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Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study
Introduction: Anterior lens capsule vascularity (ALCV) is resorbed in the developing fetus from 27 to 35 weeks gestation. In this pilot study, we evaluated the feasibility and validity of combining smartphone ophthalmoscope videos of ALCV and image analysis for gestational age estimation. Methods: A...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391335/ https://www.ncbi.nlm.nih.gov/pubmed/30842940 http://dx.doi.org/10.3389/fped.2019.00043 |
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author | Patel, Monalisa Mukherjee, Dibyendu Farsiu, Sina Munoz, Breda Blood, Arlin B. Wilson, Christopher G. Griffin, Jennifer B. |
author_facet | Patel, Monalisa Mukherjee, Dibyendu Farsiu, Sina Munoz, Breda Blood, Arlin B. Wilson, Christopher G. Griffin, Jennifer B. |
author_sort | Patel, Monalisa |
collection | PubMed |
description | Introduction: Anterior lens capsule vascularity (ALCV) is resorbed in the developing fetus from 27 to 35 weeks gestation. In this pilot study, we evaluated the feasibility and validity of combining smartphone ophthalmoscope videos of ALCV and image analysis for gestational age estimation. Methods: ALCV videos were captured longitudinally in preterm neonates from delivery using a PanOptic® Ophthalmoscope with an iExaminer® adapter (Welch-Allyn). ALCV video frames were manually selected and quantified using semi-automatic image analysis. A predictive model based on ALCV features was compared to gold-standard ultrasound gestational age estimates. Results: A total of 64 image-capture sessions were carried out in 24 neonates. Ultrasound-estimated gestational age and ALCV-predicted gestational age estimates indicate that the two methods are similar (r = 0.78, p < 0.0001). ALCV estimates of gestational age were within 0.11 ± 1.3 weeks of ultrasound estimates. In the final model, gestational age was predicted within ± 1 week for 54% and within ± 2 weeks for 86% of the measures. Conclusions: This novel application of smartphone ophthalmoscopy and ALCV image analysis may provide a safe, accurate and non-invasive technology to estimate postnatal gestational age, especially in low income countries where gestational age may not be known at birth. |
format | Online Article Text |
id | pubmed-6391335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63913352019-03-06 Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study Patel, Monalisa Mukherjee, Dibyendu Farsiu, Sina Munoz, Breda Blood, Arlin B. Wilson, Christopher G. Griffin, Jennifer B. Front Pediatr Pediatrics Introduction: Anterior lens capsule vascularity (ALCV) is resorbed in the developing fetus from 27 to 35 weeks gestation. In this pilot study, we evaluated the feasibility and validity of combining smartphone ophthalmoscope videos of ALCV and image analysis for gestational age estimation. Methods: ALCV videos were captured longitudinally in preterm neonates from delivery using a PanOptic® Ophthalmoscope with an iExaminer® adapter (Welch-Allyn). ALCV video frames were manually selected and quantified using semi-automatic image analysis. A predictive model based on ALCV features was compared to gold-standard ultrasound gestational age estimates. Results: A total of 64 image-capture sessions were carried out in 24 neonates. Ultrasound-estimated gestational age and ALCV-predicted gestational age estimates indicate that the two methods are similar (r = 0.78, p < 0.0001). ALCV estimates of gestational age were within 0.11 ± 1.3 weeks of ultrasound estimates. In the final model, gestational age was predicted within ± 1 week for 54% and within ± 2 weeks for 86% of the measures. Conclusions: This novel application of smartphone ophthalmoscopy and ALCV image analysis may provide a safe, accurate and non-invasive technology to estimate postnatal gestational age, especially in low income countries where gestational age may not be known at birth. Frontiers Media S.A. 2019-02-20 /pmc/articles/PMC6391335/ /pubmed/30842940 http://dx.doi.org/10.3389/fped.2019.00043 Text en Copyright © 2019 Patel, Mukherjee, Farsiu, Munoz, Blood, Wilson and Griffin. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pediatrics Patel, Monalisa Mukherjee, Dibyendu Farsiu, Sina Munoz, Breda Blood, Arlin B. Wilson, Christopher G. Griffin, Jennifer B. Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title | Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title_full | Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title_fullStr | Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title_full_unstemmed | Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title_short | Estimation of Gestational Age via Image Analysis of Anterior Lens Capsule Vascularity in Preterm Infants: A Pilot Study |
title_sort | estimation of gestational age via image analysis of anterior lens capsule vascularity in preterm infants: a pilot study |
topic | Pediatrics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391335/ https://www.ncbi.nlm.nih.gov/pubmed/30842940 http://dx.doi.org/10.3389/fped.2019.00043 |
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