title: A multiparametric automatic method to monitor long-term reproducibility in digital mammography: results from a regional screening programme.
abstract: OBJECTIVE
  This study aims to illustrate a multiparametric automatic method for monitoring long-term reproducibility of digital mammography systems, and its application on a large scale.
  
  
  METHODS
  Twenty-five digital mammography systems employed within a regional screening programme were controlled weekly using the same type of phantom, whose images were analysed by an automatic software tool. To assess system reproducibility levels, 15 image quality indices (IQIs) were extracted and compared with the corresponding indices previously determined by a baseline procedure. The coefficients of variation (COVs) of the IQIs were used to assess the overall variability.
  
  
  RESULTS
  A total of 2553 phantom images were collected from the 25 digital mammography systems from March 2013 to December 2014. Most of the systems showed excellent image quality reproducibility over the surveillance interval, with mean variability below 5%. Variability of each IQI was 5%, with the exception of one index associated with the smallest phantom objects (0.25 mm), which was below 10%.
  
  
  CONCLUSIONS
  The method applied for reproducibility tests-multi-detail phantoms, cloud automatic software tool to measure multiple image quality indices and statistical process control-was proven to be effective and applicable on a large scale and to any type of digital mammography system.
  
  
  CONCLUSIONS
  • Reproducibility of mammography image quality should be monitored by appropriate quality controls. • Use of automatic software tools allows image quality evaluation by multiple indices. • System reproducibility can be assessed comparing current index value with baseline data. • Overall system reproducibility of modern digital mammography systems is excellent. • The method proposed and applied is cost-effective and easily scalable.
authors.affiliation: Veneto Institute of Oncology (IOV), IRCCS, Padua, Italy. gisella.gennaro@iov.veneto.it.
authors.forename: G
authors.identifier: http://orcid.org/0000-0003-2444-1778
authors.initials: G
authors.lastname: Gennaro
authors.affiliation: CyberQual srl, Gorizia, Italy.
authors.forename: A
authors.initials: A
authors.lastname: Ballaminut
authors.affiliation: CyberQual srl, Gorizia, Italy.
authors.forename: G
authors.initials: G
authors.lastname: Contento
mesh_terms: D005260:Female; D006801:Humans; D008327:Mammography / Q000295:instrumentation / Q000379:methods* / Q000592:standards; D008403:Mass Screening / Q000592:standards; D019047:Phantoms, Imaging; D011785:Quality Assurance, Health Care / Q000379:methods*; D011786:Quality Control; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012984:Software
keywords: Breast cancer; Mammography; Quality control; Reproducibility; Screening