Literature DB >> 22109307

Impact on breast cancer diagnosis in a multidisciplinary unit after the incorporation of mammography digitalization and computer-aided detection systems.

Cristina Romero1, Celia Varela, Enriqueta Muñoz, Asunción Almenar, Jose María Pinto, Miguel Botella.   

Abstract

OBJECTIVE: The purpose of this article is to evaluate the impact on the diagnosis of breast cancer of implementing full-field digital mammography (FFDM) in a multidisciplinary breast pathology unit and, 1 year later, the addition of a computer-aided detection (CAD) system.
MATERIALS AND METHODS: A total of 13,453 mammograms performed between January and July of the years 2004, 2006, and 2007 were retrospectively reviewed using conventional mammography, digital mammography, and digital mammography plus CAD techniques. Mammograms were classified into two subsets: screening and diagnosis. Variables analyzed included cancer detection rate, rate of in situ carcinoma, tumor size at detection, biopsy rate, and positive predictive value of biopsy.
RESULTS: FFDM increased the cancer detection rate, albeit not statistically significantly. The detection rate of in situ carcinoma increased significantly using FFDM plus CAD compared with conventional technique (36.8% vs 6.7%; p = 0.05 without Bonferroni statistical correction) for the screening dataset. Relative to conventional mammography, tumor size at detection decreased with digital mammography (T1, 61.5% vs 88%; p = 0.018) and with digital mammography plus CAD (T1, 79.7%; p = 0.03 without Bonferroni statistical correction). Biopsy rates in the general population increased significantly using CAD (10.6/1000 for conventional mammography, 14.7/1000 for digital mammography, and 17.9/1000 for digital mammography plus CAD; p = 0.02). The positive predictive value of biopsy decreased slightly, but not significantly, for both subsets.
CONCLUSION: The incorporation of new techniques has improved the performance of the breast unit by increasing the overall detection rates and earlier detection (smaller tumors), both leading to an increase in interventionism.

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Year:  2011        PMID: 22109307     DOI: 10.2214/AJR.09.3408

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  4 in total

1.  Integrating CAD modules in a PACS environment using a wide computing infrastructure.

Authors:  Jorge J Suárez-Cuenca; Amara Tilve; Ricardo López; Gonzalo Ferro; Javier Quiles; Miguel Souto
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-02-10       Impact factor: 2.924

2.  Short-term outcomes of screening mammography using computer-aided detection: a population-based study of medicare enrollees.

Authors:  Joshua J Fenton; Guibo Xing; Joann G Elmore; Heejung Bang; Steven L Chen; Karen K Lindfors; Laura-Mae Baldwin
Journal:  Ann Intern Med       Date:  2013-04-16       Impact factor: 25.391

3.  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

4.  Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review.

Authors:  Baptiste Vasey; Stephan Ursprung; Benjamin Beddoe; Elliott H Taylor; Neale Marlow; Nicole Bilbro; Peter Watkinson; Peter McCulloch
Journal:  JAMA Netw Open       Date:  2021-03-01
  4 in total

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