Literature DB >> 21547517

False positive marks on unsuspicious screening mammography with computer-aided detection.

Mary C Mahoney1, Karthikeyan Meganathan.   

Abstract

The contribution of computer-aided detection (CAD) systems as an interpretive aid in screening mammography can be hampered by a high rate of false positive detections. Specificity, false positive rate, and ease of dismissing false positive marks from two CAD systems are retrospectively evaluated. One hundred screening mammographic studies with a BI-RADS assessment code of 1 or 2 and at least 2-year normal mammographic follow-up were retrospectively reviewed using two CAD systems. Breast density, CAD marks, and radiologist's ease of dismissing false positive marks were recorded. Specificities from the two CAD versions considering all marks were 23% and 15% (p value = 0.07); mass marks, 35% and 17% (p value < 0.01); and calcification marks 62% and 75% (p value = 0.01). The two CAD versions did not differ regarding mean and median marks per case for all marks (2.3, 2.0 and 2.3, 2.0, p value = 0.65) or mass marks (1.6, 1.0 and 1.8, 2.0, p value = 0.15), but differed for calcification marks (0.8, 0 and 0.5, 0, p value < 0.01). Slightly higher specificity and fewer marks per case observed in dense breasts did not reach statistical significance. The reviewing radiologist classified most marks from both CAD systems (84% and 88%) as very easy/easy to dismiss. The two CAD versions had small differences in specificity and false positive marks. Differences, although not statistically significant, in specificities and false positive rates between dense and non-dense breasts warrant further research. Most false positive marks are easily dismissed and should not affect clinical performance.

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Year:  2011        PMID: 21547517      PMCID: PMC3180536          DOI: 10.1007/s10278-011-9389-7

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  31 in total

1.  Potential contribution of computer-aided detection to the sensitivity of screening mammography.

Authors:  L J Warren Burhenne; S A Wood; C J D'Orsi; S A Feig; D B Kopans; K F O'Shaughnessy; E A Sickles; L Tabar; C J Vyborny; R A Castellino
Journal:  Radiology       Date:  2000-05       Impact factor: 11.105

2.  Soft-copy mammographic readings with different computer-assisted detection cuing environments: preliminary findings.

Authors:  B Zheng; M A Ganott; C A Britton; C M Hakim; L A Hardesty; T S Chang; H E Rockette; D Gur
Journal:  Radiology       Date:  2001-12       Impact factor: 11.105

3.  Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system.

Authors:  David Gur; Jules H Sumkin; Howard E Rockette; Marie Ganott; Christiane Hakim; Lara Hardesty; William R Poller; Ratan Shah; Luisa Wallace
Journal:  J Natl Cancer Inst       Date:  2004-02-04       Impact factor: 13.506

4.  Re: Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system.

Authors:  Stephen A Feig; Edward A Sickles; W Phil Evans; Michael N Linver
Journal:  J Natl Cancer Inst       Date:  2004-08-18       Impact factor: 13.506

5.  Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center.

Authors:  T W Freer; M J Ulissey
Journal:  Radiology       Date:  2001-09       Impact factor: 11.105

6.  Impact of breast density on computer-aided detection for breast cancer.

Authors:  Rachel F Brem; Jeffrey W Hoffmeister; Jocelyn A Rapelyea; Gilat Zisman; Kevin Mohtashemi; Guarav Jindal; Martin P Disimio; Steven K Rogers
Journal:  AJR Am J Roentgenol       Date:  2005-02       Impact factor: 3.959

7.  Influence of breast lesion size and histologic findings on tumor detection rate of a computer-aided detection system.

Authors:  Ansgar Malich; Dieter Sauner; Christiane Marx; Mirjam Facius; Thomas Boehm; Stefan O Pfleiderer; Marlies Fleck; Werner A Kaiser
Journal:  Radiology       Date:  2003-07-17       Impact factor: 11.105

8.  Comparison of two commercial systems for computer-assisted detection (CAD) as an aid to interpreting screening mammograms.

Authors:  Stefano Ciatto; Daniela Ambrogetti; Rita Bonardi; Beniamino Brancato; Sandra Catarzi; Gabriella Risso; Marco Rosselli Del Turco
Journal:  Radiol Med       Date:  2004 May-Jun       Impact factor: 3.469

9.  Improvement in sensitivity of screening mammography with computer-aided detection: a multiinstitutional trial.

Authors:  Rachel F Brem; Janet Baum; Mary Lechner; Stuart Kaplan; Stuart Souders; L Gill Naul; Jeff Hoffmeister
Journal:  AJR Am J Roentgenol       Date:  2003-09       Impact factor: 3.959

10.  Can computer-aided detection with double reading of screening mammograms help decrease the false-negative rate? Initial experience.

Authors:  Stamatia V Destounis; Patricia DiNitto; Wende Logan-Young; Ermelinda Bonaccio; Margarita L Zuley; Kathleen M Willison
Journal:  Radiology       Date:  2004-06-30       Impact factor: 11.105

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  4 in total

1.  Optimization of Image Quality and Dose in Digital Mammography.

Authors:  Agnes M F Fausto; M C Lopes; M C de Sousa; Tânia A C Furquim; Anderson W Mol; Fermin G Velasco
Journal:  J Digit Imaging       Date:  2017-04       Impact factor: 4.056

2.  Mammographic image denoising and enhancement using the Anscombe transformation, adaptive wiener filtering, and the modulation transfer function.

Authors:  Larissa C S Romualdo; Marcelo A C Vieira; Homero Schiabel; Nelson D A Mascarenhas; Lucas R Borges
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

3.  Impact of computer-aided detection systems on radiologist accuracy with digital mammography.

Authors:  Elodia B Cole; Zheng Zhang; Helga S Marques; R Edward Hendrick; Martin J Yaffe; Etta D Pisano
Journal:  AJR Am J Roentgenol       Date:  2014-10       Impact factor: 3.959

4.  Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study.

Authors:  Jeong Hoon Lee; Ki Hwan Kim; Eun Hye Lee; Jong Seok Ahn; Jung Kyu Ryu; Young Mi Park; Gi Won Shin; Young Joong Kim; Hye Young Choi
Journal:  Korean J Radiol       Date:  2022-04-04       Impact factor: 7.109

  4 in total

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