An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study
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). The purpose of this study was to develop a fetal heart...
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| Veröffentlicht in: | Heart rhythm 2024-05, Vol.21 (5), p.600-609 |
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| creator | Yang, Xin Huang, Xiaoqiong Wei, Chenchen Yu, Junxuan Yu, Xuejuan Dong, Caixia Chen, Ju Chen, Ruifeng Wu, Xiafang Yu, Zhuan Sun, Baojuan Wang, Junli Liu, Hongmei Han, Wen Sun, Biyun Jiang, Zhiyong Ding, Jie Liu, Zhe Peng, Jin Ni, Dong Deng, Xuedong Liu, Lian Gou, Zhongshan |
| description | 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).
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.
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.
Significant positive correlation (P |
| doi_str_mv | 10.1016/j.hrthm.2024.01.024 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2918514814</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S154752712400078X</els_id><sourcerecordid>2918514814</sourcerecordid><originalsourceid>FETCH-LOGICAL-c359t-182a9b7cd454d64ed870643819636348969551e4e260b1c874407afec6fcc66c3</originalsourceid><addsrcrecordid>eNp9kEtLAzEUhYMovn-BIFm6mTHvyQguiviCghtdhzRzx6bMoyYZof_e1KpLV-cGzsm590PogpKSEqquV-UypGVfMsJESWiZZQ8dUylVwXVF97ezqArJKnqETmJcEcJqRfghOuKaKVVJdozeZwP2Q4Ku8-8wJPwx2SH51jub_DjguIkJetyOAbeQbIeXYEPCYbnJzdjGCDH2OXeDZ7ifuuRdfkDA6zDGNbjkPwHHNDWbM3TQ2i7C-Y-eoreH-9e7p2L-8vh8N5sXjss6FVQzWy8q1wgpGiWg0RVRgmtaK6640LWqpaQggCmyoE5XQpDKtuBU65xSjp-iq92_eYOPCWIyvY8un2cHGKdoWE21pEJTka18Z3V52RigNevgexs2hhKzJWxW5puw2RI2hJosOXX5UzAtemj-Mr9Is-F2Z4B85qeHYKLzMDhofMhETDP6fwu-ANY6jx0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2918514814</pqid></control><display><type>article</type><title>An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Yang, Xin ; Huang, Xiaoqiong ; Wei, Chenchen ; Yu, Junxuan ; Yu, Xuejuan ; Dong, Caixia ; Chen, Ju ; Chen, Ruifeng ; Wu, Xiafang ; Yu, Zhuan ; Sun, Baojuan ; Wang, Junli ; Liu, Hongmei ; Han, Wen ; Sun, Biyun ; Jiang, Zhiyong ; Ding, Jie ; Liu, Zhe ; Peng, Jin ; Ni, Dong ; Deng, Xuedong ; Liu, Lian ; Gou, Zhongshan</creator><creatorcontrib>Yang, Xin ; Huang, Xiaoqiong ; Wei, Chenchen ; Yu, Junxuan ; Yu, Xuejuan ; Dong, Caixia ; Chen, Ju ; Chen, Ruifeng ; Wu, Xiafang ; Yu, Zhuan ; Sun, Baojuan ; Wang, Junli ; Liu, Hongmei ; Han, Wen ; Sun, Biyun ; Jiang, Zhiyong ; Ding, Jie ; Liu, Zhe ; Peng, Jin ; Ni, Dong ; Deng, Xuedong ; Liu, Lian ; Gou, Zhongshan</creatorcontrib><description>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).
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.
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.
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.
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.
[Display omitted]</description><identifier>ISSN: 1547-5271</identifier><identifier>ISSN: 1556-3871</identifier><identifier>EISSN: 1556-3871</identifier><identifier>DOI: 10.1016/j.hrthm.2024.01.024</identifier><identifier>PMID: 38266752</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Arrhythmias, Cardiac - diagnosis ; Arrhythmias, Cardiac - physiopathology ; Deep learning ; Echocardiography ; Female ; Fetal arrhythmia ; Fetal cardiac time interval ; Fetal Heart - diagnostic imaging ; Fetal Heart - physiology ; Gestational Age ; Heart Rate, Fetal - physiology ; Heart rhythm intelligent quantification system ; Humans ; Pregnancy ; Prospective Studies ; Pulsed-wave Doppler ; Ultrasonography, Prenatal - methods</subject><ispartof>Heart rhythm, 2024-05, Vol.21 (5), p.600-609</ispartof><rights>2024 Heart Rhythm Society</rights><rights>Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-182a9b7cd454d64ed870643819636348969551e4e260b1c874407afec6fcc66c3</citedby><cites>FETCH-LOGICAL-c359t-182a9b7cd454d64ed870643819636348969551e4e260b1c874407afec6fcc66c3</cites><orcidid>0009-0006-3611-5063</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.hrthm.2024.01.024$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38266752$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Xin</creatorcontrib><creatorcontrib>Huang, Xiaoqiong</creatorcontrib><creatorcontrib>Wei, Chenchen</creatorcontrib><creatorcontrib>Yu, Junxuan</creatorcontrib><creatorcontrib>Yu, Xuejuan</creatorcontrib><creatorcontrib>Dong, Caixia</creatorcontrib><creatorcontrib>Chen, Ju</creatorcontrib><creatorcontrib>Chen, Ruifeng</creatorcontrib><creatorcontrib>Wu, Xiafang</creatorcontrib><creatorcontrib>Yu, Zhuan</creatorcontrib><creatorcontrib>Sun, Baojuan</creatorcontrib><creatorcontrib>Wang, Junli</creatorcontrib><creatorcontrib>Liu, Hongmei</creatorcontrib><creatorcontrib>Han, Wen</creatorcontrib><creatorcontrib>Sun, Biyun</creatorcontrib><creatorcontrib>Jiang, Zhiyong</creatorcontrib><creatorcontrib>Ding, Jie</creatorcontrib><creatorcontrib>Liu, Zhe</creatorcontrib><creatorcontrib>Peng, Jin</creatorcontrib><creatorcontrib>Ni, Dong</creatorcontrib><creatorcontrib>Deng, Xuedong</creatorcontrib><creatorcontrib>Liu, Lian</creatorcontrib><creatorcontrib>Gou, Zhongshan</creatorcontrib><title>An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study</title><title>Heart rhythm</title><addtitle>Heart Rhythm</addtitle><description>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).
