Literature DB >> 28845078

Impact of Different Study Populations on Reader Behavior and Performance Metrics: Initial Results.

Brandon D Gallas1, Etta Pisano2,3, Elodia Cole2, Kyle Myers1.   

Abstract

The FDA recently completed a study on design methodologies surrounding the Validation of Imaging Premarket Evaluation and Regulation called VIPER. VIPER consisted of five large reader sub-studies to compare the impact of different study populations on reader behavior as seen by sensitivity, specificity, and AUC, the area under the ROC curve (receiver operating characteristic curve). The study investigated different prevalence levels and two kinds of sampling of non-cancer patients: a screening population and a challenge population. The VIPER study compared full-field digital mammography (FFDM) to screen-film mammography (SFM) for women with heterogeneously dense or extremely dense breasts. All cases and corresponding images were sampled from Digital Mammographic Imaging Screening Trial (DMIST) archives. There were 20 readers (American Board Certified radiologists) for each sub-study, and instead of every reader reading every case (fully-crossed study), readers and cases were split into groups to reduce reader workload and the total number of observations (split-plot study). For data collection, readers first decided whether or not they would recall a patient. Following that decision, they provided an ROC score for how close or far that patient was from the recall decision threshold. Performance results for FFDM show that as prevalence increases to 50%, there is a moderate increase in sensitivity and decrease in specificity, whereas AUC is mainly flat. Regarding precision, the statistical efficiency (ratio of variances) of sensitivity and specificity relative to AUC are 0.66 at best and decrease with prevalence. Analyses comparing modalities and the study populations (screening vs. challenge) are still ongoing.

Entities:  

Year:  2017        PMID: 28845078      PMCID: PMC5568780          DOI: 10.1117/12.2255977

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  10 in total

1.  Basic principles of ROC analysis.

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Journal:  Semin Nucl Med       Date:  1978-10       Impact factor: 4.446

2.  Prevalence effect in a laboratory environment.

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Journal:  Radiology       Date:  2003-07       Impact factor: 11.105

3.  The prevalence effect in a laboratory environment: Changing the confidence ratings.

Authors:  David Gur; Andriy I Bandos; Carl R Fuhrman; Amy H Klym; Jill L King; Howard E Rockette
Journal:  Acad Radiol       Date:  2007-01       Impact factor: 3.173

4.  American College of Radiology Imaging Network digital mammographic imaging screening trial: objectives and methodology.

Authors:  Etta D Pisano; Constantine A Gatsonis; Martin J Yaffe; R Edward Hendrick; Anna N A Tosteson; Dennis G Fryback; Lawrence W Bassett; Janet K Baum; Emily F Conant; Roberta A Jong; Murray Rebner; Carl J D'Orsi
Journal:  Radiology       Date:  2005-06-16       Impact factor: 11.105

5.  Reader studies for validation of CAD systems.

Authors:  Brandon D Gallas; David G Brown
Journal:  Neural Netw       Date:  2007-12-23

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Authors:  T K Egglin; A R Feinstein
Journal:  JAMA       Date:  1996-12-04       Impact factor: 56.272

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Authors:  W Chen; F W Samuelson
Journal:  Br J Radiol       Date:  2014-06-02       Impact factor: 3.039

8.  Prevalence of abnormalities influences cytologists' error rates in screening for cervical cancer.

Authors:  Karla K Evans; Rosemary H Tambouret; Andrew Evered; David C Wilbur; Jeremy M Wolfe
Journal:  Arch Pathol Lab Med       Date:  2011-12       Impact factor: 5.534

9.  Diagnostic performance of digital versus film mammography for breast-cancer screening.

Authors:  Etta D Pisano; Constantine Gatsonis; Edward Hendrick; Martin Yaffe; Janet K Baum; Suddhasatta Acharyya; Emily F Conant; Laurie L Fajardo; Lawrence Bassett; Carl D'Orsi; Roberta Jong; Murray Rebner
Journal:  N Engl J Med       Date:  2005-09-16       Impact factor: 91.245

10.  Multi-reader ROC studies with split-plot designs: a comparison of statistical methods.

Authors:  Nancy A Obuchowski; Brandon D Gallas; Stephen L Hillis
Journal:  Acad Radiol       Date:  2012-12       Impact factor: 3.173

  10 in total
  2 in total

1.  Impact of prevalence and case distribution in lab-based diagnostic imaging studies.

Authors:  Brandon D Gallas; Weijie Chen; Elodia Cole; Robert Ochs; Nicholas Petrick; Etta D Pisano; Berkman Sahiner; Frank W Samuelson; Kyle J Myers
Journal:  J Med Imaging (Bellingham)       Date:  2019-01-21

2.  Paired split-plot designs of multireader multicase studies.

Authors:  Weijie Chen; Qi Gong; Brandon D Gallas
Journal:  J Med Imaging (Bellingham)       Date:  2018-05-17
  2 in total

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