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Zhang Y, Hu P, Li L, Cao R, Khadria A, Maslov K, Tong X, Zeng Y, Jiang L, Zhou Q, Wang LV. Ultrafast longitudinal imaging of haemodynamics via single-shot volumetric photoacoustic tomography with a single-element detector. Nat Biomed Eng 2024; 8:712-725. [PMID: 38036618 PMCID: PMC11136871 DOI: 10.1038/s41551-023-01149-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 10/25/2023] [Indexed: 12/02/2023]
Abstract
Techniques for imaging haemodynamics use ionizing radiation or contrast agents or are limited by imaging depth (within approximately 1 mm), complex and expensive data-acquisition systems, or low imaging speeds, system complexity or cost. Here we show that ultrafast volumetric photoacoustic imaging of haemodynamics in the human body at up to 1 kHz can be achieved using a single laser pulse and a single element functioning as 6,400 virtual detectors. The technique, which does not require recalibration for different objects or during long-term operation, enables the longitudinal volumetric imaging of haemodynamics in vasculature a few millimetres below the skin's surface. We demonstrate this technique in vessels in the feet of healthy human volunteers by capturing haemodynamic changes in response to vascular occlusion. Single-shot volumetric photoacoustic imaging using a single-element detector may facilitate the early detection and monitoring of peripheral vascular diseases and may be advantageous for use in biometrics and point-of-care testing.
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Affiliation(s)
- Yide Zhang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Peng Hu
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Lei Li
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Rui Cao
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Anjul Khadria
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Konstantin Maslov
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Xin Tong
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Yushun Zeng
- USC Roski Eye Institute, University of Southern California, Los Angeles, CA, USA
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Laiming Jiang
- USC Roski Eye Institute, University of Southern California, Los Angeles, CA, USA
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Qifa Zhou
- USC Roski Eye Institute, University of Southern California, Los Angeles, CA, USA
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Lihong V Wang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, USA.
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2
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Zhang Y, Hu P, Li L, Cao R, Khadria A, Maslov K, Tong X, Zeng Y, Jiang L, Zhou Q, Wang LV. Single-shot 3D photoacoustic tomography using a single-element detector for ultrafast imaging of hemodynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.14.532661. [PMID: 36993341 PMCID: PMC10055152 DOI: 10.1101/2023.03.14.532661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Imaging hemodynamics is crucial for the diagnosis, treatment, and prevention of vascular diseases. However, current imaging techniques are limited due to the use of ionizing radiation or contrast agents, short penetration depth, or complex and expensive data acquisition systems. Photoacoustic tomography shows promise as a solution to these issues. However, existing photoacoustic tomography methods collect signals either sequentially or through numerous detector elements, leading to either low imaging speed or high system complexity and cost. To address these issues, here we introduce a method to capture a 3D photoacoustic image of vasculature using a single laser pulse and a single-element detector that functions as 6,400 virtual ones. Our method enables ultrafast volumetric imaging of hemodynamics in the human body at up to 1 kHz and requires only a single calibration for different objects and for long-term operations. We demonstrate 3D imaging of hemodynamics at depth in humans and small animals, capturing the variability in blood flow speeds. This concept can inspire other imaging technologies and find applications such as home-care monitoring, biometrics, point-of-care testing, and wearable monitoring.
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Affiliation(s)
- Yide Zhang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Peng Hu
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Lei Li
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Rui Cao
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Anjul Khadria
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Konstantin Maslov
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Xin Tong
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Yushun Zeng
- Department of Biomedical Engineering and Ophthalmology, University of Southern California, Los Angeles, CA 90089, USA
| | - Laiming Jiang
- Department of Biomedical Engineering and Ophthalmology, University of Southern California, Los Angeles, CA 90089, USA
| | - Qifa Zhou
- Department of Biomedical Engineering and Ophthalmology, University of Southern California, Los Angeles, CA 90089, USA
| | - Lihong V. Wang
- Caltech Optical Imaging Laboratory, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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3
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Robin J, Ozbek A, Reiss M, Dean-Ben XL, Razansky D. Dual-Mode Volumetric Optoacoustic and Contrast Enhanced Ultrasound Imaging With Spherical Matrix Arrays. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:846-856. [PMID: 34735340 DOI: 10.1109/tmi.2021.3125398] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Spherical matrix arrays represent an advantageous tomographic detection geometry for non-invasive deep tissue mapping of vascular networks and oxygenation with volumetric optoacoustic tomography (VOT). Hybridization of VOT with ultrasound (US) imaging remains difficult with this configuration due to the relatively large inter-element pitch of spherical arrays. We suggest a new approach for combining VOT and US contrast-enhanced 3D imaging employing injection of clinically-approved microbubbles. Power Doppler (PD) and US localization imaging were enabled with a sparse US acquisition sequence and model-based inversion based on infimal convolution of total variation (ICTV) regularization. In vitro experiments in tissue-mimicking phantoms and in living mouse brain demonstrate the powerful capabilities of the new dual-mode imaging approach attaining 80 μm spatial resolution and a more than 10 dB signal to noise improvement with respect to a classical delay and sum beamformer. Microbubble localization and tracking allowed for flow velocity mapping up to 40 mm/s.
