Literature DB >> 26105023

Breast cancer detection rates using four different types of mammography detectors.

Alistair Mackenzie1,2, Lucy M Warren3,4, Matthew G Wallis5, Julie Cooke6, Rosalind M Given-Wilson7, David R Dance3,4, Dev P Chakraborty8, Mark D Halling-Brown9, Padraig T Looney3, Kenneth C Young3,4.   

Abstract

OBJECTIVE: To compare the performance of different types of detectors in breast cancer detection.
METHODS: A mammography image set containing subtle malignant non-calcification lesions, biopsy-proven benign lesions, simulated malignant calcification clusters and normals was acquired using amorphous-selenium (a-Se) detectors. The images were adapted to simulate four types of detectors at the same radiation dose: digital radiography (DR) detectors with a-Se and caesium iodide (CsI) convertors, and computed radiography (CR) detectors with a powder phosphor (PIP) and a needle phosphor (NIP). Seven observers marked suspicious and benign lesions. Analysis was undertaken using jackknife alternative free-response receiver operating characteristics weighted figure of merit (FoM). The cancer detection fraction (CDF) was estimated for a representative image set from screening.
RESULTS: No significant differences in the FoMs between the DR detectors were measured. For calcification clusters and non-calcification lesions, both CR detectors' FoMs were significantly lower than for DR detectors. The calcification cluster's FoM for CR NIP was significantly better than for CR PIP. The estimated CDFs with CR PIP and CR NIP detectors were up to 15% and 22% lower, respectively, than for DR detectors.
CONCLUSION: Cancer detection is affected by detector type, and the use of CR in mammography should be reconsidered. KEY POINTS: The type of mammography detector can affect the cancer detection rates. CR detectors performed worse than DR detectors in mammography. Needle phosphor CR performed better than powder phosphor CR. Calcification clusters detection is more sensitive to detector type than other cancers.

Entities:  

Keywords:  Breast cancer screening; Computed radiography; Digital mammography; Image quality; Observer study

Mesh:

Year:  2015        PMID: 26105023      PMCID: PMC4691226          DOI: 10.1007/s00330-015-3885-y

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  23 in total

1.  Does digital mammography in a decentralized breast cancer screening program lead to screening performance parameters comparable with film-screen mammography?

Authors:  Chantal Van Ongeval; Andre Van Steen; Gretel Vande Putte; Federica Zanca; Hilde Bosmans; Guy Marchal; Erik Van Limbergen
Journal:  Eur Radiol       Date:  2010-05-09       Impact factor: 5.315

2.  Comparison of the clinical performance of three digital mammography systems in a breast cancer screening programme.

Authors:  E Keavey; N Phelan; A M O'Connell; F Flanagan; A O'Doherty; A Larke; A M Connors
Journal:  Br J Radiol       Date:  2011-11-17       Impact factor: 3.039

3.  Screening mammography: test set data can reasonably describe actual clinical reporting.

Authors:  BaoLin P Soh; Warwick Lee; Mark F McEntee; Peter L Kench; Warren M Reed; Rob Heard; Dev P Chakraborty; Patrick C Brennan
Journal:  Radiology       Date:  2013-03-12       Impact factor: 11.105

4.  Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system.

Authors:  Alistair Mackenzie; David R Dance; Adam Workman; Mary Yip; Kevin Wells; Kenneth C Young
Journal:  Med Phys       Date:  2012-05       Impact factor: 4.071

5.  Effect of image quality on calcification detection in digital mammography.

Authors:  Lucy M Warren; Alistair Mackenzie; Julie Cooke; Rosalind M Given-Wilson; Matthew G Wallis; Dev P Chakraborty; David R Dance; Hilde Bosmans; Kenneth C Young
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

6.  Comparison of digital screening mammography and screen-film mammography in the early detection of clinically relevant cancers: a multicenter study.

Authors:  Adriana M J Bluekens; Roland Holland; Nico Karssemeijer; Mireille J M Broeders; Gerard J den Heeten
Journal:  Radiology       Date:  2012-10-02       Impact factor: 11.105

7.  Does image quality matter? Impact of resolution and noise on mammographic task performance.

Authors:  Robert S Saunders; Jay A Baker; David M Delong; Jeff P Johnson; Ehsan Samei
Journal:  Med Phys       Date:  2007-10       Impact factor: 4.071

8.  Randomized trial of screen-film versus full-field digital mammography with soft-copy reading in population-based screening program: follow-up and final results of Oslo II study.

Authors:  Per Skaane; Solveig Hofvind; Arnulf Skjennald
Journal:  Radiology       Date:  2007-09       Impact factor: 11.105

9.  Full-field digital mammography compared to screen film mammography in the prevalent round of a population-based screening programme: the Vestfold County Study.

Authors:  Einar Vigeland; Herman Klaasen; Tor Audun Klingen; Solveig Hofvind; Per Skaane
Journal:  Eur Radiol       Date:  2007-08-07       Impact factor: 5.315

10.  If you don't find it often, you often don't find it: why some cancers are missed in breast cancer screening.

Authors:  Karla K Evans; Robyn L Birdwell; Jeremy M Wolfe
Journal:  PLoS One       Date:  2013-05-30       Impact factor: 3.240

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  5 in total

1.  OPTIMAM Mammography Image Database: A Large-Scale Resource of Mammography Images and Clinical Data.

Authors:  Mark D Halling-Brown; Lucy M Warren; Dominic Ward; Emma Lewis; Alistair Mackenzie; Matthew G Wallis; Louise S Wilkinson; Rosalind M Given-Wilson; Rita McAvinchey; Kenneth C Young
Journal:  Radiol Artif Intell       Date:  2020-11-25

2.  Development of an algorithm to convert mammographic images to appear as if acquired with different technique factors.

Authors:  Alistair Mackenzie; Joana Boita; David R Dance; Kenneth C Young
Journal:  J Med Imaging (Bellingham)       Date:  2022-06-08

3.  The relationship between cancer detection in mammography and image quality measurements.

Authors:  Alistair Mackenzie; Lucy M Warren; Matthew G Wallis; Rosalind M Given-Wilson; Julie Cooke; David R Dance; Dev P Chakraborty; Mark D Halling-Brown; Padraig T Looney; Kenneth C Young
Journal:  Phys Med       Date:  2016-04-06       Impact factor: 2.685

4.  Validation of a mammographic image quality modification algorithm using 3D-printed breast phantoms.

Authors:  Joana Boita; Alistair Mackenzie; Ruben E van Engen; Mireille Broeders; Ioannis Sechopoulos
Journal:  J Med Imaging (Bellingham)       Date:  2021-05-20

5.  How does image quality affect radiologists' perceived ability for image interpretation and lesion detection in digital mammography?

Authors:  Joana Boita; Ruben E van Engen; Alistair Mackenzie; Anders Tingberg; Hilde Bosmans; Anetta Bolejko; Sophia Zackrisson; Matthew G Wallis; Debra M Ikeda; Chantal Van Ongeval; Ruud Pijnappel; Mireille Broeders; Ioannis Sechopoulos
Journal:  Eur Radiol       Date:  2021-01-21       Impact factor: 5.315

  5 in total

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