Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease
© 2018 The Authors. Journal of Ultrasound in Medicine published by the American Institute of Ultrasound in Medicine. OBJECTIVE: Fetal intelligent navigation echocardiography (FINE) is a novel method that automatically generates and displays 9 standard fetal echocardiographic views in normal hearts b...
Saved in:
Main Authors: | , , |
---|---|
Format: | Journal |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055170112&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62736 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
id |
th-cmuir.6653943832-62736 |
---|---|
record_format |
dspace |
spelling |
th-cmuir.6653943832-627362018-11-29T07:50:10Z Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease Lami Yeo Suchaya Luewan Roberto Romero Health Professions Medicine © 2018 The Authors. Journal of Ultrasound in Medicine published by the American Institute of Ultrasound in Medicine. OBJECTIVE: Fetal intelligent navigation echocardiography (FINE) is a novel method that automatically generates and displays 9 standard fetal echocardiographic views in normal hearts by applying intelligent navigation technology to spatiotemporal image correlation (STIC) volume data sets. The main objective was to determine the sensitivity and specificity of FINE in the prenatal detection of congenital heart disease (CHD).METHODS: A case-control study was conducted in 50 fetuses with a broad spectrum of CHD (cases) and 100 fetuses with normal hearts (controls) in the second and third trimesters. Using 4-dimensional ultrasound with STIC technology, volume data sets were acquired. After all identifying information was removed, the data sets were randomly distributed to a different investigator for analysis using FINE. The sensitivity and specificity for the prenatal detection of CHD, as well as positive and negative likelihood ratios were determined.RESULTS: The diagnostic performance of FINE for the prenatal detection of CHD was: sensitivity of 98% (49 of 50), specificity of 93% (93 of 100), positive likelihood ratio of 14, and negative likelihood ratio of 0.02. Among cases with confirmed CHD, the diagnosis with use of FINE completely matched the final diagnosis in 74% (37 of 50); minor discrepancies were seen in 12% (6 of 50), and major discrepancies were seen in 14% (7 of 50).CONCLUSIONS: This is the first time the sensitivity and specificity of the FINE method in fetuses with normal hearts and CHD in the second and third trimesters has been reported. Because FINE identifies a broad spectrum of CHD with 98% sensitivity, this method could be used prenatally to screen for and diagnose CHD. 2018-11-29T07:44:37Z 2018-11-29T07:44:37Z 2018-11-01 Journal 15509613 2-s2.0-85055170112 10.1002/jum.14616 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055170112&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62736 |
institution |
Chiang Mai University |
building |
Chiang Mai University Library |
country |
Thailand |
collection |
CMU Intellectual Repository |
topic |
Health Professions Medicine |
spellingShingle |
Health Professions Medicine Lami Yeo Suchaya Luewan Roberto Romero Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
description |
© 2018 The Authors. Journal of Ultrasound in Medicine published by the American Institute of Ultrasound in Medicine. OBJECTIVE: Fetal intelligent navigation echocardiography (FINE) is a novel method that automatically generates and displays 9 standard fetal echocardiographic views in normal hearts by applying intelligent navigation technology to spatiotemporal image correlation (STIC) volume data sets. The main objective was to determine the sensitivity and specificity of FINE in the prenatal detection of congenital heart disease (CHD).METHODS: A case-control study was conducted in 50 fetuses with a broad spectrum of CHD (cases) and 100 fetuses with normal hearts (controls) in the second and third trimesters. Using 4-dimensional ultrasound with STIC technology, volume data sets were acquired. After all identifying information was removed, the data sets were randomly distributed to a different investigator for analysis using FINE. The sensitivity and specificity for the prenatal detection of CHD, as well as positive and negative likelihood ratios were determined.RESULTS: The diagnostic performance of FINE for the prenatal detection of CHD was: sensitivity of 98% (49 of 50), specificity of 93% (93 of 100), positive likelihood ratio of 14, and negative likelihood ratio of 0.02. Among cases with confirmed CHD, the diagnosis with use of FINE completely matched the final diagnosis in 74% (37 of 50); minor discrepancies were seen in 12% (6 of 50), and major discrepancies were seen in 14% (7 of 50).CONCLUSIONS: This is the first time the sensitivity and specificity of the FINE method in fetuses with normal hearts and CHD in the second and third trimesters has been reported. Because FINE identifies a broad spectrum of CHD with 98% sensitivity, this method could be used prenatally to screen for and diagnose CHD. |
format |
Journal |
author |
Lami Yeo Suchaya Luewan Roberto Romero |
author_facet |
Lami Yeo Suchaya Luewan Roberto Romero |
author_sort |
Lami Yeo |
title |
Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
title_short |
Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
title_full |
Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
title_fullStr |
Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
title_full_unstemmed |
Fetal Intelligent Navigation Echocardiography (FINE) Detects 98% of Congenital Heart Disease |
title_sort |
fetal intelligent navigation echocardiography (fine) detects 98% of congenital heart disease |
publishDate |
2018 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055170112&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62736 |
_version_ |
1681425862627426304 |