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Guo Y, Li B, Yin X. Dual-compressed photoacoustic single-pixel imaging. Natl Sci Rev 2022; 10:nwac058. [PMID: 36789105 PMCID: PMC9923385 DOI: 10.1093/nsr/nwac058] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 03/15/2022] [Accepted: 03/23/2022] [Indexed: 11/14/2022] Open
Abstract
Photoacoustic imaging, an acoustic imaging modality with potentially optical resolution in an optical turbid medium, has attracted great attention. However, the convergence of wavefront optimization and raster scanning in computational photoacoustic imaging leads to the challenge of fast mapping, especially for a spatial resolution approaching the acoustic deep-subwavelength regime. As a sparse sampling paradigm, compressive sensing has been applied in numerous fields to accelerate data acquisition without significant quality losses. In this work, we propose a dual-compressed approach for photoacoustic surface tomography that enables high-efficiency imaging with 3D spatial resolution unlimited by the acoustics in a turbid environment. The dual-compressed photoacoustic imaging with single-pixel detection, enabled by spatially optical modulation with synchronized temporally photoacoustic coding, allows decoding of the fine optical information from the modulated acoustic signal even when the variance of original photoacoustic signals is weak. We perform a proof-of-principle numerical demonstration of dual-compressed photoacoustic imaging, that resolves acoustic sub-acoustic-wavelength details with a significantly reduced number of measurements, revealing the potential for dynamic imaging. The dual-compressed concept, which transforms unobtrusive spatial difference into spatio-temporal detectable information, can be generalized to other imaging modalities to realize efficient, high-spatial-resolution imaging.
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Affiliation(s)
- Yuning Guo
- Department of Mechanical Engineering, University of Colorado, Boulder, CO80309, USA
| | | | - Xiaobo Yin
- Corresponding authors. E-mails: . Present affiliation: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
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5
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Silicon-photonics acoustic detector for optoacoustic micro-tomography. Nat Commun 2022; 13:1488. [PMID: 35304481 PMCID: PMC8933411 DOI: 10.1038/s41467-022-29179-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 02/28/2022] [Indexed: 11/08/2022] Open
Abstract
Medical ultrasound and optoacoustic (photoacoustic) imaging commonly rely on the concepts of beam-forming and tomography for image formation, enabled by piezoelectric array transducers whose element size is comparable to the desired resolution. However, the tomographic measurement of acoustic signals becomes increasingly impractical for resolutions beyond 100 µm due to the reduced efficiency of piezoelectric elements upon miniaturization. For higher resolutions, a microscopy approach is preferred, in which a single focused ultrasound transducer images the object point-by-point, but the bulky apparatus and long acquisition time of this approach limit clinical applications. In this work, we demonstrate a miniaturized acoustic detector capable of tomographic imaging with spread functions whose width is below 20 µm. The detector is based on an optical resonator fabricated in a silicon-photonics platform coated by a sensitivity-enhancing elastomer, which also effectively eliminates the parasitic effect of surface acoustic waves. The detector is demonstrated in vivo in high-resolution optoacoustic tomography.
