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Shen TW, Tsai MC, Chen TM, Chang CC. Photoacoustic method for measuring the elasticity of polydimethylsiloxane at various mixing ratios. Heliyon 2024; 10:e31726. [PMID: 38841497 PMCID: PMC11152934 DOI: 10.1016/j.heliyon.2024.e31726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 05/19/2024] [Accepted: 05/21/2024] [Indexed: 06/07/2024] Open
Abstract
Measuring elasticity without physical contact is challenging, as current methods often require deconstruction of the test sample. This study addresses this challenge by proposing and testing a photoacoustic effect-based method for measuring the elasticity of polydimethylsiloxane (PDMS) at various mixing ratios, which may be applied on the wide range of applications such as biomedical and optical fields. A dual-light laser source of the photoacoustic (PA) system is designed, employing cross-correlation signal processing techniques. The platform systems and a mathematical model for performing PDMS elasticity measurements are constructed. During elasticity detection, photoacoustic signal features, influenced by hardness and shapes, are analyzed using cross-correlation calculations and phase difference detection. Results from phantom tests demonstrate the potential of predicting Young's modulus using the cross-correlation method, aligning with the American Society for Testing and Materials (ASTM) standard samples. However, accuracy may be affected by mixed materials and short tubes. Normalization or calibration of signals is suggested for aligning with Young's coefficient.
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Affiliation(s)
- Tsu-Wang Shen
- Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, ROC
- Master's Program Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan, ROC
| | - Ming-Chun Tsai
- Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, ROC
| | - Ting-Mao Chen
- Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, ROC
| | - Chi-Chang Chang
- School of Medical Informatics, Chung Shan Medical University & IT Office, Chung Shan Medical University Hospital, Taichung, Taiwan, ROC
- Department of Information Management, Ming Chuan University, Taoyuan, Taiwan, ROC
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Yu Y, Feng T, Qiu H, Gu Y, Chen Q, Zuo C, Ma H. Simultaneous photoacoustic and ultrasound imaging: A review. ULTRASONICS 2024; 139:107277. [PMID: 38460216 DOI: 10.1016/j.ultras.2024.107277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 01/09/2024] [Accepted: 02/26/2024] [Indexed: 03/11/2024]
Abstract
Photoacoustic imaging (PAI) is an emerging biomedical imaging technique that combines the advantages of optical and ultrasound imaging, enabling the generation of images with both optical resolution and acoustic penetration depth. By leveraging similar signal acquisition and processing methods, the integration of photoacoustic and ultrasound imaging has introduced a novel hybrid imaging modality suitable for clinical applications. Photoacoustic-ultrasound imaging allows for non-invasive, high-resolution, and deep-penetrating imaging, providing a wealth of image information. In recent years, with the deepening research and the expanding biomedical application scenarios of photoacoustic-ultrasound bimodal systems, the immense potential of photoacoustic-ultrasound bimodal imaging in basic research and clinical applications has been demonstrated, with some research achievements already commercialized. In this review, we introduce the principles, technical advantages, and biomedical applications of photoacoustic-ultrasound bimodal imaging techniques, specifically focusing on tomographic, microscopic, and endoscopic imaging modalities. Furthermore, we discuss the future directions of photoacoustic-ultrasound bimodal imaging technology.
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Affiliation(s)
- Yinshi Yu
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Ting Feng
- Academy for Engineering & Technology, Fudan University, Shanghai 200433,China.
| | - Haixia Qiu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Ying Gu
- First Medical Center of PLA General Hospital, Beijing, China
| | - Qian Chen
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China
| | - Chao Zuo
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
| | - Haigang Ma
- Smart Computational Imaging Laboratory (SCILab), School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210094, China; Smart Computational Imaging Research Institute (SCIRI) of Nanjing University of Science and Technology, Nanjing, Jiangsu Province 210019, China; Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense, Nanjing, Jiangsu Province 210094, China.
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Bayhaqi YA, Hamidi A, Navarini AA, Cattin PC, Canbaz F, Zam A. Real-time closed-loop tissue-specific laser osteotomy using deep-learning-assisted optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:2986-3002. [PMID: 37342720 PMCID: PMC10278623 DOI: 10.1364/boe.486660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 06/23/2023]
Abstract
This article presents a real-time noninvasive method for detecting bone and bone marrow in laser osteotomy. This is the first optical coherence tomography (OCT) implementation as an online feedback system for laser osteotomy. A deep-learning model has been trained to identify tissue types during laser ablation with a test accuracy of 96.28 %. For the hole ablation experiments, the average maximum depth of perforation and volume loss was 0.216 mm and 0.077 mm3, respectively. The contactless nature of OCT with the reported performance shows that it is becoming more feasible to utilize it as a real-time feedback system for laser osteotomy.
