Literature DB >> 34331118

Virtual clinical trial to compare cancer detection using combinations of 2D mammography, digital breast tomosynthesis and synthetic 2D imaging.

Alistair Mackenzie1, Emma L Thomson2,3, Melissa Mitchell2,3, Premkumar Elangovan2, Chantal van Ongeval4, Lesley Cockmartin5, Lucy M Warren2, Louise S Wilkinson6, Matthew G Wallis7, Rosalind M Given-Wilson8, David R Dance2,3, Kenneth C Young2,3.   

Abstract

OBJECTIVES: This study was designed to compare the detection of subtle lesions (calcification clusters or masses) when using the combination of digital breast tomosynthesis (DBT) and synthetic mammography (SM) with digital mammography (DM) alone or combined with DBT.
METHODS: A set of 166 cases without cancer was acquired on a DBT mammography system. Realistic subtle calcification clusters and masses in the DM images and DBT planes were digitally inserted into 104 of the acquired cases. Three study arms were created: DM alone, DM with DBT and SM with DBT. Five mammographic readers located the centre of any lesion within the images that should be recalled for further investigation and graded their suspiciousness. A JAFROC figure of merit (FoM) and lesion detection fraction (LDF) were calculated for each study arm. The visibility of the lesions in the DBT images was compared with SM and DM images.
RESULTS: For calcification clusters, there were no significant differences (p > 0.075) in FoM or LDF. For masses, the FoM and LDF were significantly improved in the arms using DBT compared to DM alone (p < 0.001). On average, both calcification clusters and masses were more visible on DBT than on DM and SM images.
CONCLUSIONS: This study demonstrated that masses were detected better with DBT than with DM alone and there was no significant difference (p = 0.075) in LDF between DM&DBT and SM&DBT for calcifications clusters. Our results support previous studies that it may be acceptable to not acquire digital mammography alongside tomosynthesis for subtle calcification clusters and ill-defined masses. KEY POINTS: • The detection of masses was significantly better using DBT than with digital mammography alone. • The detection of calcification clusters was not significantly different between digital mammography and synthetic 2D images combined with tomosynthesis. • Our results support previous studies that it may be acceptable to not acquire digital mammography alongside tomosynthesis for subtle calcification clusters and ill-defined masses for the imaging technology used.
© 2021. European Society of Radiology.

Entities:  

Keywords:  Cancer; Mammography; Screening

Mesh:

Year:  2021        PMID: 34331118     DOI: 10.1007/s00330-021-08197-x

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


  22 in total

1.  The simulation of 3D microcalcification clusters in 2D digital mammography and breast tomosynthesis.

Authors:  Eman Shaheen; Chantal Van Ongeval; Federica Zanca; Lesley Cockmartin; Nicholas Marshall; Jurgen Jacobs; Kenneth C Young; David R Dance; Hilde Bosmans
Journal:  Med Phys       Date:  2011-12       Impact factor: 4.071

2.  MEDXVIEWER: PROVIDING A WEB-ENABLED WORKSTATION ENVIRONMENT FOR COLLABORATIVE AND REMOTE MEDICAL IMAGING VIEWING, PERCEPTION STUDIES AND READER TRAINING.

Authors:  P T Looney; K C Young; M D Halling-Brown
Journal:  Radiat Prot Dosimetry       Date:  2015-11-30       Impact factor: 0.972

3.  Simulation and assessment of realistic breast lesions using fractal growth models.

Authors:  A Rashidnasab; P Elangovan; M Yip; O Diaz; D R Dance; K C Young; K Wells
Journal:  Phys Med Biol       Date:  2013-07-29       Impact factor: 3.609

4.  Local breast density assessment using reacquired mammographic images.

Authors:  Eloy García; Oliver Diaz; Robert Martí; Yago Diez; Albert Gubern-Mérida; Melcior Sentís; Joan Martí; Arnau Oliver
Journal:  Eur J Radiol       Date:  2017-05-30       Impact factor: 3.528

5.  Performance of breast cancer screening using digital breast tomosynthesis: results from the prospective population-based Oslo Tomosynthesis Screening Trial.

Authors:  Per Skaane; Sofie Sebuødegård; Andriy I Bandos; David Gur; Bjørn Helge Østerås; Randi Gullien; Solveig Hofvind
Journal:  Breast Cancer Res Treat       Date:  2018-02-10       Impact factor: 4.872

6.  Implementation of Synthesized Two-dimensional Mammography in a Population-based Digital Breast Tomosynthesis Screening Program.

Authors:  Samantha P Zuckerman; Emily F Conant; Brad M Keller; Andrew D A Maidment; Bruno Barufaldi; Susan P Weinstein; Marie Synnestvedt; Elizabeth S McDonald
Journal:  Radiology       Date:  2016-07-28       Impact factor: 11.105

7.  Clinical implementation of synthesized mammography with digital breast tomosynthesis in a routine clinical practice.

Authors:  Phoebe E Freer; Joanna Riegert; Laura Eisenmenger; Dominik Ose; Nicole Winkler; Matthew A Stein; Gregory J Stoddard; Rachel Hess
Journal:  Breast Cancer Res Treat       Date:  2017-08-05       Impact factor: 4.872

8.  Two-view digital breast tomosynthesis screening with synthetically reconstructed projection images: comparison with digital breast tomosynthesis with full-field digital mammographic images.

Authors:  Per Skaane; Andriy I Bandos; Ellen B Eben; Ingvild N Jebsen; Mona Krager; Unni Haakenaasen; Ulrika Ekseth; Mina Izadi; Solveig Hofvind; Randi Gullien
Journal:  Radiology       Date:  2014-01-24       Impact factor: 11.105

Review 9.  Evidence on Synthesized Two-dimensional Mammography Versus Digital Mammography When Using Tomosynthesis (Three-dimensional Mammography) for Population Breast Cancer Screening.

Authors:  Nehmat Houssami
Journal:  Clin Breast Cancer       Date:  2017-09-28       Impact factor: 3.225

10.  Breast cancer screening with tomosynthesis (3D mammography) with acquired or synthetic 2D mammography compared with 2D mammography alone (STORM-2): a population-based prospective study.

Authors:  Daniela Bernardi; Petra Macaskill; Marco Pellegrini; Marvi Valentini; Carmine Fantò; Livio Ostillio; Paolina Tuttobene; Andrea Luparia; Nehmat Houssami
Journal:  Lancet Oncol       Date:  2016-06-23       Impact factor: 41.316

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