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Development and face validation of ultrasound-guided renal biopsy virtual trainer

The overall prevalence of chronic kidney disease in the general population is ∼14% with more than 661,000 Americans having a kidney failure. Ultrasound (US)-guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies. This Letter presents KBVTrainer, a vi...

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Autores principales: Enquobahrie, Andinet, Horvath, Sam, Arikatla, Sreekanth, Rosenberg, Avi, Cleary, Kevin, Sharma, Karun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952253/
https://www.ncbi.nlm.nih.gov/pubmed/32038859
http://dx.doi.org/10.1049/htl.2019.0081
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author Enquobahrie, Andinet
Horvath, Sam
Arikatla, Sreekanth
Rosenberg, Avi
Cleary, Kevin
Sharma, Karun
author_facet Enquobahrie, Andinet
Horvath, Sam
Arikatla, Sreekanth
Rosenberg, Avi
Cleary, Kevin
Sharma, Karun
author_sort Enquobahrie, Andinet
collection PubMed
description The overall prevalence of chronic kidney disease in the general population is ∼14% with more than 661,000 Americans having a kidney failure. Ultrasound (US)-guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies. This Letter presents KBVTrainer, a virtual simulator that the authors developed to train clinicians to improve procedural skill competence in US-guided renal biopsy. The simulator was built using low-cost hardware components and open source software libraries. They conducted a face validation study with five experts who were either adult/pediatric nephrologists or interventional/diagnostic radiologists. The trainer was rated very highly (>4.4) for the usefulness of the real US images (highest at 4.8), potential usefulness of the trainer in training for needle visualization, tracking, steadiness and hand-eye coordination, and overall promise of the trainer to be useful for training US-guided needle biopsies. The lowest score of 2.4 was received for the look and feel of the US probe and needle compared to clinical practice. The force feedback received a moderate score of 3.0. The clinical experts provided abundant verbal and written subjective feedback and were highly enthusiastic about using the trainer as a valuable tool for future trainees.
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spelling pubmed-69522532020-02-07 Development and face validation of ultrasound-guided renal biopsy virtual trainer Enquobahrie, Andinet Horvath, Sam Arikatla, Sreekanth Rosenberg, Avi Cleary, Kevin Sharma, Karun Healthc Technol Lett Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions The overall prevalence of chronic kidney disease in the general population is ∼14% with more than 661,000 Americans having a kidney failure. Ultrasound (US)-guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies. This Letter presents KBVTrainer, a virtual simulator that the authors developed to train clinicians to improve procedural skill competence in US-guided renal biopsy. The simulator was built using low-cost hardware components and open source software libraries. They conducted a face validation study with five experts who were either adult/pediatric nephrologists or interventional/diagnostic radiologists. The trainer was rated very highly (>4.4) for the usefulness of the real US images (highest at 4.8), potential usefulness of the trainer in training for needle visualization, tracking, steadiness and hand-eye coordination, and overall promise of the trainer to be useful for training US-guided needle biopsies. The lowest score of 2.4 was received for the look and feel of the US probe and needle compared to clinical practice. The force feedback received a moderate score of 3.0. The clinical experts provided abundant verbal and written subjective feedback and were highly enthusiastic about using the trainer as a valuable tool for future trainees. The Institution of Engineering and Technology 2019-11-26 /pmc/articles/PMC6952253/ /pubmed/32038859 http://dx.doi.org/10.1049/htl.2019.0081 Text en http://creativecommons.org/licenses/by/3.0/ This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
spellingShingle Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions
Enquobahrie, Andinet
Horvath, Sam
Arikatla, Sreekanth
Rosenberg, Avi
Cleary, Kevin
Sharma, Karun
Development and face validation of ultrasound-guided renal biopsy virtual trainer
title Development and face validation of ultrasound-guided renal biopsy virtual trainer
title_full Development and face validation of ultrasound-guided renal biopsy virtual trainer
title_fullStr Development and face validation of ultrasound-guided renal biopsy virtual trainer
title_full_unstemmed Development and face validation of ultrasound-guided renal biopsy virtual trainer
title_short Development and face validation of ultrasound-guided renal biopsy virtual trainer
title_sort development and face validation of ultrasound-guided renal biopsy virtual trainer
topic Special Issue: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952253/
https://www.ncbi.nlm.nih.gov/pubmed/32038859
http://dx.doi.org/10.1049/htl.2019.0081
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