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Visual expertise in detecting and diagnosing skeletal fractures

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Abstract

Objective

Failure to identify fractures is the most common error in accident and emergency departments. Therefore, the current research aimed to understand more about the processes underlying perceptual expertise when interpreting skeletal radiographs.

Materials and methods

Thirty participants, consisting of ten novices, ten intermediates, and ten experts were presented with ten clinical cases of normal and abnormal skeletal radiographs of varying difficulty (obvious or subtle) while wearing eye tracking equipment.

Results

Experts were significantly more accurate, more confident, and faster in their diagnoses than intermediates or novices and this performance advantage was more pronounced for the subtle cases. Experts were also faster to fixate the site of the fracture and spent more relative time fixating the fracture than intermediates or novices and this was again most pronounced for subtle cases. Finally, a multiple linear regression analysis found that time to fixate the fracture was inversely related to diagnostic accuracy and explained 34 % of the variance in this variable.

Conclusions

The results suggest that the performance advantage of expert radiologists is underpinned by superior pattern recognition skills, as evidenced by a quicker time to first fixate the pathology, and less time spent searching the image.

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Notes

  1. We used a percentage ratio to better illustrate that experts spent more time fixating the fracture and less time searching the image. Indeed, the raw data illustrates that in general experts spent 22.76 (SD = 20.84) seconds fixating the radiographs with 5.70 (SD = 4.90) seconds of this spent focusing on the fracture regardless of case difficulty. Novices and intermediates spent a mean of 58.96 (SD = 39.91) seconds and 39.17 (SD = 17.01) seconds fixating the radiograph and 10.18 (SD = 7.08) and 8.68 (SD = 6.01) seconds fixating the fracture, respectively.

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Acknowledgments

The authors declare that they have no conflicts of interest.

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Authors and Affiliations

  1. College of Life and Environmental Sciences, University of Exeter, Richards Building, St Luke’s Campus, Exeter, EX1 2LU, UK

    Greg Wood & Mark R. Wilson

  2. College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4QL, UK

    Karen M. Knapp

  3. Peninsula Radiology Academy, Plymouth, PL6 5WR, UK

    Benjamin Rock, Chris Cousens & Carl Roobottom

Authors
  1. Greg Wood
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  2. Karen M. Knapp
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  3. Benjamin Rock
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  4. Chris Cousens
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  5. Carl Roobottom
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  6. Mark R. Wilson
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Correspondence to Greg Wood.

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Wood, G., Knapp, K.M., Rock, B. et al. Visual expertise in detecting and diagnosing skeletal fractures. Skeletal Radiol 42, 165–172 (2013). https://doi.org/10.1007/s00256-012-1503-5

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  • DOI: https://doi.org/10.1007/s00256-012-1503-5

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