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Nozdriukhin D, Kalva SK, Li W, Yashchenok A, Gorin D, Razansky D, Deán-Ben XL. Rapid Volumetric Optoacoustic Tracking of Individual Microparticles In Vivo Enabled by a NIR-Absorbing Gold-Carbon Shell. ACS APPLIED MATERIALS & INTERFACES 2021; 13:48423-48432. [PMID: 34613688 DOI: 10.1021/acsami.1c15509] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Rapid volumetric in vivo visualization of circulating microparticles can facilitate new biomedical applications, such as blood flow characterization or targeted drug delivery. However, existing imaging modalities generally lack the sensitivity to detect the weak signals generated by individual micrometer-sized particles distributed across millimeter- to centimeter-scale depths in living mammalian tissues. Also, the temporal resolution is typically insufficient to track the particles in an entire three-dimensional region. Herein, we introduce a new type of monodisperse (4 μm) silica-core microparticle coated with a shell formed by a multilayered structure of carbon nanotubes (CNT) and gold nanoparticles (AuNP) to provide strong optoacoustic (OA) absorption-based contrast. We capitalize on the unique advantages of a state-of-the-art high-frame-rate OA tomography system to visualize and track the motion of these core-shell particles individually and volumetrically as they flow throughout the mouse brain vasculature. The feasibility of localizing individual solid particles smaller than red blood cells opens new opportunities for mapping the blood flow velocity, enhancing the resolution and visibility of OA images, and developing new biosensing assays.
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Affiliation(s)
- Daniil Nozdriukhin
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, 8057 Zürich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, 8093 Zürich, Switzerland
- Center for Photonics and Quantum Materials, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Sandeep Kumar Kalva
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, 8057 Zürich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, 8093 Zürich, Switzerland
| | - Weiye Li
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, 8057 Zürich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, 8093 Zürich, Switzerland
| | - Alexey Yashchenok
- Center for Photonics and Quantum Materials, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Dmitry Gorin
- Center for Photonics and Quantum Materials, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, 8057 Zürich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, 8093 Zürich, Switzerland
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zürich, 8057 Zürich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, 8093 Zürich, Switzerland
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7
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Egolf D, Barber Q, Zemp R. Single laser-shot super-resolution photoacoustic tomography with fast sparsity-based reconstruction. PHOTOACOUSTICS 2021; 22:100258. [PMID: 33816111 PMCID: PMC8005825 DOI: 10.1016/j.pacs.2021.100258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 02/24/2021] [Accepted: 03/01/2021] [Indexed: 06/12/2023]
Abstract
Recently, ℓ 1 -norm based reconstruction approaches have been used with linear array systems to improve photoacoustic resolution and demonstrate undersampled imaging when there is sufficient sparsity in some domain. However, such approaches have yet to beat the half-wavelength resolution limit. In this paper, the ability to beat the half-wavelength diffraction limit is demonstrated using a 5 MHz ring array photoacoustic tomography system and ℓ 1 -norm based reconstruction approaches. We used the array system to image wire targets at ≈ 2 - 3 cm depth in both intralipid scattering solution and water. The minimum observable separation was estimated as 70 ± 10 μ m , improving on the half-wavelength resolution limit of 145 μ m . This improvement was demonstrated even when using a random projection transform to reduce data by 99 % , enabling substantially faster reconstruction times. This is the first photoacoustic tomography approach capable of beating the half-wavelength resolution limit with a single laser shot.
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8
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Lan H, Jiang D, Gao F, Gao F. Deep learning enabled real-time photoacoustic tomography system via single data acquisition channel. PHOTOACOUSTICS 2021; 22:100270. [PMID: 34026492 PMCID: PMC8122165 DOI: 10.1016/j.pacs.2021.100270] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 05/02/2023]
Abstract
Photoacoustic computed tomography (PACT) combines the optical contrast of optical imaging and the penetrability of sonography. In this work, we develop a novel PACT system to provide real-time imaging, which is achieved by a 120-elements ultrasound array only using a single data acquisition (DAQ) channel. To reduce the channel number of DAQ, we superimpose 30 nearby channels' signals together in the analog domain, and shrinking to 4 channels of data (120/30 = 4). Furthermore, a four-to-one delay-line module is designed to combine these four channels' data into one channel before entering the single-channel DAQ, followed by decoupling the signals after data acquisition. To reconstruct the image from four superimposed 30-channels' PA signals, we train a dedicated deep learning model to reconstruct the final PA image. In this paper, we present the preliminary results of phantom and in-vivo experiments, which manifests its robust real-time imaging performance. The significance of this novel PACT system is that it dramatically reduces the cost of multi-channel DAQ module (from 120 channels to 1 channel), paving the way to a portable, low-cost and real-time PACT system.
