Literature DB >> 30732923

Qualitative ultrasound training: defining the learning curve.

P J Mullaney1.   

Abstract

AIM: To assess the developing competence of two trainees learning groin and shoulder ultrasound when compared to an expert practitioner.
MATERIALS AND METHODS: Specific pro formas were used to record ultrasound trainee performance in each scan region and their diagnosis was compared to the opinion of the expert. The data derived were reviewed using kappa analysis and training end points were defined as a minimum 80% trainee agreement with the expert. Retrospectively, cumulative sum analysis was applied to the data to assess case-by-case performance.
RESULTS: For groin hernias, reporting an average of 70 examinations was required to become competent and inguinal hernias required higher numbers of examinations than femoral hernias. For shoulders, an average of 80 examinations was required and the supraspinatus and infraspinatus tendons proved the most challenging structures.
CONCLUSIONS: Kappa analysis demonstrated a differential in the learning curves for individual structures within each examination region. Sequential kappa scores are consistent with a sigmoid learning curve. The numbers required to achieve satisfactory agreement are suggested as required minima for ultrasound training curricula. Cumulative sum analysis provided a sensitive indicator of trainee performance, quickly highlighting individual learning difficulties when they arose. Its prospective use can ensure extra training support is instigated quickly and appropriately. Crown
Copyright © 2019. Published by Elsevier Ltd. All rights reserved.

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Year:  2019        PMID: 30732923     DOI: 10.1016/j.crad.2018.12.018

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  3 in total

1.  Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts.

Authors:  Naoshi Nishida; Makoto Yamakawa; Tsuyoshi Shiina; Yoshito Mekada; Mutsumi Nishida; Naoya Sakamoto; Takashi Nishimura; Hiroko Iijima; Toshiko Hirai; Ken Takahashi; Masaya Sato; Ryosuke Tateishi; Masahiro Ogawa; Hideaki Mori; Masayuki Kitano; Hidenori Toyoda; Chikara Ogawa; Masatoshi Kudo
Journal:  J Gastroenterol       Date:  2022-02-27       Impact factor: 7.527

2.  Adaptation of an anatomy graduate course in ultrasound imaging from in-person to live, remote instruction during the Covid-19 pandemic.

Authors:  Robert M DePhilip; Melissa M Quinn
Journal:  Anat Sci Educ       Date:  2022-04-05       Impact factor: 6.652

3.  Learning curves in radiological reporting of whole-body MRI in plasma cell disease: a retrospective study.

Authors:  Davide Negroni; Alessia Cassarà; Alessandra Trisoglio; Eleonora Soligo; Sara Berardo; Alessandro Carriero; Alessandro Stecco
Journal:  Radiol Med       Date:  2021-07-26       Impact factor: 3.469

  3 in total

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