Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity
Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) o...
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| Autor*in: |
DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Chinesisch |
| Erschienen: |
2022 |
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In: Zhenduanxue lilun yu shijian - Editorial Office of Journal of Diagnostics Concepts & Practice, 2022, 21(2022), 03, Seite 326-330 |
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| Übergeordnetes Werk: |
volume:21 ; year:2022 ; number:03 ; pages:326-330 |
| Links: |
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| DOI / URN: |
10.16150/j.1671-2870.2022.03.006 |
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DOAJ01557265X |
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| 520 | |a Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. | ||
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10.16150/j.1671-2870.2022.03.006 doi (DE-627)DOAJ01557265X (DE-599)DOAJ47e8c1c669e041608a34efb0522c90a4 DE-627 ger DE-627 rakwb chi DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao verfasserin aut Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |radiomics|fetal lung maturity|neonatal respiratory morbidity|fetal lung ultrasound|pregnancy complications Medicine R In Zhenduanxue lilun yu shijian Editorial Office of Journal of Diagnostics Concepts & Practice, 2022 21(2022), 03, Seite 326-330 (DE-627)DOAJ000151246 16712870 nnns volume:21 year:2022 number:03 pages:326-330 https://doi.org/10.16150/j.1671-2870.2022.03.006 kostenfrei https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 kostenfrei http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf kostenfrei https://doaj.org/toc/1671-2870 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA AR 21 2022 03 326-330 |
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10.16150/j.1671-2870.2022.03.006 doi (DE-627)DOAJ01557265X (DE-599)DOAJ47e8c1c669e041608a34efb0522c90a4 DE-627 ger DE-627 rakwb chi DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao verfasserin aut Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |radiomics|fetal lung maturity|neonatal respiratory morbidity|fetal lung ultrasound|pregnancy complications Medicine R In Zhenduanxue lilun yu shijian Editorial Office of Journal of Diagnostics Concepts & Practice, 2022 21(2022), 03, Seite 326-330 (DE-627)DOAJ000151246 16712870 nnns volume:21 year:2022 number:03 pages:326-330 https://doi.org/10.16150/j.1671-2870.2022.03.006 kostenfrei https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 kostenfrei http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf kostenfrei https://doaj.org/toc/1671-2870 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA AR 21 2022 03 326-330 |
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10.16150/j.1671-2870.2022.03.006 doi (DE-627)DOAJ01557265X (DE-599)DOAJ47e8c1c669e041608a34efb0522c90a4 DE-627 ger DE-627 rakwb chi DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao verfasserin aut Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |radiomics|fetal lung maturity|neonatal respiratory morbidity|fetal lung ultrasound|pregnancy complications Medicine R In Zhenduanxue lilun yu shijian Editorial Office of Journal of Diagnostics Concepts & Practice, 2022 21(2022), 03, Seite 326-330 (DE-627)DOAJ000151246 16712870 nnns volume:21 year:2022 number:03 pages:326-330 https://doi.org/10.16150/j.1671-2870.2022.03.006 kostenfrei https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 kostenfrei http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf kostenfrei https://doaj.org/toc/1671-2870 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA AR 21 2022 03 326-330 |
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10.16150/j.1671-2870.2022.03.006 doi (DE-627)DOAJ01557265X (DE-599)DOAJ47e8c1c669e041608a34efb0522c90a4 DE-627 ger DE-627 rakwb chi DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao verfasserin aut Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |radiomics|fetal lung maturity|neonatal respiratory morbidity|fetal lung ultrasound|pregnancy complications Medicine R In Zhenduanxue lilun yu shijian Editorial Office of Journal of Diagnostics Concepts & Practice, 2022 21(2022), 03, Seite 326-330 (DE-627)DOAJ000151246 16712870 nnns volume:21 year:2022 number:03 pages:326-330 https://doi.org/10.16150/j.1671-2870.2022.03.006 kostenfrei https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 kostenfrei http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf kostenfrei https://doaj.org/toc/1671-2870 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA AR 21 2022 03 326-330 |
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10.16150/j.1671-2870.2022.03.006 doi (DE-627)DOAJ01557265X (DE-599)DOAJ47e8c1c669e041608a34efb0522c90a4 DE-627 ger DE-627 rakwb chi DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao verfasserin aut Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |radiomics|fetal lung maturity|neonatal respiratory morbidity|fetal lung ultrasound|pregnancy complications Medicine R In Zhenduanxue lilun yu shijian Editorial Office of Journal of Diagnostics Concepts & Practice, 2022 21(2022), 03, Seite 326-330 (DE-627)DOAJ000151246 16712870 nnns volume:21 year:2022 number:03 pages:326-330 https://doi.org/10.16150/j.1671-2870.2022.03.006 kostenfrei https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 kostenfrei http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf kostenfrei https://doaj.org/toc/1671-2870 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA AR 21 2022 03 326-330 |
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Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity |
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Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity |
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DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao |
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Zhenduanxue lilun yu shijian |
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Zhenduanxue lilun yu shijian |
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2022 |
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DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao |
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Elektronische Aufsätze |
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DU Yanran, JIAO Jing, REN Yunyun, ZHOU Jianqiao |
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10.16150/j.1671-2870.2022.03.006 |
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application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity |
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Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity |
| abstract |
Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |
| abstractGer |
Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |
| abstract_unstemmed |
Objective: To establish a model with ultrasound-based radiomics technology for evaluating fetal lung maturity and verify its efficacy in predicting risk of newborn respiratory disease. Methods: A total of 295 singleton pregnancies were enrolled, and fetal lung ultrasound images (four-chamber view) of each fetal were obtained within 72 hours before delivery. The 295 images were divided into 2 groups according to gestational age (GA) of the day fetal lung ultrasound images collected on examination day: Group 1(GA <36 weeks) and Group 2(GA 36-37 weeks). Images of Group 1 （66） and Group 2 （229） were further grouped into training set（40, 26） and validation set（95, 134）,respectively. High throughput radiomics features were extracted from each fetal lung ultrasound image by fetal lung texture analysis based on ultrasound-based radiomics technology. Based on outcomes of fetus, diagnostic models by Group 1 or 2 for predicting risk of newborn respiratory disease were established combined with pregnancy complications using training set of Group 1 or Group 2, respectively, and the predictive efficacy were verified in correspondingly validation set. Results: The diagnostic performance of models by Group1 and 2 were as follows: sensitivity were 83.3%(Group 1) and 75.0%, respectively; specificity were 84.6% and 78.3%,respectively; accuracy were 80.8% and 77.2%, respectively. Conclusions: The fetal lung maturity evaluation model based on ultrasonic-based radiomics technology is a new method for noninvasive evaluation of fetal lung maturity, Which have certain efficacy in predicting newborn respiratory disease. |
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Application of ultrasound-based radiomics technology in the evaluation of fetal lung maturity |
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https://doi.org/10.16150/j.1671-2870.2022.03.006 https://doaj.org/article/47e8c1c669e041608a34efb0522c90a4 http://www.qk.sjtu.edu.cn/jdcp/fileup/1671-2870/PDF/1660723284856-1991327071.pdf https://doaj.org/toc/1671-2870 |
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2024-07-03T15:48:15.364Z |
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