Literature DB >> 27345635

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.

Daniela Bernardi1, Petra Macaskill2, Marco Pellegrini1, Marvi Valentini1, Carmine Fantò1, Livio Ostillio1, Paolina Tuttobene1, Andrea Luparia1, Nehmat Houssami3.   

Abstract

BACKGROUND: Breast tomosynthesis (pseudo-3D mammography) improves breast cancer detection when added to 2D mammography. In this study, we examined whether integrating 3D mammography with either standard 2D mammography acquisitions or with synthetic 2D images (reconstructed from 3D mammography) would detect more cases of breast cancer than 2D mammography alone, to potentially reduce the radiation burden from the combination of 2D plus 3D acquisitions.
METHODS: The Screening with Tomosynthesis Or standard Mammography-2 (STORM-2) study was a prospective population-based screening study comparing integrated 3D mammography (dual-acquisition 2D-3D mammography or 2D synthetic-3D mammography) with 2D mammography alone. Asymptomatic women aged 49 years or older who attended population-based screening in Trento, Italy were recruited for the study. All participants underwent digital mammography with 2D and 3D mammography acquisitions, with the use of software that allowed synthetic 2D mammographic images to be reconstructed from 3D acquisitions. Mammography screen-reading was done in two parallel double-readings conducted sequentially for 2D acquisitions followed by integrated acquisitions. Recall based on a positive mammography result was defined as recall at any screen read. Primary outcome measures were a comparison between integrated (2D-3D or 2D synthetic-3D) mammography and 2D mammography alone of the number of cases of screen-detected breast cancer, the cancer detection rate per 1000 screens, the incremental cancer detection rate, and the number and percentage of false-positive recalls.
FINDINGS: Between May 31, 2013, and May 29, 2015, 10 255 women were invited to participate, of whom 9672 agreed to participate and were screened. In these 9672 participants (median age 58 years [IQR 53-63]), screening detected 90 cases of breast cancer, including 74 invasive breast cancers, in 85 women (five women had bilateral breast cancer). To account for these bilateral cancers in cancer detection rate estimates, the number of screens used for analysis was 9677. Both 2D-3D mammography (cancer detection rate 8·5 per 1000 screens [82 cancers detected in 9677 screens]; 95% CI 6·7-10·5) and 2D synthetic-3D mammography (8·8 per 1000 [85 in 9677]; 7·0-10·8) had significantly higher rates of breast cancer detection than 2D mammography alone (6·3 per 1000 [61 in 9677], 4·8-8·1; p<0·0001 for both comparisons). The cancer detection rate did not differ significantly between 2D-3D mammography and 2D synthetic-3D mammography (p=0·58). Compared with 2D mammography alone, the incremental cancer detection rate from 2D-3D mammography was 2·2 per 1000 screens (95% CI 1·2-3·3) and that from 2D synthetic-3D mammography was 2·5 per 1000 (1·4-3·8). Compared with the proportion of false-positive recalls from 2D mammography alone (328 of 9587 participants not found to have cancer at assessment) [3·42%; 95% CI 3·07-3·80]), false-positive recall was significantly higher for 2D-3D mammography (381 of 9587 [3·97%; 3·59-4·38], p=0·00063) and for 2D synthetic-3D mammography (427 of 9587 [4·45%; 4·05-4·89], p<0·0001).
INTERPRETATION: Integration of 3D mammography (2D-3D or 2D synthetic-3D) detected more cases of breast cancer than 2D mammography alone, but increased the percentage of false-positive recalls in sequential screen-reading. These results should be considered in the context of the trade-off between benefits and harms inherent in population breast cancer screening, including that significantly increased breast cancer detection from integrating 3D mammography into screening has the potential to augment screening benefit and also possibly contribute to overdiagnosis. FUNDING: None.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2016        PMID: 27345635     DOI: 10.1016/S1470-2045(16)30101-2

Source DB:  PubMed          Journal:  Lancet Oncol        ISSN: 1470-2045            Impact factor:   41.316


  51 in total

1.  Synthesizing mammogram from digital breast tomosynthesis.

Authors:  Jun Wei; Heang-Ping Chan; Mark A Helvie; Marilyn A Roubidoux; Colleen H Neal; Yao Lu; Lubomir M Hadjiiski; Chuan Zhou
Journal:  Phys Med Biol       Date:  2019-02-11       Impact factor: 3.609

Review 2.  Digital Breast Tomosynthesis: Concepts and Clinical Practice.

Authors:  Alice Chong; Susan P Weinstein; Elizabeth S McDonald; Emily F Conant
Journal:  Radiology       Date:  2019-05-14       Impact factor: 11.105

Review 3.  Deep learning in breast radiology: current progress and future directions.

Authors:  William C Ou; Dogan Polat; Basak E Dogan
Journal:  Eur Radiol       Date:  2021-01-15       Impact factor: 5.315

Review 4.  Applications of Advanced Breast Imaging Modalities.

Authors:  Arwa A Alzaghal; Pamela J DiPiro
Journal:  Curr Oncol Rep       Date:  2018-05-29       Impact factor: 5.075

Review 5.  Imaging Surveillance After Primary Breast Cancer Treatment.

Authors:  Diana L Lam; Nehmat Houssami; Janie M Lee
Journal:  AJR Am J Roentgenol       Date:  2017-01-11       Impact factor: 3.959

6.  External validation of AI algorithms in breast radiology: the last healthcare security checkpoint?

Authors:  Teodoro Martin-Noguerol; Antonio Luna
Journal:  Quant Imaging Med Surg       Date:  2021-06

7.  Technical evaluation of image quality in synthetic mammograms obtained from 15° and 40° digital breast tomosynthesis in a commercial system: a quantitative comparison.

Authors:  Patrizio Barca; Rocco Lamastra; Raffaele Maria Tucciariello; Antonio Traino; Carolina Marini; Giacomo Aringhieri; Davide Caramella; Maria Evelina Fantacci
Journal:  Phys Eng Sci Med       Date:  2020-11-23

8.  Prospective study aiming to compare 2D mammography and tomosynthesis + synthesized mammography in terms of cancer detection and recall. From double reading of 2D mammography to single reading of tomosynthesis.

Authors:  Sara Romero Martín; Jose Luis Raya Povedano; María Cara García; Ana Luz Santos Romero; Margarita Pedrosa Garriguet; Marina Álvarez Benito
Journal:  Eur Radiol       Date:  2018-01-02       Impact factor: 5.315

9.  Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction.

Authors:  Yao Lu; Heang-Ping Chan; Jun Wei; Lubomir M Hadjiiski; Ravi K Samala
Journal:  Phys Med Biol       Date:  2017-09-15       Impact factor: 3.609

10.  Cost-effectiveness of Digital Breast Tomosynthesis in Population-based Breast Cancer Screening: A Probabilistic Sensitivity Analysis.

Authors:  Valérie D V Sankatsing; Karolina Juraniec; Sabine E Grimm; Manuela A Joore; Ruud M Pijnappel; Harry J de Koning; Nicolien T van Ravesteyn
Journal:  Radiology       Date:  2020-08-04       Impact factor: 11.105

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.