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Ye L, Chang CC, Li Q, Tintut Y, Hsu JJ. Advanced Imaging Techniques for Atherosclerosis and Cardiovascular Calcification in Animal Models. J Cardiovasc Dev Dis 2024; 11:410. [PMID: 39728300 DOI: 10.3390/jcdd11120410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 12/13/2024] [Accepted: 12/18/2024] [Indexed: 12/28/2024] Open
Abstract
The detection and assessment of atherosclerosis and cardiovascular calcification can inform risk stratification and therapies to reduce cardiovascular morbidity and mortality. In this review, we provide an overview of current and emerging imaging techniques for assessing atherosclerosis and cardiovascular calcification in animal models. Traditional imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), offer non-invasive approaches of visualizing atherosclerotic calcification in vivo; integration of these techniques with positron emission tomography (PET) imaging adds molecular imaging capabilities, such as detection of metabolically active microcalcifications with 18F-sodium fluoride. Photoacoustic imaging provides high contrast that enables in vivo evaluation of plaque composition, yet this method is limited by optical penetration depth. Light-sheet fluorescence microscopy provides high-resolution, three-dimensional imaging of cardiovascular structures and has been used for ex vivo assessment of atherosclerotic calcification, but its limited tissue penetration and requisite complex sample preparation preclude its use in vivo to evaluate cardiac tissue. Overall, with these evolving imaging tools, our understanding of cardiovascular calcification development in animal models is improving, and the combination of traditional imaging techniques with emerging molecular imaging modalities will enhance our ability to investigate therapeutic strategies for atherosclerotic calcification.
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Affiliation(s)
- Lifang Ye
- Heart Center, Department of Cardiovascular Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou 310014, China
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
| | - Chih-Chiang Chang
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California, Los Angeles, CA 90095, USA
| | - Qian Li
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
| | - Yin Tintut
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Physiology, University of California, Los Angeles, CA 90095, USA
- Department of Orthopedic Surgery, University of California, Los Angeles, CA 90404, USA
| | - Jeffrey J Hsu
- Department of Medicine, University of California, 650 Charles E Young Dr. S, Center for Health Sciences, Room A2-237, Los Angeles, CA 90095, USA
- Department of Bioengineering, University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, CA 90073, USA
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Feng T, Li J, Xie W, Cheng Q, Ta D. Adaptively multi-scale microstructure characterization of cancellous bone via Photoacoustic signal decomposition. ULTRASONICS 2024; 144:107407. [PMID: 39173274 DOI: 10.1016/j.ultras.2024.107407] [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: 12/10/2023] [Revised: 07/09/2024] [Accepted: 07/15/2024] [Indexed: 08/24/2024]
Abstract
Osteoporosis is a systemic disease with a high incidence in the elderly and seriously affects the quality of life of patients. Photoacoustic (PA) technology, which combines the advantages of light and ultrasound, can provide information about the physiological structure and chemical information of biological tissues in a non-invasive and non-radiative way. Due to the complex structural characteristics of bone tissue, PA signals generated by bone tissue are non-stationary and nonlinear. However, conventional PA signal processing methods are not effective for non-stationary signal processing. In this study, an empirical mode decomposition (EMD)-based Hilbert-Huang transform (HHT) PA signal analysis method, called HHT PA signal analysis (HPSA), was developed to assess the microstructure information of bone tissue, which is closely related to bone health. The feasibility of the HPSA method in bone health assessment was proven by numerical simulation and experimental studies on animal samples with different bone volume/total volume (BV/TV) and bone mineral densities. First, based on adaptive EMD, the different modes correlated with multi-scale information were mined from the PA signal, the correlations between different intrinsic mode function (IMF) modes and BV/TVs were analyzed, and the optimal mode for more efficient PA time-frequency analysis was selected. Second, multi-wavelength HPSA was used to assess the changes in the chemical components of the bone tissue. The results demonstrate that the HPSA method can distinguish bones with different BV/TVs and microstructure conditions adaptively with high efficiency. They further emphasize the potential of PA techniques in characterizing biological tissues in bones for early and rapid detection of bone diseases.
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Affiliation(s)
- Ting Feng
- Institute of Biomedical Engineering & Technology, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China.
| | - Jieshu Li
- School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
| | - Weiya Xie
- Institute of Acoustics, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China; Qingdao innovation and development base, Harbin Engineering University, Qingdao 266000, China
| | - Qian Cheng
- Institute of Acoustics, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China.
| | - Dean Ta
- Institute of Biomedical Engineering & Technology, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China; Department of Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
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Pang W, Yuan C, Zhong T, Huang X, Pan Y, Qu J, Nie L, Zhou Y, Lai P. Diagnostic and therapeutic optical imaging in cardiovascular diseases. iScience 2024; 27:111216. [PMID: 39569375 PMCID: PMC11576408 DOI: 10.1016/j.isci.2024.111216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2024] Open
Abstract
Cardiovascular disease (CVD) is one of the most prevalent health threats globally. Traditional diagnostic methods for CVDs, including electrocardiography, ultrasound, and cardiac magnetic resonance imaging, have inherent limitations in real-time monitoring and high-resolution visualization of cardiovascular pathophysiology. In recent years, optical imaging technology has gained considerable attention as a non-invasive, high-resolution, real-time monitoring solution in the study and diagnosis of CVD. This review discusses the latest advancements, and applications of optical techniques in cardiac imaging. We compare the advantages of optical imaging over traditional modalities and especially scrutinize techniques such as optical coherence tomography, photoacoustic imaging, and fluorescence imaging. We summarize their investigations in atherosclerosis, myocardial infarction, and heart valve disease, etc. Additionally, we discuss challenges like deep-tissue imaging and high spatiotemporal resolution adjustment, and review existing solutions such as multimodal integration, artificial intelligence, and enhanced optical probes. This article aims to drive further development in optical imaging technologies to provide more precise and efficient tools for early diagnosis, pathological mechanism exploration, and treatment of CVD.
