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Yang X, Huang X, Wei C, Yu J, Yu X, Dong C, Chen J, Chen R, Wu X, Yu Z, Sun B, Wang J, Liu H, Han W, Sun B, Jiang Z, Ding J, Liu Z, Peng J, Ni D, Deng X, Liu L, Gou Z. An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study. Heart Rhythm 2024:S1547-5271(24)00078-X. [PMID: 38266752 DOI: 10.1016/j.hrthm.2024.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/04/2024] [Accepted: 01/15/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND The motion relationship and time intervals of the pulsed-wave Doppler (PWD) spectrum are essential for diagnosing fetal arrhythmia. However, few technologies currently are available to automatically calculate fetal cardiac time intervals (CTIs). OBJECTIVE The purpose of this study was to develop a fetal heart rhythm intelligent quantification system (HR-IQS) for the automatic extraction of CTIs and establish the normal reference range for fetal CTIs. METHODS A total of 6498 PWD spectrums of 2630 fetuses over the junction between the left ventricular inflow and outflow tracts were recorded across 14 centers. E, A, and V waves were manually labeled by 3 experienced fetal cardiologists, with 17 CTIs extracted. Five-fold cross-validation was performed for training and testing of the deep learning model. Agreement between the manual and HR-IQS-based values was evaluated using the intraclass correlation coefficient and Spearman's rank correlation coefficient. The Jarque-Bera test was applied to evaluate the normality of CTIs' distributions, and the normal reference range of 17 CTIs was established with quantile regression. Arrhythmia subset was compared with the non-arrhythmia subset using the Mann-Whitney U test. RESULTS Significant positive correlation (P <.001) and moderate-to-excellent consistency (P <.001) between the manual and HR-IQS automated measurements of CTIs was found. The distribution of CTIs was non-normal (P <.001). The normal range (2.5th to 97.5th percentiles) was successfully established for the 17 CTIs. CONCLUSIONS Using our HR-IQS is feasible for the automated calculation of CTIs in practice and thus could provide a promising tool for the assessment of fetal rhythm and function.
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Affiliation(s)
- Xin Yang
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Xiaoqiong Huang
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Chenchen Wei
- Center for Cardiovascular Disease, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu, China
| | - Junxuan Yu
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China; Shenzhen RayShape Medical Technology Co., Ltd, Shenzhen, Guangdong, China
| | - Xuejuan Yu
- Department of Ultrasonography, Suzhou Xiangcheng People's Hospital, Suzhou, Jiangsu, China
| | - Caixia Dong
- Department of Ultrasonography, Wulin Hospital, Hangzhou, Zhejiang, China
| | - Ju Chen
- Department of Ultrasonography, Taicang First People's Hospital, Suzhou, Jiangsu, China
| | - Ruifeng Chen
- Department of Ultrasound Diagnosis, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China
| | - Xiafang Wu
- Department of Ultrasonography, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, China
| | - Zhuan Yu
- Department of Ultrasonography, The Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China
| | - Baojuan Sun
- Department of Ultrasonography, Huai'an Maternal and Child Health Hospital, Huai'an, Jiangsu, China
| | - Junli Wang
- Department of Ultrasonography, Wuhu No.2 People's Hospital, Wuhu, Anhui, China
| | - Hongmei Liu
- Department of Ultrasonography, Panzhou Emerging Hospital, Panzhou, Guizhou, China
| | - Wen Han
- Department of Ultrasonography, Suzhou Gaoxin District People's Hospital, Suzhou, Jiangsu, China
| | - Biyun Sun
- Department of Ultrasonography, The Affiliated Yijishan Hospital of Wannan Medical University, Wuhu, Anhui, China
| | - Zhiyong Jiang
- Department of Ultrasonography, The Huaren Hospital, Wuhu, Zhejiang, China
| | - Jie Ding
- Department of Ultrasonography, The Affiliated Suzhou Hospital of Nanjing University, Suzhou, Jiangsu, China
| | - Zhe Liu
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China; Shenzhen RayShape Medical Technology Co., Ltd, Shenzhen, Guangdong, China
| | - Jin Peng
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China; Shenzhen RayShape Medical Technology Co., Ltd, Shenzhen, Guangdong, China
| | - Dong Ni
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Xuedong Deng
- Center for Medical Ultrasound, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu, China
| | - Lian Liu
- National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China; Shenzhen RayShape Medical Technology Co., Ltd, Shenzhen, Guangdong, China.
| | - Zhongshan Gou
- Center for Cardiovascular Disease, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu, China.
