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Published in: European Radiology 9/2017

01-09-2017 | Breast

A multiparametric automatic method to monitor long-term reproducibility in digital mammography: results from a regional screening programme

Authors: G. Gennaro, A. Ballaminut, G. Contento

Published in: European Radiology | Issue 9/2017

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Abstract

Objectives

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.

Key Points

• 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.
Literature
1.
go back to reference European Commission. Directorate-General for Health and Consumer Protection (2006) European guidelines for quality assurance in breast cancer screening and diagnosis. Office for Official Publications of the European Communities, Luxembourg European Commission. Directorate-General for Health and Consumer Protection (2006) European guidelines for quality assurance in breast cancer screening and diagnosis. Office for Official Publications of the European Communities, Luxembourg
2.
go back to reference McLean ID (2011) Quality assurance programme for digital mammography. International Atomic Energy Agency, Vienna McLean ID (2011) Quality assurance programme for digital mammography. International Atomic Energy Agency, Vienna
4.
go back to reference Bloomquist AK, Yaffe MJ, Pisano ED et al (2006) Quality control for digital mammography in the ACRIN DMIST trial: Part I. Med Phys 33:719–736CrossRefPubMed Bloomquist AK, Yaffe MJ, Pisano ED et al (2006) Quality control for digital mammography in the ACRIN DMIST trial: Part I. Med Phys 33:719–736CrossRefPubMed
5.
go back to reference Yaffe MJ, Bloomquist AK, Mawdsley GE et al (2006) Quality control for digital mammography: Part II. Recommendations from the ACRIN DMIST trial. Med Phys 33:737–752CrossRefPubMed Yaffe MJ, Bloomquist AK, Mawdsley GE et al (2006) Quality control for digital mammography: Part II. Recommendations from the ACRIN DMIST trial. Med Phys 33:737–752CrossRefPubMed
6.
go back to reference Rose A (1948) The sensitivity performance of the human eye on an absolute scale. J Opt Soc Am 38:196–208CrossRefPubMed Rose A (1948) The sensitivity performance of the human eye on an absolute scale. J Opt Soc Am 38:196–208CrossRefPubMed
7.
8.
go back to reference Brooks KW, Trueblood JH, Kearfott KJ, Lawton DT (1997) Automated analysis of the American College of Radiology mammographic accreditation phantom images. Med Phys 24:709–723CrossRefPubMed Brooks KW, Trueblood JH, Kearfott KJ, Lawton DT (1997) Automated analysis of the American College of Radiology mammographic accreditation phantom images. Med Phys 24:709–723CrossRefPubMed
9.
go back to reference Huda W, Sajewicz AM, Ogden KM, Scalzetti EM, Dance DR (2002) How good is the ACR accreditation phantom for assessing image quality in digital mammography? Acad Radiol 9:764–772CrossRefPubMed Huda W, Sajewicz AM, Ogden KM, Scalzetti EM, Dance DR (2002) How good is the ACR accreditation phantom for assessing image quality in digital mammography? Acad Radiol 9:764–772CrossRefPubMed
10.
go back to reference Castellano Smith AD, Castellano Smith IA, Dance DR (1998) Objective assessment of phantom image quality in mammography: a feasibility study. Br J Radiol 71:48–58CrossRefPubMed Castellano Smith AD, Castellano Smith IA, Dance DR (1998) Objective assessment of phantom image quality in mammography: a feasibility study. Br J Radiol 71:48–58CrossRefPubMed
11.
go back to reference Mayo P, Rodenas F, Verdu G, Villaescusa JI, Campayo JM (2004) Automatic evaluation of the image quality of a mammographic phantom. Comput Methods Programs Biomed 73:115–128CrossRefPubMed Mayo P, Rodenas F, Verdu G, Villaescusa JI, Campayo JM (2004) Automatic evaluation of the image quality of a mammographic phantom. Comput Methods Programs Biomed 73:115–128CrossRefPubMed
12.
go back to reference Pascoal A, Lawinski CP, Honey I, Blake P (2005) Evaluation of a software package for automated quality assessment of contrast detail images–comparison with subjective visual assessment. Phys Med Biol 50:5743–5757CrossRefPubMed Pascoal A, Lawinski CP, Honey I, Blake P (2005) Evaluation of a software package for automated quality assessment of contrast detail images–comparison with subjective visual assessment. Phys Med Biol 50:5743–5757CrossRefPubMed
13.
go back to reference de las Heras H, Schofer F, Tiller B, Chevalier M, Zwettler G, Semturs F (2013) A phantom using titanium and Landolt rings for image quality evaluation in mammography. Phys Med Biol 58:L17–30 de las Heras H, Schofer F, Tiller B, Chevalier M, Zwettler G, Semturs F (2013) A phantom using titanium and Landolt rings for image quality evaluation in mammography. Phys Med Biol 58:L17–30
14.
go back to reference Chakraborty DP (1997) Computer analysis of mammography phantom images (CAMPI): an application to the measurement of microcalcification image quality of directly acquired digital images. Med Phys 24:1269–1277CrossRefPubMed Chakraborty DP (1997) Computer analysis of mammography phantom images (CAMPI): an application to the measurement of microcalcification image quality of directly acquired digital images. Med Phys 24:1269–1277CrossRefPubMed
