Literature DB >> 19444587

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

S Ciatto1, D Cascio, F Fauci, R Magro, G Raso, R Ienzi, F Martinelli, M Vasile Simone.   

Abstract

PURPOSE: The study compares the diagnostic accuracy (correct identification of cancer) of a new computer-assisted diagnosis (CAD) system (Cyclopus) with two other commercial systems (R2 and CADx).
MATERIALS AND METHODS: Cyclopus was tested on a set of 120 mammograms on which the two compared commercial systems had been previously tested. The set consisted of mammograms reported as negative, preceding 31 interval cancers reviewed as screening error or minimal sign, and of 89 verified negative controls randomly selected from the same screening database.
RESULTS: Cyclopus sensitivity was 74.1% (R2=54.8%; CADx=41.9%) and was higher for interval cancers reviewed as screening error (90.9%; R2=54.5%; CADx=81.8%) compared with those reviewed as minimal sign (65.0%; R2=55.0%; CADx=20.0%). Specificity was 15.7% (R2=29.2%; CADx=17.9%). Overall accuracy was 30.8% (R2=35.8%; CADx=24.1%). The positive predictive value of a case with CAD marks [regions of interest (ROI)] was 23.4% (23/98; R2=16.0%; CADx=15.1%). Average ROI number per view among negative controls was 1.13 (R2=0.93; CADx=0.99). Cyclopus was more sensitive for masses compared with isolated microcalcifications (208 vs 62 ROI; R2=90 vs 213; CADx=192 vs 130).
CONCLUSIONS: Compared with two other commercial systems, Cyclopus was more sensitive (R2 p=0.14; CADx p=0.02) and less specific (R2 p=0.02; CADx p=0.64).

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Mesh:

Year:  2009        PMID: 19444587     DOI: 10.1007/s11547-009-0396-4

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  20 in total

Review 1.  Does the accuracy of single reading with CAD (computer-aided detection) compare with that of double reading?: A review of the literature.

Authors:  R L Bennett; R G Blanks; S M Moss
Journal:  Clin Radiol       Date:  2006-12       Impact factor: 2.350

2.  Computer-aided detection with screening mammography in a university hospital setting.

Authors:  Robyn L Birdwell; Parul Bandodkar; Debra M Ikeda
Journal:  Radiology       Date:  2005-08       Impact factor: 11.105

3.  Impact of computer-aided detection in a regional screening mammography program.

Authors:  Tommy E Cupples; Joan E Cunningham; James C Reynolds
Journal:  AJR Am J Roentgenol       Date:  2005-10       Impact factor: 3.959

4.  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

5.  Population screening and intensity of screening are associated with reduced breast cancer mortality: evidence of efficacy of mammography screening in Australia.

Authors:  D Roder; N Houssami; G Farshid; G Gill; C Luke; P Downey; K Beckmann; P Iosifidis; L Grieve; L Williamson
Journal:  Breast Cancer Res Treat       Date:  2007-05-22       Impact factor: 4.872

6.  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

7.  Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial.

Authors:  Mark A Helvie; Lubomir Hadjiiski; Erini Makariou; Heang-Ping Chan; Nicholas Petrick; Berkman Sahiner; Shih-Chung B Lo; Matthew Freedman; Dorit Adler; Janet Bailey; Caroline Blane; Donna Hoff; Karen Hunt; Lynn Joynt; Katherine Klein; Chintana Paramagul; Stephanie K Patterson; Marilyn A Roubidoux
Journal:  Radiology       Date:  2004-02-27       Impact factor: 11.105

Review 8.  Radiological surveillance of interval breast cancers in screening programmes.

Authors:  Nehmat Houssami; Les Irwig; Stefano Ciatto
Journal:  Lancet Oncol       Date:  2006-03       Impact factor: 41.316

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

Authors:  Stefano Ciatto; Beniamino Brancato; Marco Rosselli Del Turco; Gabriella Risso; Sandra Catarzi; Daniela Morrone; Daniela Bricolo; Marco Zappa
Journal:  Radiol Med       Date:  2003 Jul-Aug       Impact factor: 3.469

10.  The detectability of breast cancer by screening mammography.

Authors:  S Ciatto; M Rosselli Del Turco; M Zappa
Journal:  Br J Cancer       Date:  1995-02       Impact factor: 7.640

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  5 in total

1.  "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

2.  Feature Selection Based on Machine Learning in MRIs for Hippocampal Segmentation.

Authors:  Sabina Tangaro; Nicola Amoroso; Massimo Brescia; Stefano Cavuoti; Andrea Chincarini; Rosangela Errico; Paolo Inglese; Giuseppe Longo; Rosalia Maglietta; Andrea Tateo; Giuseppe Riccio; Roberto Bellotti
Journal:  Comput Math Methods Med       Date:  2015-05-18       Impact factor: 2.238

3.  Mammographic images segmentation based on chaotic map clustering algorithm.

Authors:  Marius Iacomi; Donato Cascio; Francesco Fauci; Giuseppe Raso
Journal:  BMC Med Imaging       Date:  2014-03-25       Impact factor: 1.930

4.  Fuzzy technique for microcalcifications clustering in digital mammograms.

Authors:  Letizia Vivona; Donato Cascio; Francesco Fauci; Giuseppe Raso
Journal:  BMC Med Imaging       Date:  2014-06-24       Impact factor: 1.930

5.  Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project.

Authors:  Amel Benammar Elgaaied; Donato Cascio; Salvatore Bruno; Maria Cristina Ciaccio; Marco Cipolla; Alessandro Fauci; Rossella Morgante; Vincenzo Taormina; Yousr Gorgi; Raja Marrakchi Triki; Melika Ben Ahmed; Hechmi Louzir; Sadok Yalaoui; Sfar Imene; Yassine Issaoui; Ahmed Abidi; Myriam Ammar; Walid Bedhiafi; Oussama Ben Fraj; Rym Bouhaha; Khouloud Hamdi; Koudhi Soumaya; Bilel Neili; Gati Asma; Mariano Lucchese; Maria Catanzaro; Vincenza Barbara; Ignazio Brusca; Maria Fregapane; Gaetano Amato; Giuseppe Friscia; Trai Neila; Souayeh Turkia; Haouami Youssra; Raja Rekik; Hayet Bouokez; Maria Vasile Simone; Francesco Fauci; Giuseppe Raso
Journal:  Biomed Res Int       Date:  2016-03-03       Impact factor: 3.411

  5 in total

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