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Jiménez-González A, Salas-Márquez U. Time-frequency characteristics of the vibrations underlying the first fetal heart sound: a preliminary study. Med Biol Eng Comput 2023; 61:739-756. [PMID: 36598675 DOI: 10.1007/s11517-022-02756-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 12/22/2022] [Indexed: 01/05/2023]
Abstract
This work studied, for the first time, the time-frequency characteristics of the vibrations underlying the first fetal heart sound (S1). To this end, the continuous wavelet transform was used to produce time-energy and time-frequency representations of S1 from where five vibrations were studied by their timing, energy, and frequency characteristics in three gestational age groups (early, G1, preterm, G2, and term, G3). Results on a dataset of 1111 S1s (9 phonocardiograms between 33 and 40 weeks) indicate that such representations uncovered a set of five well-defined, non-overlapped, and large-energy vibrations whose features presented interesting behaviors. Thus, for each group, while the timing characteristics of the five vibrations were likely to be statically different, their frequencies were similar. Also, the energies of the vibrations were likely to be different only in G2 and G3. Alternatively, while the frequencies and energies of each vibration were likely to statistically change among groups (excluding the energy of the third vibration), the timings were more likely to change only from G1 to G2 and from G2 to G3. Therefore, this methodology seems suitable to detect and study the generating vibrations of S1. Future work will test the correlation between these vibrations and the valvular events.
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Affiliation(s)
- Aída Jiménez-González
- Department of Electrical Engineering, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Alcaldía Iztapalapa, C.P. 09340, México City, México.
| | - Usiel Salas-Márquez
- Department of Electrical Engineering, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Alcaldía Iztapalapa, C.P. 09340, México City, México
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Kodkin V. Cardiotocography in Obstetrics: New Solutions for "Routine" Technology. Sensors (Basel) 2022; 22:5126. [PMID: 35890806 PMCID: PMC9320740 DOI: 10.3390/s22145126] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 06/21/2022] [Accepted: 07/04/2022] [Indexed: 06/15/2023]
Abstract
This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 years. During this time, it has undergone many upgrades and has been characterized several times as a hopelessly outdated routine technology. Over the past 5-7 years, many in-depth studies and review papers on cardiotocography have appeared, which revealed both the problems and prospects of the technology. Basically, hopes are associated with artificial intelligence, which should increase the accuracy of the analysis of initially inaccurate measurements obtained using ultrasonic testing. At the same time, after the introduction of pulsed operating modes and the appearance of multi-chip sensors, the quality of the original signal remains practically unchanged. This circumstance makes the prospects of the technology very problematic. However, until now, there has not been a reliable replacement for this screening, which is equally safe, non-invasive, and accessible to a wide range of specialists, medical institutions, and patients. The paper discusses and substantiates proposals for improving the technology based on original (different from traditional CTG) methods of processing information received from ultrasonic sensors, which, in the author's opinion, allow for solving the main problems of CTG: identifying the correct direction of radiation to the fetal heart and to reliably evaluate beat-to-beat heart rate.
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Affiliation(s)
- Vladimir Kodkin
- Department of Electric Drive and Mechatronics, South Ural State University, 454080 Chelyabinsk, Russia
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Ribeiro M, Monteiro-Santos J, Castro L, Antunes L, Costa-Santos C, Teixeira A, Henriques TS. Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review. Front Med (Lausanne) 2021; 8:661226. [PMID: 34917624 PMCID: PMC8669823 DOI: 10.3389/fmed.2021.661226] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 11/04/2021] [Indexed: 12/19/2022] Open
Abstract
The analysis of fetal heart rate variability has served as a scientific and diagnostic tool to quantify cardiac activity fluctuations, being good indicators of fetal well-being. Many mathematical analyses were proposed to evaluate fetal heart rate variability. We focused on non-linear analysis based on concepts of chaos, fractality, and complexity: entropies, compression, fractal analysis, and wavelets. These methods have been successfully applied in the signal processing phase and increase knowledge about cardiovascular dynamics in healthy and pathological fetuses. This review summarizes those methods and investigates how non-linear measures are related to each paper's research objectives. Of the 388 articles obtained in the PubMed/Medline database and of the 421 articles in the Web of Science database, 270 articles were included in the review after all exclusion criteria were applied. While approximate entropy is the most used method in classification papers, in signal processing, the most used non-linear method was Daubechies wavelets. The top five primary research objectives covered by the selected papers were detection of signal processing, hypoxia, maturation or gestational age, intrauterine growth restriction, and fetal distress. This review shows that non-linear indices can be used to assess numerous prenatal conditions. However, they are not yet applied in clinical practice due to some critical concerns. Some studies show that the combination of several linear and non-linear indices would be ideal for improving the analysis of the fetus's well-being. Future studies should narrow the research question so a meta-analysis could be performed, probing the indices' performance.
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Affiliation(s)
- Maria Ribeiro
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.,Computer Science Department, Faculty of Sciences, University of Porto, Porto, Portugal
| | - João Monteiro-Santos
- Centre for Health Technology and Services Research, Faculty of Medicine University of Porto, Porto, Portugal.,Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal
| | - Luísa Castro
- Centre for Health Technology and Services Research, Faculty of Medicine University of Porto, Porto, Portugal.,Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal.,School of Health of Polytechnic of Porto, Porto, Portugal
| | - Luís Antunes
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.,Computer Science Department, Faculty of Sciences, University of Porto, Porto, Portugal
| | - Cristina Costa-Santos
- Centre for Health Technology and Services Research, Faculty of Medicine University of Porto, Porto, Portugal.,Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal
| | - Andreia Teixeira
- Centre for Health Technology and Services Research, Faculty of Medicine University of Porto, Porto, Portugal.,Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal.,Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal
| | - Teresa S Henriques
- Centre for Health Technology and Services Research, Faculty of Medicine University of Porto, Porto, Portugal.,Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal
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