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Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination

Identifieur interne : 002064 ( Main/Curation ); précédent : 002063; suivant : 002065

Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination

Auteurs : S J Johnson [Royaume-Uni] ; C M Hunt [Royaume-Uni] ; H M Woolnough [Royaume-Uni] ; M. Crawshaw [Royaume-Uni] ; C. Kilkenny [Royaume-Uni] ; D A Gould [Royaume-Uni] ; A. England [Royaume-Uni] ; A. Sinha [Royaume-Uni] ; P F Villard [Royaume-Uni]

Source :

The British Journal of Radiology [ 0007-1285 ] ; 2012.

RBID : PMC:3479890

Abstract

Objectives

The aim of this article was to identify and prospectively investigate simulated ultrasound-guided targeted liver biopsy performance metrics as differentiators between levels of expertise in interventional radiology.

Methods

Task analysis produced detailed procedural step documentation allowing identification of critical procedure steps and performance metrics for use in a virtual reality ultrasound-guided targeted liver biopsy procedure. Consultant (n=14; male=11, female=3) and trainee (n=26; male=19, female=7) scores on the performance metrics were compared. Ethical approval was granted by the Liverpool Research Ethics Committee (UK). Independent t-tests and analysis of variance (ANOVA) investigated differences between groups.

Results

Independent t-tests revealed significant differences between trainees and consultants on three performance metrics: targeting, p=0.018, t=−2.487 (−2.040 to −0.207); probe usage time, p = 0.040, t=2.132 (11.064 to 427.983); mean needle length in beam, p=0.029, t=−2.272 (−0.028 to −0.002). ANOVA reported significant differences across years of experience (0–1, 1–2, 3+ years) on seven performance metrics: no-go area touched, p=0.012; targeting, p=0.025; length of session, p=0.024; probe usage time, p=0.025; total needle distance moved, p=0.038; number of skin contacts, p<0.001; total time in no-go area, p=0.008. More experienced participants consistently received better performance scores on all 19 performance metrics.

Conclusion

It is possible to measure and monitor performance using simulation, with performance metrics providing feedback on skill level and differentiating levels of expertise. However, a transfer of training study is required.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3479890

DOI: 10.1259/bjr/47436030
PubMed: 21304005
PubMed Central: 3479890

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PMC:3479890

Le document en format XML

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<author><name sortKey="Villard, P F" sort="Villard, P F" uniqKey="Villard P" first="P F" last="Villard">P F Villard</name>
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<author><name sortKey="Johnson, S J" sort="Johnson, S J" uniqKey="Johnson S" first="S J" last="Johnson">S J Johnson</name>
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</nlm:aff>
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<wicri:regionArea>Royal Liverpool University Hospital NHS Trust, Liverpool</wicri:regionArea>
<wicri:noRegion>Liverpool</wicri:noRegion>
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</author>
<author><name sortKey="Villard, P F" sort="Villard, P F" uniqKey="Villard P" first="P F" last="Villard">P F Villard</name>
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<series><title level="j">The British Journal of Radiology</title>
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<front><div type="abstract" xml:lang="en"><sec><title>Objectives</title>
<p>The aim of this article was to identify and prospectively investigate simulated ultrasound-guided targeted liver biopsy performance metrics as differentiators between levels of expertise in interventional radiology.</p>
</sec>
<sec><title>Methods</title>
<p>Task analysis produced detailed procedural step documentation allowing identification of critical procedure steps and performance metrics for use in a virtual reality ultrasound-guided targeted liver biopsy procedure. Consultant (<italic>n</italic>
=14; male=11, female=3) and trainee (<italic>n</italic>
=26; male=19, female=7) scores on the performance metrics were compared. Ethical approval was granted by the Liverpool Research Ethics Committee (UK). Independent <italic>t</italic>
-tests and analysis of variance (ANOVA) investigated differences between groups.</p>
</sec>
<sec><title>Results</title>
<p>Independent <italic>t</italic>
-tests revealed significant differences between trainees and consultants on three performance metrics: targeting, <italic>p</italic>
=0.018, <italic>t</italic>
=−2.487 (−2.040 to −0.207); probe usage time, <italic>p =</italic>
 0.040, <italic>t</italic>
=2.132 (11.064 to 427.983); mean needle length in beam, <italic>p</italic>
=0.029, <italic>t</italic>
=−2.272 (−0.028 to −0.002). ANOVA reported significant differences across years of experience (0–1, 1–2, 3+ years) on seven performance metrics: no-go area touched, <italic>p</italic>
=0.012; targeting, <italic>p</italic>
=0.025; length of session, <italic>p</italic>
=0.024; probe usage time, <italic>p</italic>
=0.025; total needle distance moved, <italic>p</italic>
=0.038; number of skin contacts, <italic>p</italic>
<0.001; total time in no-go area, <italic>p</italic>
=0.008. More experienced participants consistently received better performance scores on all 19 performance metrics.</p>
</sec>
<sec><title>Conclusion</title>
<p>It is possible to measure and monitor performance using simulation, with performance metrics providing feedback on skill level and differentiating levels of expertise. However, a transfer of training study is required.</p>
</sec>
</div>
</front>
</TEI>
</record>

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Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination

Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination

Source :

Abstract

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Pour générer des pages wiki