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Affiliation(s)
- Weiran Pang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Chuqi Yuan
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Tianting Zhong
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Xiazi Huang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yue Pan
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
- Nanchang Research Institute, Sun Yat-Sen University, Nanchang 330096, China
| | - Junle Qu
- Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen 518060, China
| | - Liming Nie
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Yingying Zhou
- College of Professional and Continuing Education, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Puxiang Lai
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- The Joint Research Centre for Biosensing and Precision Theranostics, The Hong Kong Polytechnic University, Hong Kong SAR, China
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Leandri A, Lecrosnier L, Ghazel A, Faure B. Survey on portable sensing technologies for the radial artery characterization. Physiol Meas 2024; 45:10TR01. [PMID: 39411783 DOI: 10.1088/1361-6579/ad838d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2024] [Accepted: 10/04/2024] [Indexed: 11/03/2024]
Abstract
The radial artery, one of the terminal branches of the forearm, is utilized for vascular access and in various non-invasive measurement method, providing crucial medical insights. Various sensor technologies have been developed, each suited to specific characterization requirements. The work presented in this paper is based on a systematic literature review of the main publications relating to this topic. Analysis of the forearm vascular system complex array of anatomical structures shows that the radial artery can be characterized by its size, position, elasticity, tissue evaluation, blood flow and blood composition. The survey of medical procedures for patient monitoring, diagnosis and pre-operative validation shows the use of measures for pulse wave, blood pressure, heart rate, skin temperature, tissue response,…By exploring sensor technologies used for artery characterization, we produce a synthesis of measurement principles, measured phenomena and measurement accuracy for capacitive, piezoresistive, bioimpedance, thermography, fiber optic based, piezoelectric and photoacoustic sensors. A comparative study is conducted for sensor technologies by considering the metrics of the information to be collected and the associated accuracy as well as the portability, the complexity of the processing, the cost and the mode of contact with the arm. Finally, a comprehensive framework is proposed to facilitate informed decisions in the development of medical devices tailored to specific characterization needs.
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Affiliation(s)
- Aurélia Leandri
- MUniv Rouen Normandie, ESIGELEC, Normandie Univ, IRSEEM UR 4353, F-76000 Rouen, France
- ARTERYA, F-14200 Hérouville-Saint-Clair, France
| | - Louis Lecrosnier
- MUniv Rouen Normandie, ESIGELEC, Normandie Univ, IRSEEM UR 4353, F-76000 Rouen, France
| | - Adel Ghazel
- MUniv Rouen Normandie, ESIGELEC, Normandie Univ, IRSEEM UR 4353, F-76000 Rouen, France
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Mirg S, Turner KL, Chen H, Drew PJ, Kothapalli SR. Photoacoustic imaging for microcirculation. Microcirculation 2022; 29:e12776. [PMID: 35793421 PMCID: PMC9870710 DOI: 10.1111/micc.12776] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 06/13/2022] [Accepted: 06/28/2022] [Indexed: 01/26/2023]
Abstract
Microcirculation facilitates the blood-tissue exchange of nutrients and regulates blood perfusion. It is, therefore, essential in maintaining tissue health. Aberrations in microcirculation are potentially indicative of underlying cardiovascular and metabolic pathologies. Thus, quantitative information about it is of great clinical relevance. Photoacoustic imaging (PAI) is a capable technique that relies on the generation of imaging contrast via the absorption of light and can image at micron-scale resolution. PAI is especially desirable to map microvasculature as hemoglobin strongly absorbs light and can generate a photoacoustic signal. This paper reviews the current state of the art for imaging microvascular networks using photoacoustic imaging. We further describe how quantitative information about blood dynamics such as the total hemoglobin concentration, oxygen saturation, and blood flow rate is obtained using PAI. We also discuss its importance in understanding key pathophysiological processes in neurovascular, cardiovascular, ophthalmic, and cancer research fields. We then discuss the current challenges and limitations of PAI and the approaches that can help overcome these limitations. Finally, we provide the reader with an overview of future trends in the field of PAI for imaging microcirculation.
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Affiliation(s)
- Shubham Mirg
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
| | - Kevin L. Turner
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
| | - Haoyang Chen
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA 16802, USA
| | - Patrick J. Drew
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA 16802, USA
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
- Penn State Cancer Institute, Pennsylvania State University, Hershey, PA 17033, USA
- Graduate Program in Acoustics, Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA 16802, USA
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Singh H, Rehman TB, Gangadhar C, Anand R, Sindhwani N, Babu MVS. Accuracy detection of coronary artery disease using machine learning algorithms. APPLIED NANOSCIENCE 2021. [DOI: 10.1007/s13204-021-02036-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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