Literature DB >> 12536093

Comparison of standard reading and computer aided detection (CAD) on a national proficiency test of screening mammography.

Stefano Ciatto1, Marco Rosselli Del Turco, Gabriella Risso, Sandra Catarzi, Rita Bonardi, Valeria Viterbo, Pierangela Gnutti, Barbara Guglielmoni, Lelio Pinelli, Anna Pandiscia, Francesco Navarra, Adele Lauria, Rosa Palmiero, Pietro Luigi Indovina.   

Abstract

OBJECTIVE: To evaluate the role of computer aided detection (CAD) in improving the interpretation of screening mammograms
MATERIAL AND METHODS: Ten radiologists underwent a proficiency test of screening mammography first by conventional reading and then with the help of CAD. Radiologists were blinded to test results for the whole study duration. Results of conventional and CAD reading were compared in terms of sensitivity and recall rate. Double reading was simulated combining conventional readings of four expert radiologists and compared with CAD reading.
RESULTS: Considering all ten readings, cancer was identified in 146 or 153 of 170 cases (85.8 vs. 90.0%; chi(2)=0.99, df=1, P=0.31) and recalls were 106 or 152 of 1330 cases (7.9 vs. 11.4%; chi(2)=8.69, df=1, P=0.003) at conventional or CAD reading, respectively. CAD reading was essentially the same (sensitivity 97.0 vs. 96.0%; chi(2)=7.1, df=1, P=0.93; recall rate 10.7 vs. 10.6%; chi(2)=1.5, df=1, P=0.96) as compared with simulated conventional double reading.
CONCLUSION: CAD reading seems to improve the sensitivity of conventional reading while reducing specificity, both effects being of limited size. CAD reading had almost the same performance of simulated conventional double reading, suggesting a possible use of CAD which needs to be confirmed by further studies inclusive of cost-effective analysis.

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Year:  2003        PMID: 12536093     DOI: 10.1016/s0720-048x(02)00011-6

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  14 in total

1.  Consensus versus disagreement in imaging research: a case study using the LIDC database.

Authors:  Dmitriy Zinovev; Yujie Duo; Daniela S Raicu; Jacob Furst; Samuel G Armato
Journal:  J Digit Imaging       Date:  2012-06       Impact factor: 4.056

2.  Classification of breast masses via nonlinear transformation of features based on a kernel matrix.

Authors:  Tingting Mu; Asoke K Nandi; Rangaraj M Rangayyan
Journal:  Med Biol Eng Comput       Date:  2007-07-21       Impact factor: 2.602

3.  Shape-based Automatic Detection of Pectoral Muscle Boundary in Mammograms.

Authors:  Chunxiao Chen; Gao Liu; Jing Wang; Gail Sudlow
Journal:  J Med Biol Eng       Date:  2015-06-10       Impact factor: 1.553

4.  "CADEAT": considerations on the use of CAD (computer-aided diagnosis) in mammography.

Authors:  R Chersevani; S Ciatto; C Del Favero; A Frigerio; L Giordano; G Giuseppetti; C Naldoni; P Panizza; M Petrella; G Saguatti
Journal:  Radiol Med       Date:  2010-01-15       Impact factor: 3.469

Review 5.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

6.  Computer-assisted diagnosis (CAD) in mammography: comparison of diagnostic accuracy of a new algorithm (Cyclopus, Medicad) with two commercial systems.

Authors:  S Ciatto; D Cascio; F Fauci; R Magro; G Raso; R Ienzi; F Martinelli; M Vasile Simone
Journal:  Radiol Med       Date:  2009-05-14       Impact factor: 3.469

7.  External Evaluation of 3 Commercial Artificial Intelligence Algorithms for Independent Assessment of Screening Mammograms.

Authors:  Mattie Salim; Erik Wåhlin; Karin Dembrower; Edward Azavedo; Theodoros Foukakis; Yue Liu; Kevin Smith; Martin Eklund; Fredrik Strand
Journal:  JAMA Oncol       Date:  2020-10-01       Impact factor: 31.777

8.  Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection.

Authors:  Constance D Lehman; Robert D Wellman; Diana S M Buist; Karla Kerlikowske; Anna N A Tosteson; Diana L Miglioretti
Journal:  JAMA Intern Med       Date:  2015-11       Impact factor: 21.873

Review 9.  Is single reading with computer-aided detection (CAD) as good as double reading in mammography screening? A systematic review.

Authors:  Edward Azavedo; Sophia Zackrisson; Ingegerd Mejàre; Marianne Heibert Arnlind
Journal:  BMC Med Imaging       Date:  2012-07-24       Impact factor: 1.930

10.  CAD May Not be Necessary for Microcalcifications in the Digital era, CAD May Benefit Radiologists for Masses.

Authors:  Stamatia V Destounis; Andrea L Arieno; Renee C Morgan
Journal:  J Clin Imaging Sci       Date:  2012-07-28
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