15.
go back to reference Gennaro G, Ferro F, Contento G, Fornasin F, di Maggio C (2007) Automated analysis of phantom images for the evaluation of long-term reproducibility in digital mammography. Phys Med Biol 52:1387–1407CrossRefPubMed Gennaro G, Ferro F, Contento G, Fornasin F, di Maggio C (2007) Automated analysis of phantom images for the evaluation of long-term reproducibility in digital mammography. Phys Med Biol 52:1387–1407CrossRefPubMed
16.
go back to reference Lee Y, Tsai DY, Shinohara N (2010) Computerized quantitative evaluation of mammographic accreditation phantom images. Med Phys 37:6323–6331CrossRefPubMed Lee Y, Tsai DY, Shinohara N (2010) Computerized quantitative evaluation of mammographic accreditation phantom images. Med Phys 37:6323–6331CrossRefPubMed
17.
go back to reference Asahara M, Kodera Y (2012) Computerized scheme for evaluating mammographic phantom images. Med Phys 39:1609–1617CrossRefPubMed Asahara M, Kodera Y (2012) Computerized scheme for evaluating mammographic phantom images. Med Phys 39:1609–1617CrossRefPubMed
18.
go back to reference Gerard K, Grandhaye JP, Marchesi V, Kafrouni H, Husson F, Aletti P (2009) A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC). Med Phys 36:1275–1285CrossRefPubMed Gerard K, Grandhaye JP, Marchesi V, Kafrouni H, Husson F, Aletti P (2009) A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC). Med Phys 36:1275–1285CrossRefPubMed
19.
go back to reference Cheung YY, Jung B, Sohn JH, Ogrinc G (2012) Quality initiatives: statistical control charts: simplifying the analysis of data for quality improvement. Radiographics 32:2113–2126CrossRefPubMed Cheung YY, Jung B, Sohn JH, Ogrinc G (2012) Quality initiatives: statistical control charts: simplifying the analysis of data for quality improvement. Radiographics 32:2113–2126CrossRefPubMed
20.
go back to reference Shewhart WA (1986) Statistical method from the viewpoint of quality control. Dover, New York Shewhart WA (1986) Statistical method from the viewpoint of quality control. Dover, New York
21.
go back to reference Montgomery DC (2005) Introduction to statistical quality control. Wiley, Chichester Montgomery DC (2005) Introduction to statistical quality control. Wiley, Chichester
22.
go back to reference Leeds Test Objects (2014) TOR MAS/TOR MAX user manual. Leeds Test Objects, Leeds Leeds Test Objects (2014) TOR MAS/TOR MAX user manual. Leeds Test Objects, Leeds
23.
go back to reference Droege RT, Morin RL (1982) A practical method to measure the MTF of CT scanners. Med Phys 9:758–760CrossRefPubMed Droege RT, Morin RL (1982) A practical method to measure the MTF of CT scanners. Med Phys 9:758–760CrossRefPubMed
24.
go back to reference Droege RT (1983) A practical method to routinely monitor resolution in digital images. Med Phys 10:337–343CrossRefPubMed Droege RT (1983) A practical method to routinely monitor resolution in digital images. Med Phys 10:337–343CrossRefPubMed
25.
26.
go back to reference Duncan AJ (1986) Quality control and industrial statistics, 5th edn. Irwin, Homewood Duncan AJ (1986) Quality control and industrial statistics, 5th edn. Irwin, Homewood
27.
go back to reference Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52:591–611CrossRef Shapiro SS, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52:591–611CrossRef
28.
go back to reference Pisano ED, Gatsonis C, Hendrick E et al (2005) Diagnostic performance of digital versus film mammography for breast-cancer screening. NEJM 353:1773–1783CrossRefPubMed Pisano ED, Gatsonis C, Hendrick E et al (2005) Diagnostic performance of digital versus film mammography for breast-cancer screening. NEJM 353:1773–1783CrossRefPubMed
29.
go back to reference Hendrick RE, Bassett L, Botsco MA et al (1999) Mammography quality control manual. American College of Radiology, Reston Hendrick RE, Bassett L, Botsco MA et al (1999) Mammography quality control manual. American College of Radiology, Reston
30.
go back to reference Pedersen K, Landmark ID (2009) Trial of a proposed protocol for constancy control of digital mammography systems. Med Phys 36:5537–5546CrossRefPubMed Pedersen K, Landmark ID (2009) Trial of a proposed protocol for constancy control of digital mammography systems. Med Phys 36:5537–5546CrossRefPubMed
31.
go back to reference Looney P, Halling-Brown MD, Oduko JM, Young KC (2015) A pilot study on the development of remote quality control of digital mammography systems in the NHS breast screening programme. J Digit Imaging 28:586–593CrossRefPubMedPubMedCentral Looney P, Halling-Brown MD, Oduko JM, Young KC (2015) A pilot study on the development of remote quality control of digital mammography systems in the NHS breast screening programme. J Digit Imaging 28:586–593CrossRefPubMedPubMedCentral
Metadata
Title
A multiparametric automatic method to monitor long-term reproducibility in digital mammography: results from a regional screening programme
Authors
G. Gennaro
A. Ballaminut
G. Contento
Publication date
01-09-2017
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 9/2017
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-017-4735-x

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