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

Elgendy, Essam; El Gelany, Saad Abd Elnaby; Hassan, Moamen Mohamed; Abd Elwahab, Abd Elrahman Hegazy; Mahmoud, Amr Ahmed

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

Document Type : Original Article

Authors

¹ obstetrics and gynecology department, faculty of medicine , minia university , minia city ,egypt

² Gynecology, Faculty of Medicine, Minia University, Minia, Egypt

³ obs &amp; Gyn, faculty of medicine, Minia University

⁴ obstetrics and gynecology department ,faculty of medicine, minia university

⁵ Obstetrics and Gynaecology Faculty of Medicine - Minia University

10.21608/mjmr.2024.265055.1680

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 .

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