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Affiliation(s)
- Yakub. A. Bayhaqi
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Arsham Hamidi
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Alexander A. Navarini
- Digital Dermatology Group, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Philippe C. Cattin
- Center for medical Image Analysis and Navigation (CIAN), Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Ferda Canbaz
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
| | - Azhar Zam
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland
- Division of Engineering, New York University Abu Dhabi, Abu Dhabi, 129188, United Arab Emirates
- Tandon School of Engineering, New York University, Brooklyn, NY, 11201, USA
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Remote Photoacoustic Sensing Using Single Speckle Analysis by an Ultra-Fast Four Quadrant Photo-Detector. SENSORS 2021; 21:s21062109. [PMID: 33802885 PMCID: PMC8002695 DOI: 10.3390/s21062109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/09/2021] [Accepted: 03/11/2021] [Indexed: 12/15/2022]
Abstract
The need for tissue contact makes photoacoustic imaging not applicable for special medical applications like wound imaging, endoscopy, or laser surgery. An easy, stable, and contact-free sensing technique might thus help to broaden the applications of the medical imaging modality. In this work, it is demonstrated for the first time that remote photoacoustic sensing by speckle analysis can be performed in the MHz sampling range by tracking a single speckle using a four quadrant photo-detector. A single speckle, which is created by self-interference of surface back-reflection, is temporally analyzed using this photo-detector. Phantoms and skin samples are measured in transmission and reflection mode. The potential for miniaturization for endoscopic application is demonstrated by fiber bundle measurements. In addition, sensing parameters are discussed. Photoacoustic sensing in the MHz sampling range by single speckle analysis with the four quadrant detector is successfully demonstrated. Furthermore, the endoscopic applicability is proven, and the sensing parameters are convenient for photoacoustic sensing. It can be concluded that a single speckle contains all the relevant information for remote photoacoustic signal detection. Single speckle sensing is therefore an easy, robust, contact-free photoacoustic detection technique and holds the potential for economical, ultra-fast photoacoustic sensing. The new detection technique might thus help to broaden the field of photoacoustic imaging applications in the future.
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Hosseinaee Z, Le M, Bell K, Reza PH. Towards non-contact photoacoustic imaging [review]. PHOTOACOUSTICS 2020; 20:100207. [PMID: 33024694 PMCID: PMC7530308 DOI: 10.1016/j.pacs.2020.100207] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 06/29/2020] [Accepted: 07/10/2020] [Indexed: 05/06/2023]
Abstract
Photoacoustic imaging (PAI) takes advantage of both optical and ultrasound imaging properties to visualize optical absorption with high resolution and contrast. Photoacoustic microscopy (PAM) is usually categorized with all-optical microscopy techniques such as optical coherence tomography or confocal microscopes. Despite offering high sensitivity, novel imaging contrast, and high resolution, PAM is not generally an all-optical imaging method unlike the other microscopy techniques. One of the significant limitations of photoacoustic microscopes arises from their need to be in physical contact with the sample through a coupling media. This physical contact, coupling, or immersion of the sample is undesirable or impractical for many clinical and pre-clinical applications. This also limits the flexibility of photoacoustic techniques to be integrated with other all-optical imaging microscopes for providing complementary imaging contrast. To overcome these limitations, several non-contact photoacoustic signal detection approaches have been proposed. This paper presents a brief overview of current non-contact photoacoustic detection techniques with an emphasis on all-optical detection methods and their associated physical mechanisms.
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Affiliation(s)
- Zohreh Hosseinaee
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, Ontario, N2L 3G1, Canada
| | - Martin Le
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, Ontario, N2L 3G1, Canada
| | - Kevan Bell
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, Ontario, N2L 3G1, Canada
- IllumiSonics Inc., Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada
| | - Parsin Haji Reza
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, Ontario, N2L 3G1, Canada
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Abbasi H, Beltrán Bernal LM, Hamidi A, Droneau A, Canbaz F, Guzman R, Jacques SL, Cattin PC, Zam A. Combined Nd:YAG and Er:YAG lasers for real-time closed-loop tissue-specific laser osteotomy. BIOMEDICAL OPTICS EXPRESS 2020; 11:1790-1807. [PMID: 32341848 PMCID: PMC7173907 DOI: 10.1364/boe.385862] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/26/2020] [Accepted: 02/26/2020] [Indexed: 06/11/2023]
Abstract
A novel real-time and non-destructive method for differentiating soft from hard tissue in laser osteotomy has been introduced and tested in a closed-loop fashion. Two laser beams were combined: a low energy frequency-doubled nanosecond Nd:YAG for detecting the type of tissue, and a high energy microsecond Er:YAG for ablating bone. The working principle is based on adjusting the energy of the Nd:YAG laser until it is low enough to create a microplasma in the hard tissue only (different energies are required to create plasma in different tissue types). Analyzing the light emitted from the generated microplasma enables real-time feedback to a shutter that prevents the Er:YAG laser from ablating the soft tissue.
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Affiliation(s)
- Hamed Abbasi
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
| | - Lina M Beltrán Bernal
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
| | - Arsham Hamidi
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
| | - Antoine Droneau
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
- Grenoble INP, Grenoble Alpes University, Phelma, France
| | - Ferda Canbaz
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
| | - Raphael Guzman
- Department of Neurosurgery, University Hospital Basel, CH-4056 Basel, Switzerland
| | - Steven L Jacques
- Department of Bioengineering, University of Washington, Seattle, Washington 98195, USA
| | - Philippe C Cattin
- Center for medical Image Analysis and Navigation (CIAN), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
| | - Azhar Zam
- Biomedical Laser and Optics Group (BLOG), Department of Biomedical Engineering, University of Basel, CH-4123 Allschwil, Switzerland
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