imaging of tissue hypoxia; placental biology and imaging; tissue hypoxia imaging
Special Issues, Collections and Topics in MDPI journals
Dr. Hao Yang

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Guest Editor
Department of Medical Engineering, University of South Florida, Tampa, FL 33620, USA
Interests: biomedical imaging; photoacoustic imaging; optical imaging; optical engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Photoacoustic imaging is a hybrid imaging modality combining rich optical contrast with high spatial resolution and deep tissue penetration of ultrasound imaging. With the technical developments in the past decade, this new imaging modality has emerged as a powerful tool in life science and clinical studies, and can provide multiscale highly resolved structural, functional, metabolic, and molecular information relating to organelles, cells, tissues, and organs in vivo. The three major embodiments of photoacoustic imaging are microscopy, endoscopy, and computed tomography. Currently, many commercial and home-made photoacoustic imaging systems or ultrasound-photoacoustic imaging systems are available. Many attempts have been made to use these systems to detect degenerative diseases and malignancies as well as to guide cancer treatments. The objective of this Special Issue is to highlight the applications of photoacoustic imaging in preclinical and clinical studies.

For this Special Issue, the topics of interest include, but are not limited to:

  • Photoacoustic imaging in arthritis diagnostics;
  • Photoacoustic imaging in neuroimaging;
  • Photoacoustic imaging in cancer detection;
  • Photoacoustic imaging in nanomedicine;
  • Photoacoustic imaging in image guided ultrasound treatment;
  • Photoacoustic imaging in image guided photothermal therapy;
  • Photoacoustic imaging in image guided photodynamic therapy.

Dr. Yao Sun
Prof. Liliya Yamaleyeva
Dr. Hao Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

