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Yang L, Gao Z, Wang C, Wang H, Dai J, Liu Y, Qin Y, Dai M, Cao X, Zhao Z. Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system. Physiol Meas 2024; 45:025004. [PMID: 38266301 DOI: 10.1088/1361-6579/ad2215] [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: 08/14/2023] [Accepted: 01/24/2024] [Indexed: 01/26/2024]
Abstract
Objective.Wearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers.Approach.A total of 96 test sets of EIT measurement was recorded in 12 healthy subjects by employing adjacent and opposite current injection patterns with four amplitudes of small current (i.e. 1 mA, 500 uA, 250 uA and 125 uA). The performance of the two injection patterns with various currents was evaluated in terms of signal-to-noise ratio (SNR) of thorax impedance, EIT image metrics and EIT-based clinical parameters.Main results.Compared with adjacent injection, opposite injection had higher SNR (p< 0.01), less inverse artifacts (p< 0.01), and less boundary artifacts (p< 0.01) with the same current amplitude. In addition, opposite injection exhibited more stable EIT-based clinical parameters (p< 0.01) across the current range. For adjacent injection, significant differences were found for three EIT image metrics (p< 0.05) and four EIT-based clinical parameters (p< 0.01) between the group of 125 uA and the other groups.Significance.For better performance of wearable pulmonary EIT, currents greater than 250 uA should be used in opposite injection, 500 uA in adjacent one, to ensure a high level of SNR, a high quality of reconstructed image as well as a high reliability of clinical parameters.
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Affiliation(s)
- Lin Yang
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Zhijun Gao
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Chunchen Wang
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Hang Wang
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Jing Dai
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Yang Liu
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Yilong Qin
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Meng Dai
- Department of Biomedical Engineering, Air Force Medical University, Xi'an, People's Republic of China
| | - Xinsheng Cao
- Department of Aerospace Medicine, Air Force Medical University, Xi'an, People's Republic of China
| | - Zhanqi Zhao
- School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, People's Republic of China
- Department of Critical Care Medicine, Peking Union Medical College Hospital, Beijing, People's Republic of China
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Singh RK, Nayak NP, Behl T, Arora R, Anwer MK, Gulati M, Bungau SG, Brisc MC. Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences. Diagnostics (Basel) 2024; 14:139. [PMID: 38248016 PMCID: PMC11154438 DOI: 10.3390/diagnostics14020139] [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: 11/10/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
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Affiliation(s)
- Rahul Kumar Singh
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Nirlipta Priyadarshini Nayak
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Tapan Behl
- Amity School of Pharmaceutical Sciences, Amity University, Mohali 140306, Punjab, India
| | - Rashmi Arora
- Chitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, India;
| | - Md. Khalid Anwer
- Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia;
| | - Monica Gulati
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 1444411, Punjab, India;
- Australian Research Centre in Complementary and Integrative Medicine, Faculty of Health, University of Technology Sydney, Ultimo, NSW 20227, Australia
| | - Simona Gabriela Bungau
- Department of Pharmacy, Faculty of Medicine and Pharmacy, University of Oradea, 410028 Oradea, Romania
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania
| | - Mihaela Cristina Brisc
- Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania;
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Shishvan OR, Abdelwahab A, da Rosa NB, Saulnier GJ, Mueller JL, Newell J, Isaacson D. ACT5 Electrical Impedance Tomography System. IEEE Trans Biomed Eng 2024; 71:227-236. [PMID: 37459258 PMCID: PMC10798853 DOI: 10.1109/tbme.2023.3295771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
OBJECTIVE This article introduces the Adaptive Current Tomograph 5 (ACT5) Electrical Impedance Tomography (EIT) system. ACT5 is a 32 electrode applied-current multiple-source EIT system that can display real-time images of conductivity and susceptivity at 27 frames per second. The adaptive current sources in ACT5 can apply fully programmable current patterns with frequencies varying from 5 kHz to 500 kHz. The system also displays real-time ECG readings during the EIT imaging process. METHODS The hardware and software design and specifications are presented, including the current source design, FPGA hardware, safety features, calibration, and shunt impedance measurement. RESULTS Images of conductivity and susceptivity are presented from ACT5 data collected on tank phantoms and a human subject illustrating the system's ability to provide real-time images of pulsatile perfusion and ECG traces. SIGNIFICANCE The portability, high signal-to-noise ratio, and flexibility of applied currents over a wide range of frequencies enable this instrument to be used to obtain useful human subject data with relative clinical ease.
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Li X, Liu K, Xing L, Rubinsky B. A review of tumor treating fields (TTFields): advancements in clinical applications and mechanistic insights. Radiol Oncol 2023; 57:279-291. [PMID: 37665740 PMCID: PMC10476910 DOI: 10.2478/raon-2023-0044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 08/04/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Tumor Treating Fields (TTFields) is a non-invasive modality for cancer treatment that utilizes a specific sinusoidal electric field ranging from 100 kHz to 300 kHz, with an intensity of 1 V/cm to 3 V/cm. Its purpose is to inhibit cancer cell proliferation and induce cell death. Despite promising outcomes from clinical trials, TTFields have received FDA approval for the treatment of glioblastoma multiforme (GBM) and malignant pleural mesothelioma (MPM). Nevertheless, global acceptance of TTFields remains limited. To enhance its clinical application in other types of cancer and gain a better understanding of its mechanisms of action, this review aims to summarize the current research status by examining existing literature on TTFields' clinical trials and mechanism studies. CONCLUSIONS Through this comprehensive review, we seek to stimulate novel ideas and provide physicians, patients, and researchers with a better comprehension of the development of TTFields and its potential applications in cancer treatment.
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Affiliation(s)
- Xing Li
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing, Jiang Su, China
| | - Kaida Liu
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing, Jiang Su, China
| | - Lidong Xing
- College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nan Jing, Jiang Su, China
| | - Boris Rubinsky
- Department of Mechanical Engineering, University of California Berkeley, BerkeleyCA, United States of America
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