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.
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.
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.
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.
[Display omitted]</description><subject>Arrhythmias, Cardiac - diagnosis</subject><subject>Arrhythmias, Cardiac - physiopathology</subject><subject>Deep learning</subject><subject>Echocardiography</subject><subject>Female</subject><subject>Fetal arrhythmia</subject><subject>Fetal cardiac time interval</subject><subject>Fetal Heart - diagnostic imaging</subject><subject>Fetal Heart - physiology</subject><subject>Gestational Age</subject><subject>Heart Rate, Fetal - physiology</subject><subject>Heart rhythm intelligent quantification system</subject><subject>Humans</subject><subject>Pregnancy</subject><subject>Prospective Studies</subject><subject>Pulsed-wave Doppler</subject><subject>Ultrasonography, Prenatal - methods</subject><issn>1547-5271</issn><issn>1556-3871</issn><issn>1556-3871</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtLAzEUhYMovn-BIFm6mTHvyQguiviCghtdhzRzx6bMoyYZof_e1KpLV-cGzsm590PogpKSEqquV-UypGVfMsJESWiZZQ8dUylVwXVF97ezqArJKnqETmJcEcJqRfghOuKaKVVJdozeZwP2Q4Ku8-8wJPwx2SH51jub_DjguIkJetyOAbeQbIeXYEPCYbnJzdjGCDH2OXeDZ7ifuuRdfkDA6zDGNbjkPwHHNDWbM3TQ2i7C-Y-eoreH-9e7p2L-8vh8N5sXjss6FVQzWy8q1wgpGiWg0RVRgmtaK6640LWqpaQggCmyoE5XQpDKtuBU65xSjp-iq92_eYOPCWIyvY8un2cHGKdoWE21pEJTka18Z3V52RigNevgexs2hhKzJWxW5puw2RI2hJosOXX5UzAtemj-Mr9Is-F2Z4B85qeHYKLzMDhofMhETDP6fwu-ANY6jx0</recordid><startdate>202405</startdate><enddate>202405</enddate><creator>Yang, Xin</creator><creator>Huang, Xiaoqiong</creator><creator>Wei, Chenchen</creator><creator>Yu, Junxuan</creator><creator>Yu, Xuejuan</creator><creator>Dong, Caixia</creator><creator>Chen, Ju</creator><creator>Chen, Ruifeng</creator><creator>Wu, Xiafang</creator><creator>Yu, Zhuan</creator><creator>Sun, Baojuan</creator><creator>Wang, Junli</creator><creator>Liu, Hongmei</creator><creator>Han, Wen</creator><creator>Sun, Biyun</creator><creator>Jiang, Zhiyong</creator><creator>Ding, Jie</creator><creator>Liu, Zhe</creator><creator>Peng, Jin</creator><creator>Ni, Dong</creator><creator>Deng, Xuedong</creator><creator>Liu, Lian</creator><creator>Gou, Zhongshan</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0009-0006-3611-5063</orcidid></search><sort><creationdate>202405</creationdate><title>An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study</title><author>Yang, Xin ; 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However, few technologies currently are available to automatically calculate fetal cardiac time intervals (CTIs).
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.
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.
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.
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.
[Display omitted]</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>38266752</pmid><doi>10.1016/j.hrthm.2024.01.024</doi><tpages>10</tpages><orcidid>https://orcid.org/0009-0006-3611-5063</orcidid></addata></record> |
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| subjects | Arrhythmias, Cardiac - diagnosis Arrhythmias, Cardiac - physiopathology Deep learning Echocardiography Female Fetal arrhythmia Fetal cardiac time interval Fetal Heart - diagnostic imaging Fetal Heart - physiology Gestational Age Heart Rate, Fetal - physiology Heart rhythm intelligent quantification system Humans Pregnancy Prospective Studies Pulsed-wave Doppler Ultrasonography, Prenatal - methods |
| title | An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study |
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