Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study
Elgendy, E., El Gelany, S., Hassan, M., Abd Elwahab, A., Mahmoud, A. (2024). Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study. EKB Journal Management System, (), -. doi: 10.21608/mjmr.2024.265055.1680
Essam Elgendy; Saad Abd Elnaby El Gelany; Moamen Mohamed Hassan; Abd Elrahman Hegazy Abd Elwahab; Amr Ahmed Mahmoud. "Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study". EKB Journal Management System, , , 2024, -. doi: 10.21608/mjmr.2024.265055.1680
Elgendy, E., El Gelany, S., Hassan, M., Abd Elwahab, A., Mahmoud, A. (2024). 'Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study', EKB Journal Management System, (), pp. -. doi: 10.21608/mjmr.2024.265055.1680
Elgendy, E., El Gelany, S., Hassan, M., Abd Elwahab, A., Mahmoud, A. Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study. EKB Journal Management System, 2024; (): -. doi: 10.21608/mjmr.2024.265055.1680

Prediction of neonatal respiratory distress syndrome by Quantitative ultrasound texture analysis of fetal lung Observational cross section study

Minia Journal of Medical Research
Articles in Press, Accepted Manuscript, Available Online from 24 March 2024  XML
Document Type: Original Article
DOI: 10.21608/mjmr.2024.265055.1680
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Authors
Essam Elgendy1; Saad Abd Elnaby El Gelany2; Moamen Mohamed Hassan3; Abd Elrahman Hegazy Abd Elwahab4; Amr Ahmed Mahmoud email 5
1obstetrics and gynecology department, faculty of medicine , minia university , minia city ,egypt
2Gynecology, Faculty of Medicine, Minia University, Minia, Egypt
3obs & Gyn, faculty of medicine, Minia University
4obstetrics and gynecology department ,faculty of medicine, minia university
5Obstetrics and Gynaecology Faculty of Medicine - Minia University
Abstract
Aim and objectives; to predict respiratory distress syndrome using a noninvasive method called quantitative ultrasonography study of fetal lung texture.

Subjects and methods; a cohort of 304 cases and was conducted in the feto maternity unit of Minia Maternity and Children University Hospital over 3 years. fetal lung images were used to develop a computerized

method based on texture analysis and machine learning algorithms, trained to predict neonatal respiratory morbidity risk on fetal lung ultrasound images.

Result; RI in Control group ranged from 0.58 to 1.04 with mean ± SD = 0.82 ± 0.1 while in RD group the RI ranged from 0.53 to 1.06 with mean ± SD = 0.77 ± 0.13 with statistical significant difference (p= 0.002 ) between the two groups.

Regarding texture lung analysis using computerized programs there was no significant difference between the two groups .

Conclusion: The research showed a significant and meaningful difference between the groups regarding Doppler indices

There was no significant difference regarding texture lung analysis .
Keywords
Lung; Pulmonary; Artery
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