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Affiliation(s)
- Hengrong Lan
- Hybrid Imaging System Laboratory, Shanghai Engineering Research Center of Intelligent Vision and Imaging, School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Chinese Academy of Sciences, Shanghai Institute of Microsystem and Information Technology, Shanghai, 200050, China
| | - Daohuai Jiang
- Hybrid Imaging System Laboratory, Shanghai Engineering Research Center of Intelligent Vision and Imaging, School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Chinese Academy of Sciences, Shanghai Institute of Microsystem and Information Technology, Shanghai, 200050, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Feng Gao
- Hybrid Imaging System Laboratory, Shanghai Engineering Research Center of Intelligent Vision and Imaging, School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Fei Gao
- Hybrid Imaging System Laboratory, Shanghai Engineering Research Center of Intelligent Vision and Imaging, School of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China
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9
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Hahamovich E, Rosenthal A. Ultrasound Detection Arrays via Coded Hadamard Apertures. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:2095-2102. [PMID: 32396080 DOI: 10.1109/tuffc.2020.2993583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In the medical fields, ultrasound detection is often performed with piezoelectric arrays that enable one to simultaneously map the acoustic fields at several positions. In this work, we develop a novel method for transforming a single-element ultrasound detector into an effective detection array by spatially filtering the incoming acoustic fields using a binary acoustic mask coded with cyclic Hadamard patterns. By scanning the mask in front of the detector, we obtain a multiplexed measurement data set from which a map of the acoustic field is analytically constructed. We experimentally demonstrate our method by transforming a single-element ultrasound detector into 1-D arrays with up to 59 elements.
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10
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Ozbekxs A, Dean-Ben XL, Razansky D. Compressed Optoacoustic Sensing of Volumetric Cardiac Motion. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3250-3255. [PMID: 32746091 DOI: 10.1109/tmi.2020.2985134] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The recently developed optoacoustic tomography systems have attained volumetric frame rates exceeding 100 Hz, thus opening up new venues for studying previously invisible biological dynamics. Further gains in temporal resolution can potentially be achieved via partial data acquisition, though a priori knowledge on the acquired data is essential for rendering accurate reconstructions using compressed sensing approaches. In this work, we suggest a machine learning method based on principal component analysis for high-frame-rate volumetric cardiac imaging using only a few tomographic optoacoustic projections. The method is particularly effective for discerning periodic motion, as demonstrated herein by non-invasive imaging of a beating mouse heart. A training phase enables efficiently compressing the heart motion information, which is subsequently used as prior information for image reconstruction from sparse sampling at a higher frame rate. It is shown that image quality is preserved with a 64-fold reduction in the data flow. We demonstrate that, under certain conditions, the volumetric motion could effectively be captured by relying on time-resolved data from a single optoacoustic detector. Feasibility of capturing transient (non-periodic) events not registered in the training phase is further demonstrated by visualizing perfusion of a contrast agent in vivo. The suggested approach can be used to significantly boost the temporal resolution of optoacoustic imaging and facilitate development of more affordable and data efficient systems.
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11
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Chen Z, Özbek A, Rebling J, Zhou Q, Deán-Ben XL, Razansky D. Multifocal structured illumination optoacoustic microscopy. LIGHT, SCIENCE & APPLICATIONS 2020; 9:152. [PMID: 32922766 PMCID: PMC7459102 DOI: 10.1038/s41377-020-00390-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 08/15/2020] [Accepted: 08/18/2020] [Indexed: 05/06/2023]
Abstract
Optoacoustic (OA) imaging has the capacity to effectively bridge the gap between macroscopic and microscopic realms in biological imaging. High-resolution OA microscopy has so far been performed via point-by-point scanning with a focused laser beam, thus greatly restricting the achievable imaging speed and/or field of view. Herein we introduce multifocal structured illumination OA microscopy (MSIOAM) that attains real-time 3D imaging speeds. For this purpose, the excitation laser beam is shaped to a grid of focused spots at the tissue surface by means of a beamsplitting diffraction grating and a condenser and is then scanned with an acousto-optic deflector operating at kHz rates. In both phantom and in vivo mouse experiments, a 10 mm wide volumetric field of view was imaged with 15 Hz frame rate at 28 μm spatial resolution. The proposed method is expected to greatly aid in biological investigations of dynamic functional, kinetic, and metabolic processes across multiple scales.
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Affiliation(s)
- Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Ali Özbek
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Johannes Rebling
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Quanyu Zhou
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, University of Zurich and ETH Zurich, Zurich, Switzerland
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