Development and validation of an automated assessment tool of echocardiography skills acquired on a neonatal simulator.

echocardiography skill assessment echocardiography training simulation ultrasound simulation

Journal

Echocardiography (Mount Kisco, N.Y.)
ISSN: 1540-8175
Titre abrégé: Echocardiography
Pays: United States
ID NLM: 8511187

Informations de publication

Date de publication:
02 2021
Historique:
received: 05 08 2020
revised: 04 11 2020
accepted: 28 11 2020
pubmed: 16 12 2020
medline: 9 7 2021
entrez: 15 12 2020
Statut: ppublish

Résumé

Simulators are increasingly used for training in echocardiography. However, there is no objective method to assess the skills acquired. Our objective was to develop and test an automated method to assess echocardiography skills. To automate the image quality evaluation, we expanded our previously developed neonatal echocardiography simulator to enable recording of images of the 26 standard cuts and process the image quality. We then compared the automated and visual methods in scoring image quality of the echocardiograms obtained by 22 trainees. Each echocardiographic image representing a slice of a three-dimensional volume possesses 3 axes (X, Y, and Z) that correspond to the roll, pitch, and yaw angles of the transducer, respectively. Therefore, if the placement and orientation of the transducer are correct, the acquired image represents the appropriate cardiac window with the desired orientation in all 3 axes. The automated system gives a score of 0 if the transducer is not in the appropriate cardiac window. A score of 1, 2, or 3 is given if the image falls within the range of one, two, or three angles, respectively. There was no difference in the image quality score between automated and visual assessment methods (46.0 ± 13.0 vs 45.1 ± 14.4, P = .19). The two methods had excellent correlation (r = .95). The bias and precision were 0.9 and 8.8, respectively. The automated method is comparable to visual method for assessment of image quality. The automated process allows for instantaneous feedback and has the potential to standardize assessment of echocardiography skills of trainees.

Identifiants

pubmed: 33319414
doi: 10.1111/echo.14965
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

217-221

Informations de copyright

© 2020 Wiley Periodicals LLC.

Références

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Auteurs

Shahab Noori (S)

Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Mahmood Ebrahimi (M)

Division of Neonatology, Department of Pediatrics, LAC+USC Medical Center, Keck School of Medicine of USC, Los Angeles, CA, USA.

Huiwen Luo (H)

Division of Neonatology, Department of Pediatrics, LAC+USC Medical Center, Keck School of Medicine of USC, Los Angeles, CA, USA.

Istvan Seri (I)

Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
First Department of Pediatrics, Faculty of Medicine, Semmelweis University, Budapest, Hungary.

Bijan Siassi (B)

Division of Neonatology, Department of Pediatrics, LAC+USC Medical Center, Keck School of Medicine of USC, Los Angeles, CA, USA.

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Classifications MeSH