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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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Jantzie LL. Placental mediated mechanisms of perinatal brain injury. Exp Neurol 2022; 358:114229. [PMID: 36152499 PMCID: PMC10115519 DOI: 10.1016/j.expneurol.2022.114229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Lauren L Jantzie
- Division of Neonatal-Perinatal Medicine, Departments of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; Neurosciences Intensive Care Nursery, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; Division of Pediatric Neurosurgery, Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; Kennedy Krieger Institute, Baltimore, MD, United States of America
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Biswas D, Roy S, Vasudevan S. Biomedical Application of Photoacoustics: A Plethora of Opportunities. MICROMACHINES 2022; 13:1900. [PMID: 36363921 PMCID: PMC9692656 DOI: 10.3390/mi13111900] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/19/2022] [Accepted: 10/29/2022] [Indexed: 06/16/2023]
Abstract
The photoacoustic (PA) technique is a non-invasive, non-ionizing hybrid technique that exploits laser irradiation for sample excitation and acquires an ultrasound signal generated due to thermoelastic expansion of the sample. Being a hybrid technique, PA possesses the inherent advantages of conventional optical (high resolution) and ultrasonic (high depth of penetration in biological tissue) techniques and eliminates some of the major limitations of these conventional techniques. Hence, PA has been employed for different biomedical applications. In this review, we first discuss the basic physics of PA. Then, we discuss different aspects of PA techniques, which includes PA imaging and also PA frequency spectral analysis. The theory of PA signal generation, detection and analysis is also detailed in this work. Later, we also discuss the major biomedical application area of PA technique.
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Affiliation(s)
- Deblina Biswas
- School of Bioengineering and Food Technology, Shoolini University, Solan 173229, HP, India
| | - Swarup Roy
- School of Bioengineering and Food Technology, Shoolini University, Solan 173229, HP, India
| | - Srivathsan Vasudevan
- Discipline of Electrical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol 453552, MP, India
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An exploratory study to identify neonatal arterial ischemic stroke: A single-center study. Brain Dev 2022; 44:672-680. [PMID: 36058756 DOI: 10.1016/j.braindev.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/03/2022] [Accepted: 08/18/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Neonatal arterial ischemic stroke (NAIS) presents as seizures, including convulsions, subtle seizures, and apnea, and most patients experience neurological sequelae. Diagnosis is often delayed owing to low test sensitivity. The present study aimed to identify the early clinical diagnostic factors for NAIS in neonates with seizures. METHODS The present study included 54 patients born at ≥36 weeks of gestation during the last 15 years who presented to the neonatal intensive care unit with neonatal seizures and underwent brain magnetic resonance imaging (MRI), 6 of whom were diagnosed with NAIS. Maternal background, clinical characteristics, and transcranial pulsed Doppler sonography results were retrospectively reviewed. RESULTS Of the 24 patients who presented with convulsions or subtle seizures, 3 (13%) were diagnosed with NAIS and 3 of 30 patients (10%) presented with apnea. Maternal premature ventricular contraction complications were higher in the NAIS group than in the non-NAIS group (p = 0.01). NAIS group showed lower mean middle cerebral artery (MCA) resistance index (RI) was lower the non-NAIS group (p = 0.009), while the left-right RI difference (p = 0.019), mean MCA blood velocity (MnV; p = 0.04), and left-right MnV difference (p < 0.001) in cerebral blood flow velocities (CBFVs) were higher in the NAIS group. CONCLUSIONS Our results revealed that maternal arrhythmia may be a diagnostic factor for NAIS in neonates with seizures. Early brain MRI is essential in neonates with seizures and findings of low MCA-RI, high MCA-MnV, or high left-right difference in CBFVs to distinguish between NAIS and non-NAIS.
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Wen Y, Guo D, Zhang J, Liu X, Liu T, Li L, Jiang S, Wu D, Jiang H. Clinical photoacoustic/ultrasound dual-modal imaging: Current status and future trends. Front Physiol 2022; 13:1036621. [PMID: 36388111 PMCID: PMC9651137 DOI: 10.3389/fphys.2022.1036621] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 10/05/2022] [Indexed: 08/24/2023] Open
Abstract
Photoacoustic tomography (PAT) is an emerging biomedical imaging modality that combines optical and ultrasonic imaging, providing overlapping fields of view. This hybrid approach allows for a natural integration of PAT and ultrasound (US) imaging in a single platform. Due to the similarities in signal acquisition and processing, the combination of PAT and US imaging creates a new hybrid imaging for novel clinical applications. Over the recent years, particular attention is paid to the development of PAT/US dual-modal systems highlighting mutual benefits in clinical cases, with an aim of substantially improving the specificity and sensitivity for diagnosis of diseases. The demonstrated feasibility and accuracy in these efforts open an avenue of translating PAT/US imaging to practical clinical applications. In this review, the current PAT/US dual-modal imaging systems are discussed in detail, and their promising clinical applications are presented and compared systematically. Finally, this review describes the potential impacts of these combined systems in the coming future.
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Affiliation(s)
- Yanting Wen
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Dan Guo
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
| | - Jing Zhang
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Xiaotian Liu
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
| | - Ting Liu
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
| | - Lu Li
- Department of Ultrasound Imaging, The Fifth People’s Hospital of Chengdu, Chengdu, China
| | - Shixie Jiang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Dan Wu
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Huabei Jiang
- Department of Medical Engineering, University of South Florida, Tampa, FL, United States
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