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8 pages, 2223 KiB  
Article
Tutorial on Development of 3D Vasculature Digital Phantoms for Evaluation of Photoacoustic Image Reconstruction Algorithms
by Seyed Mohsen Ranjbaran, Azam Khan, Rayyan Manwar and Kamran Avanaki
Photonics 2022, 9(8), 538; https://doi.org/10.3390/photonics9080538 - 31 Jul 2022
Cited by 3 | Viewed by 1734
Abstract
A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional [...] Read more.
A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional shapes are used as imaging targets to calibrate reconstruction algorithms. However, these structures are not representative of complex biological tissue, and therefore the artifacts that exist in reconstructed images of biological tissue vasculature are ignored. Real data from 3D MRI/CT volumes can be extrapolated to create high-quality phantom models; however, these sometimes involve complicated pre-processing and mostly are challenging, due to the inaccessibility of these datasets or the requirement for approval to utilize the data. Therefore, it is necessary to develop a 3D tissue-mimicking phantom model consisting of different compartments with characteristics that can be easily modified. In this tutorial, we present an optimized development process of a generic 3D complex digital vasculature phantom model in Blender. The proposed workflow is such that an accurate and easily editable digital phantom can be developed. Other workflows for creating the same phantom will take much longer to set up and require more time to edit. We have made a few examples of editable 3D phantom models, which are publicly available to test and modify. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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13 pages, 4877 KiB  
Article
Simulation Study of Acoustic-Resolution-Based Photoacoustic Microscopy for Imaging Complex Blood Vessel Networks
by Yuan Liu, Chuqi Yuan and Hongyan Zhang
Photonics 2022, 9(6), 433; https://doi.org/10.3390/photonics9060433 - 18 Jun 2022
Cited by 1 | Viewed by 1933
Abstract
The high-quality imaging of vascular networks in biological tissue is significant to accurate cancer diagnosis with acoustic-resolution-based photoacoustic microscopy (AR-PAM). So far, many new back-projection (BP) models have been proposed to improve the image quality of AR-PAM in the off-focal regions. However, many [...] Read more.
The high-quality imaging of vascular networks in biological tissue is significant to accurate cancer diagnosis with acoustic-resolution-based photoacoustic microscopy (AR-PAM). So far, many new back-projection (BP) models have been proposed to improve the image quality of AR-PAM in the off-focal regions. However, many essential arguments are still open regarding the effectiveness of these methods. To settle these remaining questions and explore the potential and adaptability of these BP methods in vascular network imaging, we conducted extensive simulations of a complex vascular network based on a GPU-based data generation framework. Results show that the SAFT-CF algorithm effectively improves the reconstructed image but mainly highlights point targets. In contrast, the STR-BP algorithm can effectively balance the computational cost, signal-to-noise ratio (SNR), and consistency of target intensity for both point and line targets. Results proved that data interpolation for more A-line numbers would not improve the image quality due to information lost. Thus, the detector number in the scan should be sufficiently large. Results also showed that the STR-BP method improved the PSNR of the image by 4.7 to 7.5 dB, which helps the image withstand a noise level of higher than 25%. The proposed simulation framework and the intuitive findings will guide the design of AR-PAM systems and image reconstruction. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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16 pages, 1497 KiB  
Article
Enhancing Finite Element-Based Photoacoustic Tomography by Localized Reconstruction Method
by Yao Sun and Huabei Jiang
Photonics 2022, 9(5), 337; https://doi.org/10.3390/photonics9050337 - 12 May 2022
Cited by 1 | Viewed by 1685
Abstract
Iterative reconstruction algorithm based on finite element (FE) modeling is a powerful approach in photoacoustic tomography (PAT). However, an iterative inverse algorithm using conventional FE meshing of the entire imaging zone is computationally demanding, which hinders this powerful tool in applications where quick [...] Read more.
Iterative reconstruction algorithm based on finite element (FE) modeling is a powerful approach in photoacoustic tomography (PAT). However, an iterative inverse algorithm using conventional FE meshing of the entire imaging zone is computationally demanding, which hinders this powerful tool in applications where quick image acquisition and/or a large image matrix is needed. To address this challenge, parallel computing techniques are proposed and implemented in the field. Here, we present an alternative approach for 2D PAT, which locoregionally reconstructs the region of interest (ROI) instead of the full imaging zone. Our simulated and phantom experimental results demonstrate that this ROI reconstruction algorithm can produce almost the same image quality as the conventional full zone-based reconstruction algorithm; however, the computation time can be significantly reduced without any additional hardware cost by more than two orders of magnitude (100-fold). This algorithm is further applied and validated in an in vivo study. The major vessel structures in a rat’s brain can be imaged clearly using our ROI-based approach, coupled with a mesh of 11,801 nodes. This novel algorithm can also be parallelized using MPI or GPU acceleration techniques to further enhance the reconstruction performance of FE-based PAT. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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14 pages, 6320 KiB  
Article
Multimodal In Vivo Imaging of Retinal and Choroidal Vascular Occlusion
by Van Phuc Nguyen, Tianye Zhu, Jessica Henry, Wei Zhang, Xueding Wang and Yannis M. Paulus
Photonics 2022, 9(3), 201; https://doi.org/10.3390/photonics9030201 - 21 Mar 2022
Cited by 3 | Viewed by 2595
Abstract
Photoacoustic microscopy (PAM) is an emerging retinal imaging technique that can provide high spatial resolution and high contrast of chorioretinal vessels. PAM is compatible with optical coherence tomography (OCT) and fluorescence imaging, allowing for development of a multimodal imaging system that combines these [...] Read more.
Photoacoustic microscopy (PAM) is an emerging retinal imaging technique that can provide high spatial resolution and high contrast of chorioretinal vessels. PAM is compatible with optical coherence tomography (OCT) and fluorescence imaging, allowing for development of a multimodal imaging system that combines these imaging modalities into one. This study presents a non-invasive, label-free in vivo imaging of retinal and choroidal vascular occlusion using multimodal imaging system, including PAM and OCT. Both retinal vein occlusion (RVO) and choroidal vascular occlusion (CVO) were clearly identified selectively using a spectroscopic PAM imaging. RVO and CVO were created in six rabbits using laser photocoagulation. The dynamic changes of retinal vasculature were observed and evaluated using color fundus photography, fluorescein angiography, OCT, and PAM. The position of RVO and CVO were imaged with different wavelengths ranging from 532 to 600 nm. The data shows that occluded vessels were clearly distinguished from the surrounding retinal vessels on the PAM images. This advanced imaging system is a promising technique for imaging retinal ischemia in preclinical disease models. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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14 pages, 3136 KiB  
Article
Fast Correction of “Finite Aperture Effect” in Photoacoustic Tomography Based on Spatial Impulse Response
by Xiaofei Luo, Jiaying Xiao, Congcong Wang and Bo Wang
Photonics 2021, 8(9), 356; https://doi.org/10.3390/photonics8090356 - 27 Aug 2021
Cited by 7 | Viewed by 2023
Abstract
Photoacoustic computed tomography (PACT) is a fast-developing imaging technique, which can provide structural and functional information in biological tissues with high-resolution beyond the depth of the optical diffusion limit. However, the most current PACT reconstruction method generally employs a point detector assumption, whereas [...] Read more.
Photoacoustic computed tomography (PACT) is a fast-developing imaging technique, which can provide structural and functional information in biological tissues with high-resolution beyond the depth of the optical diffusion limit. However, the most current PACT reconstruction method generally employs a point detector assumption, whereas in most PAT systems with circular or spherical scanning modes, the transducer is mostly flat and with a finite size. This model mismatch leads to a notable deterioration in the lateral direction in regions far from the rotation center, which is known as the “finite aperture effect”. In this work, we propose to compensate a novel Back-projection (BP) method based on the transducer’s spatial impulse response (SIR) for fast correction of the “finite aperture effect”. The SIR accounts for the waveform change of the transducer for an arbitrary point source due to the geometry of the detection surface. Simulation results showed that the proposed SIR-BP method can effectively improve the lateral resolution and signal to noise ratio (SNR) in the off-center regions. For a target 4.5 mm far from the rotation center, this new method improved the lateral resolution about five times along with a 7 dB increase in the SNR. Experimental results also showed that this SIR-BP method can well restore the image angular blur to recover small structures, as demonstrated by the imaging of leaf veins. This new method offers a valuable alternative to the conventional BP method, and can guide the design of PAT systems based on circular/spherical scan. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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13 pages, 9494 KiB  
Article
High-Sensitivity Optical-Resolution Photoacoustic Microscopy with an Optical-Acoustic Combiner Based on an Off-Axis Parabolic Acoustic Mirror
by Xiang Zhang, Yang Liu, Chao Tao, Jie Yin, Zizhong Hu, Songtao Yuan, Qinghuai Liu and Xiaojun Liu
Photonics 2021, 8(4), 127; https://doi.org/10.3390/photonics8040127 - 18 Apr 2021
Cited by 8 | Viewed by 2832
Abstract
Optical-resolution photoacoustic microscopy (OR-PAM) is a promising noninvasive biomedical imaging technology with label-free optical absorption contrasts. Performance of OR-PAM is usually closely related to the optical-acoustic combiner. In this study, we propose an optical-acoustic combiner based on a flat acoustic reflector and an [...] Read more.
Optical-resolution photoacoustic microscopy (OR-PAM) is a promising noninvasive biomedical imaging technology with label-free optical absorption contrasts. Performance of OR-PAM is usually closely related to the optical-acoustic combiner. In this study, we propose an optical-acoustic combiner based on a flat acoustic reflector and an off-axis parabolic acoustic mirror with a conical bore. Quantitative simulation and experiments demonstrated that this combiner can provide better acoustic focusing performance and detection sensitivity. Moreover, OR-PAM is based on the combiner suffer low optical disorders, which guarantees the good resolution. In vivo experiments of the mouse brain and the iris were also conducted to show the practicability of the combiner in biomedicine. This proposed optical-acoustic combiner realizes a high-quality optical-acoustic confocal alignment with minimal optical disorders and acoustic insertion loss, strong acoustic focusing, and easy implementation. These characteristics might be useful for improving the performance of OR-PAM. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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Review

