Rationale and Objectives
Determine whether there are patterns of lesion recall among breast imaging subspecialists
interpreting screening mammography, and if so, whether recall patterns correlate to
morphologies of screen-detected cancers.
Materials and Methods
This Institutional Review Board-approved, retrospective review included all screening
examinations January 3, 2012–October 1, 2018 interpreted by fifteen breast imaging
subspecialists at a large academic medical center and two outpatient imaging centers.
Natural language processing identified radiologist recalls by lesion type (mass, calcifications,
asymmetry, architectural distortion); proportions of callbacks by lesion types were
calculated per radiologist. Hierarchical cluster analysis grouped radiologists based
on recall patterns. Groups were compared to overall practice and each other by proportions
of lesion types recalled, and overall and lesion-specific positive predictive value-1
(PPV1).
Results
Among 161,859 screening mammograms with 13,086 (8.1%) recalls, Hierarchical cluster
analysis grouped 15 radiologists into five groups. There was substantial variation
in proportions of lesions recalled: calcifications 13%–18% (Chi-square 45.69, p < 0.00001); mass 16%–44% (Chi-square 498.42, p < 0.00001); asymmetry 13%–47% (Chi-square 660.93, p < 0.00001) architectural distortion 6%–20% (Chi-square 283.81, p < 0.00001). Radiologist groups differed significantly in overall PPV1 (range 5.6%–8.8%;
Chi-square 17.065, p = 0.0019). PPV1 by lesion type varied among groups: calcifications 9.2%–15.4% (Chi-square
2.56, p = 0.6339); mass 5.6%–8.5% (Chi-square 1.31, p = 0.8597); asymmetry 3.4%–5.9% (Chi-square 2.225, p = 0.6945); architectural distortion 5.6%–10.8% (Chi-square 5.810, p = 0.2138). Proportions of recalled lesions did not consistently correlate to proportions
of screen-detected cancer.
Conclusion
Breast imaging subspecialists have patterns for screening mammography recalls, suggesting
differential weighting of imaging findings for perceived malignant potential. Radiologist
recall patterns are not always predictive of screen-detected cancers nor lesion-specific
PPV1s.
Key Words
Abbreviations:
CDR (cancer detection rate), DBT (digital breast tomosynthesis), FFDM (full field digital mammogram), HCA (hierarchical cluster analysis), NLP (natural language processing), PPV1 (positive predictive value of recalled screening examinations]), US (United States)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: July 05, 2022
Accepted:
June 8,
2022
Received in revised form:
May 22,
2022
Received:
April 21,
2022
Identification
Copyright
© 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
