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Subjective assessment of ovarian masses using pattern recognition: the impact of experience on diagnostic performance and interobserver variability

  • General Gynecology
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Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Purpose

To compare diagnostic performance and interobserver variability in a group of 36 examiners, with four different levels of experience.

Methods

Nine junior trainees, eight level I senior trainees, 11 level II senior gynecologists, and eight level III expert sonologists classified 105 ultrasound images of adnexal masses into three subgroups of ovarian lesions (malignancies, functional cysts, and dermoid cysts).

Results

The level III sonologists obtained the best diagnostic results together with the lowest interobserver variability (κ = 0.70, SD = 0.04). They achieved significantly better results in comparison with the junior trainees and also the senior trainees (κ = 0.51, SD = 0.12, p < 0.001; and κ = 0.51, SD = 0.09, p < 0.001). Differences between level III sonologists and the group of level II observers did not reach statistical significance (κ = 0.65, SD = 0.09, p = 0.70). There were no significant differences between senior and junior trainees (p = 1.0) and both groups achieved a significantly poorer diagnostic performance in comparison with the level II observers (p < 0.01 and p < 0.01). For all observers, the largest differences were seen for classifying malignancies, the best results for classifying functional cysts, and the poorest for evaluating dermoid cysts.

Conclusions

Diagnostic performance of pattern recognition significantly improves with an increasing level of experience, emphasizing the importance of standardized ultrasound training programs with supervision by experts.

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Conflict of interest

The authors declare that there are not any financial and personal relationships with other people or organisations that could inappropriately influence their work.

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Erlangen University Hospital, Universitätsstrasse 21–23, 91054, Erlangen, Germany

    Florian Faschingbauer, Lothar Häberle, Tamme W. Goecke, Matthias W. Beckmann, Stefan Renner & Andreas Müller

  2. Fraunhofer Institute for Integrated Circuits (IIS), Erlangen, Germany

    Michaela Benz, Thomas Wittenberg & Christian Münzenmayer

Authors
  1. Florian Faschingbauer
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  2. Michaela Benz
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  3. Lothar Häberle
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  4. Tamme W. Goecke
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  5. Matthias W. Beckmann
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  6. Stefan Renner
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  7. Andreas Müller
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  8. Thomas Wittenberg
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  9. Christian Münzenmayer
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Correspondence to Florian Faschingbauer.

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Faschingbauer, F., Benz, M., Häberle, L. et al. Subjective assessment of ovarian masses using pattern recognition: the impact of experience on diagnostic performance and interobserver variability. Arch Gynecol Obstet 285, 1663–1669 (2012). https://doi.org/10.1007/s00404-012-2229-2

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  • DOI: https://doi.org/10.1007/s00404-012-2229-2

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