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17 pages, 3439 KiB  
Review
Segmentation and Quantitative Analysis of Photoacoustic Imaging: A Review
by Thanh Dat Le, Seong-Young Kwon and Changho Lee
Photonics 2022, 9(3), 176; https://doi.org/10.3390/photonics9030176 - 11 Mar 2022
Cited by 7 | Viewed by 3233
Abstract
Photoacoustic imaging is an emerging biomedical imaging technique that combines optical contrast and ultrasound resolution to create unprecedented light absorption contrast in deep tissue. Thanks to its fusional imaging advantages, photoacoustic imaging can provide multiple structural and functional insights into biological tissues such [...] Read more.
Photoacoustic imaging is an emerging biomedical imaging technique that combines optical contrast and ultrasound resolution to create unprecedented light absorption contrast in deep tissue. Thanks to its fusional imaging advantages, photoacoustic imaging can provide multiple structural and functional insights into biological tissues such as blood vasculatures and tumors and monitor the kinetic movements of hemoglobin and lipids. To better visualize and analyze the regions of interest, segmentation and quantitative analyses were used to extract several biological factors, such as the intensity level changes, diameter, and tortuosity of the tissues. Over the past 10 years, classical segmentation methods and advances in deep learning approaches have been utilized in research investigations. In this review, we provide a comprehensive review of segmentation and quantitative methods that have been developed to process photoacoustic imaging in preclinical and clinical experiments. We focus on the parametric reliability of quantitative analysis for semantic and instance-level segmentation. We also introduce the similarities and alternatives of deep learning models in qualitative measurements using classical segmentation methods for photoacoustic imaging. Full article
(This article belongs to the Special Issue Photoacoustic Imaging for Biomedical Applications)
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