Literature DB >> 19000873

Agreement of the order of overall performance levels under different reading paradigms.

David Gur1, Andriy I Bandos, Amy H Klym, Cathy S Cohen, Christiane M Hakim, Lara A Hardesty, Marie A Ganott, Ronald L Perrin, William R Poller, Ratan Shah, Jules H Sumkin, Luisa P Wallace, Howard E Rockette.   

Abstract

RATIONALE AND
OBJECTIVES: To investigate consistency of the orders of performance levels when interpreting mammograms under three different reading paradigms.
MATERIALS AND METHODS: We performed a retrospective observer study in which nine experienced radiologists rated an enriched set of mammography examinations that they personally had read in the clinic ("individualized") mixed with a set that none of them had read in the clinic ("common set"). Examinations were interpreted under three different reading paradigms: binary using screening Breast Imaging Reporting and Data System (BI-RADS), receiver-operating characteristic (ROC), and free-response ROC (FROC). The performance in discriminating between cancer and noncancer findings under each of the paradigms was summarized using Youden's index/2+0.5 (Binary), nonparameteric area under the ROC curve (AUC), and an overall FROC index (JAFROC-2). Pearson correlation coefficients were then computed to assess consistency in the ordering of observers' performance levels. Statistical significance of the computed correlation coefficients was assessed using bootstrap confidence intervals obtained by resampling sets of examination-specific observations.
RESULTS: All but one of the computed pair-wise correlation coefficients were larger than 0.66 and were significantly different from zero. The correlation between the overall performance measures under the Binary and ROC paradigms was the lowest (0.43) and was not significantly different from zero (95% confidence interval -0.078 to 0.733).
CONCLUSION: The use of different evaluation paradigms in the laboratory tends to lead to consistent ordering of the overall performance levels of observers. However, one should recognize that conceptually similar performance indexes resulting from different paradigms often measure different performance characteristics and thus disagreements are not only possible but frequently quite natural.

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Mesh:

Year:  2008        PMID: 19000873      PMCID: PMC2601626          DOI: 10.1016/j.acra.2008.07.011

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  33 in total

1.  Continuous versus categorical data for ROC analysis: some quantitative considerations.

Authors:  R F Wagner; S V Beiden; C E Metz
Journal:  Acad Radiol       Date:  2001-04       Impact factor: 3.173

2.  Components-of-variance models and multiple-bootstrap experiments: an alternative method for random-effects, receiver operating characteristic analysis.

Authors:  S V Beiden; R F Wagner; G Campbell
Journal:  Acad Radiol       Date:  2000-05       Impact factor: 3.173

3.  Improving the accuracy of mammography: volume and outcome relationships.

Authors:  Laura Esserman; Helen Cowley; Carey Eberle; Alastair Kirkpatrick; Sophia Chang; Kevin Berbaum; Alastair Gale
Journal:  J Natl Cancer Inst       Date:  2002-03-06       Impact factor: 13.506

4.  Observer variation and the performance accuracy gained by averaging ratings of abnormality.

Authors:  R G Swensson; J L King; W F Good; D Gur
Journal:  Med Phys       Date:  2000-08       Impact factor: 4.071

5.  An empirical comparison of discrete ratings and subjective probability ratings.

Authors:  Kevin S Berbaum; Donald D Dorfman; E A Franken; Robert T Caldwell
Journal:  Acad Radiol       Date:  2002-07       Impact factor: 3.173

Review 6.  Assessment of medical imaging and computer-assist systems: lessons from recent experience.

Authors:  Robert F Wagner; Sergey V Beiden; Gregory Campbell; Charles E Metz; William M Sacks
Journal:  Acad Radiol       Date:  2002-11       Impact factor: 3.173

7.  Spatial localization accuracy of radiologists in free-response studies: Inferring perceptual FROC curves from mark-rating data.

Authors:  Dev Chakraborty; Hong-Jun Yoon; Claudia Mello-Thoms
Journal:  Acad Radiol       Date:  2007-01       Impact factor: 3.173

Review 8.  Assessment of medical imaging systems and computer aids: a tutorial review.

Authors:  Robert F Wagner; Charles E Metz; Gregory Campbell
Journal:  Acad Radiol       Date:  2007-06       Impact factor: 3.173

9.  The "laboratory" effect: comparing radiologists' performance and variability during prospective clinical and laboratory mammography interpretations.

Authors:  David Gur; Andriy I Bandos; Cathy S Cohen; Christiane M Hakim; Lara A Hardesty; Marie A Ganott; Ronald L Perrin; William R Poller; Ratan Shah; Jules H Sumkin; Luisa P Wallace; Howard E Rockette
Journal:  Radiology       Date:  2008-08-05       Impact factor: 11.105

10.  Binary and multi-category ratings in a laboratory observer performance study: a comparison.

Authors:  David Gur; Andriy I Bandos; Jill L King; Amy H Klym; Cathy S Cohen; Christiane M Hakim; Lara A Hardesty; Marie A Ganott; Ronald L Perrin; William R Poller; Ratan Shah; Jules H Sumkin; Luisa P Wallace; Howard E Rockette
Journal:  Med Phys       Date:  2008-10       Impact factor: 4.071

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  5 in total

1.  ROCView: prototype software for data collection in jackknife alternative free-response receiver operating characteristic analysis.

Authors:  J Thompson; P Hogg; S Thompson; D Manning; K Szczepura
Journal:  Br J Radiol       Date:  2012-05-09       Impact factor: 3.039

2.  Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: results from independently conducted FROC∕ROC studies in mammography.

Authors:  Federica Zanca; Stephen L Hillis; Filip Claus; Chantal Van Ongeval; Valerie Celis; Veerle Provoost; Hong-Jun Yoon; Hilde Bosmans
Journal:  Med Phys       Date:  2012-10       Impact factor: 4.071

3.  Is an ROC-type response truly always better than a binary response in observer performance studies?

Authors:  David Gur; Andriy I Bandos; Howard E Rockette; Margarita L Zuley; Christiane M Hakim; Denise M Chough; Marie A Ganott; Jules H Sumkin
Journal:  Acad Radiol       Date:  2010-03-16       Impact factor: 3.173

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

Authors:  Diana L Miglioretti; Charlotte C Gard; Patricia A Carney; Tracy L Onega; Diana S M Buist; Edward A Sickles; Karla Kerlikowske; Robert D Rosenberg; Bonnie C Yankaskas; Berta M Geller; Joann G Elmore
Journal:  Radiology       Date:  2009-09-29       Impact factor: 11.105

5.  Imaging technology and practice assessments: what next?

Authors:  David Gur
Journal:  Acad Radiol       Date:  2009-05       Impact factor: 3.173

  5 in total

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