When radiologists perform best: the learning curve in screening mammogram interpretation

Radiology. 2009 Dec;253(3):632-40. doi: 10.1148/radiol.2533090070. Epub 2009 Sep 29.

Abstract

Purpose: To examine changes in screening mammogram interpretation as radiologists with and radiologists without fellowship training in breast imaging gain clinical experience.

Materials and methods: In an institutional review board-approved HIPAA-compliant study, the performance of 231 radiologists who interpreted screen-film screening mammograms from 1996 to 2005 at 280 facilities that contribute data to the Breast Cancer Surveillance Consortium was examined. Radiologists' demographic data and clinical experience levels were collected by means of a mailed survey. Mammograms were grouped on the basis of how many years the interpreting radiologist had been practicing mammography, and the influence of increasing experience on performance was examined separately for radiologists with and those without fellowship training in breast imaging, taking into account case-mix and radiologist-level differences.

Results: A total of 1 599 610 mammograms were interpreted during the study period. Performance for radiologists without fellowship training improved most during their 1st 3 years of clinical practice, when the odds of a false-positive reading dropped 11%-15% per year (P < .015) with no associated decrease in sensitivity (P > .89). The number of women recalled per breast cancer detected decreased from 33 for radiologists in their 1st year of practice to 24 for radiologists with 3 years of experience to 19 for radiologists with 20 years of experience. Radiologists with fellowship training in breast imaging experienced no learning curve and reached desirable goals during their 1st year of practice.

Conclusion: Radiologists' interpretations of screening mammograms improve during their first few years of practice and continue to improve throughout much of their careers. Additional residency training and targeted continuing medical education may help reduce the number of work-ups of benign lesions while maintaining high cancer detection rates.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / diagnostic imaging*
  • Clinical Competence*
  • Diagnosis, Differential
  • Education, Medical, Graduate*
  • Fellowships and Scholarships*
  • Female
  • Humans
  • Logistic Models
  • Mammography*
  • Predictive Value of Tests
  • Radiology / education*
  • Registries
  • Sensitivity and Specificity