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Enhancing Radiologist Reading Performance by Ordering Screening Mammograms Based on Characteristics That Promote
Jessie J J Gommers1, Sarah D Verboom1, Katya M Duvivier1
1From the Departments of Medical Imaging (J.J.J.G., S.D.V., I.S.) and IQ Health (M.J.M.B.), Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands (K.M.D.); Department of Radiology and Nuclear Medicine, Haga Teaching Hospital, Den Haag, the Netherlands (J.K.v.R.); Department of Radiology, Gelre Hospitals, Apeldoorn, the Netherlands (A.F.v.R.); Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands (J.B.H.); Department of Radiology, Diakonessenhuis, Utrecht, the Netherlands (D.B.N.); Department of Radiology, Canisius Wilhelmina Hospital, Nijmegen, the Netherlands (L.E.M.D.); Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, Calif (C.K.A.); Department of Psychology, University of Nevada, Reno, Nev (M.A.W.); Dutch Expert Centre for Screening, Nijmegen, the Netherlands (M.J.M.B., I.S.); and Technical Medicine Center, University of Twente, Enschede, the Netherlands (I.S.).
Ordering mammograms by increasing volumetric breast density (VBD) improves radiologist screening performance and reduces reading time. This method enhances detection of abnormalities, unlike grouping by self-supervised learning (SSL).
Area of Science:
- Radiology and Medical Imaging
- Artificial Intelligence in Healthcare
- Human Visual Perception
Background:
- Mammographic background characteristics may influence visual adaptation in radiologists, potentially improving abnormality detection.
- The specific characteristic driving this visual adaptation, such as breast density, remains unclear.
Purpose of the Study:
- To determine if screening mammography performance is enhanced when examinations are batched based on characteristics that may promote visual adaptation.
- Investigate the impact of ordering mammograms by volumetric breast density (VBD) and self-supervised learning (SSL) groupings on radiologist performance.
Main Methods:
- Retrospective multireader multicase study using mammograms from 2016-2019.
- 13 radiologists interpreted examinations in random, increasing VBD, and SSL-ordered batches.
- Eye-tracking recorded radiologist eye movements; performance metrics (AUC, sensitivity, specificity) and reading times were analyzed.
Main Results:
- Increasing VBD order significantly improved the area under the receiver operating characteristic curve (AUC) compared to random order (0.93 vs 0.92).
- VBD ordering reduced reading time (24.3 vs 27.9 seconds) and fixation time in malignant regions (3.7 vs 4.6 seconds).
- Self-supervised learning (SSL) ordering showed no significant improvement in AUC, sensitivity, or specificity compared to random order.
Conclusions:
- Ordering screening mammography examinations by increasing volumetric breast density (VBD) enhances radiologist screening performance.
- This VBD-based ordering strategy also reduces reading time and visual fixation duration, suggesting improved efficiency and effectiveness.
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