Literature DB >> 30322817

One-view breast tomosynthesis versus two-view mammography in the Malmö Breast Tomosynthesis Screening Trial (MBTST): a prospective, population-based, diagnostic accuracy study.

Sophia Zackrisson1, Kristina Lång2, Aldana Rosso2, Kristin Johnson2, Magnus Dustler3, Daniel Förnvik4, Hannie Förnvik4, Hanna Sartor2, Pontus Timberg4, Anders Tingberg4, Ingvar Andersson2.   

Abstract

BACKGROUND: Digital breast tomosynthesis is an advancement of the mammographic technique, with the potential to increase detection of lesions during breast cancer screening. The main aim of the Malmö Breast Tomosynthesis Screening Trial (MBTST) was to investigate the accuracy of one-view digital breast tomosynthesis in population screening compared with standard two-view digital mammography.
METHODS: In this prospective, population-based screening study, of women aged 40-74 years invited to attend national breast cancer screening at Skåne University Hospital, Malmö, Sweden, a random sample was asked to participate in the trial (every third woman who was invited to attend regular screening was invited to participate). Participants had to be able to speak English or Swedish and were excluded from the study if they were pregnant. Participants underwent screening with two-view digital mammography (ie, craniocaudal and mediolateral oblique views) followed by one-view digital breast tomosynthesis with reduced compression in the mediolateral oblique view (with a wide tomosynthesis angle of 50°) at one screening visit. Images were read with masked double reading and scoring by two separate reading groups, one for each method, made up of seven radiologists. Any cancer detected with a malignancy probability score of three or higher by any reader in either group was discussed in a consensus meeting of at least two readers, from which the decision of whether or not to recall the woman for further investigation was made. The primary outcome measures were sensitivity and specificity of breast cancer detection. Secondary outcome measures were screening performance measures of cancer detection, recall, and interval cancers (cancers clinically detected between screenings), and positive predictive value for screen recalls and negative predictive value of each method. Outcomes were analysed in the per-protocol population. Follow-up of the participants for at least 2 years allowed for identification of interval cancers. This trial is registered with ClinicalTrials.gov, number NCT01091545.
FINDINGS: Between Jan 27, 2010, and Feb 13, 2015, of 21 691 women invited, 14 851 (68%) agreed to participate. Three women withdrew consent during follow-up and were excluded from the analyses. 139 breast cancers were detected in 137 (<1%) of 14 848 women. Sensitivity was higher for digital breast tomosynthesis than for digital mammography (81·1%, 95% CI 74·2-86·9, vs 60·4%, 52·3-68·0) and specificity was slightly lower for digital breast tomosynthesis than was for digital mammography (97·2%, 95% CI 97·0-97·5, vs 98·1%, 97·9-98·3). The proportion of cancers detected was significantly higher with digital breast tomosynthesis than with digital mammography (8·7 cancers per 1000 women screened, 95% CI 7·3-10·3 vs 6·5 cancers per 1000 screened, 5·2-7·9; p<0·0001). The proportion of women recalled after discussion was higher among cancers detected by digital breast tomosynthesis than for those detected by digital mammography after consensus (3·6%, 95% CI 3·3-3·9 vs 2·5%, 2·2-2·8; p<0·0001). The positive predictive value for screen recalls was 24·1% (95% CI 20·5-28·0) for digital breast tomosynthesis and 25·9% (21·6-30·7) for digital mammography, and the negative predictive value was 99·8% (99·7-99·9) and 99·6% (99·4-99·7), respectively. The proportion of women who developed interval cancers after trial screening was 1·48 cancers per 1000 women screened (95% CI 0·93-2·24).
INTERPRETATION: Breast cancer screening by use of one-view digital breast tomosynthesis with a reduced compression force has higher sensitivity at a slightly lower specificity for breast cancer detection compared with two-view digital mammography and has the potential to reduce the radiation dose and screen-reading burden required by two-view digital breast tomosynthesis with two-view digital mammography. FUNDING: The Swedish Cancer Society, The Swedish Research Council, The Breast Cancer Foundation, The Swedish Medical Society, The Crafoord Foundation, The Gunnar Nilsson Cancer Foundation, The Skåne University Hospital Foundation, Governmental funding for clinical research, The South Swedish Health Care Region, The Malmö Hospital Cancer Foundation and The Cancer Foundation at the Department of Oncology, Skåne University Hospital.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Mesh:

Year:  2018        PMID: 30322817     DOI: 10.1016/S1470-2045(18)30521-7

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


  28 in total

1.  Verification of the accuracy of a hybrid breast imaging simulation framework for virtual clinical trial applications.

Authors:  Liesbeth Vancoillie; Nicholas Marshall; Lesley Cockmartin; Janne Vignero; Guozhi Zhang; Hilde Bosmans
Journal:  J Med Imaging (Bellingham)       Date:  2020-04-22

2.  Artificial Intelligence Detection of Missed Cancers at Digital Mammography That Were Detected at Digital Breast Tomosynthesis.

Authors:  Victor Dahlblom; Ingvar Andersson; Kristina Lång; Anders Tingberg; Sophia Zackrisson; Magnus Dustler
Journal:  Radiol Artif Intell       Date:  2021-09-01

3.  Artificial intelligence computer-aided detection enhances synthesized mammograms: comparison with original digital mammograms alone and in combination with tomosynthesis images in an experimental setting.

Authors:  Takayoshi Uematsu; Kazuaki Nakashima; Taiyo Leopoldo Harada; Hatsuko Nasu; Tatsuya Igarashi
Journal:  Breast Cancer       Date:  2022-08-24       Impact factor: 3.307

4.  Five Consecutive Years of Screening with Digital Breast Tomosynthesis: Outcomes by Screening Year and Round.

Authors:  Emily F Conant; Samantha P Zuckerman; Elizabeth S McDonald; Susan P Weinstein; Katrina E Korhonen; Julia A Birnbaum; Jennifer D Tobey; Mitchell D Schnall; Rebecca A Hubbard
Journal:  Radiology       Date:  2020-03-10       Impact factor: 11.105

5.  Breast Cancer Screening Among Medically Underserved Women in New Mexico: Potential for Lower Recall Rates with Digital Breast Tomosynthesis.

Authors:  Martha T Manda-Mapalo; Stephanie G Fine; Sarah Safadi; Ji-Hyun Lee; Ruofei Du; Andrew L Sussman; Shiraz Mishra; Reed G Selwyn; Jennifer L Saline; Wendy L Hine; Ursa A Brown-Glaberman
Journal:  J Womens Health (Larchmt)       Date:  2020-09-29       Impact factor: 2.681

6.  Evaluation of a new image reconstruction method for digital breast tomosynthesis: effects on the visibility of breast lesions and breast density.

Authors:  Julia Krammer; Sergei Zolotarev; Inge Hillman; Konstantinos Karalis; Dzmitry Stsepankou; Valeriy Vengrinovich; Jürgen Hesser; Tony M Svahn
Journal:  Br J Radiol       Date:  2019-09-05       Impact factor: 3.039

7.  Interval breast cancer rates for digital breast tomosynthesis versus digital mammography population screening: An individual participant data meta-analysis.

Authors:  Nehmat Houssami; Solveig Hofvind; Anne L Soerensen; Kristy P Robledo; Kylie Hunter; Daniela Bernardi; Kristina Lång; Kristin Johnson; Camilla F Aglen; Sophia Zackrisson
Journal:  EClinicalMedicine       Date:  2021-03-20

8.  First proof-of-concept evaluation of the FUSION-X-US-II prototype for the performance of automated breast ultrasound in healthy volunteers.

Authors:  Benedikt Schaefgen; Marija Juskic; Madeleine Hertel; Richard G Barr; Marcus Radicke; Anne Stieber; André Hennigs; Fabian Riedel; Christof Sohn; Joerg Heil; Michael Golatta
Journal:  Arch Gynecol Obstet       Date:  2021-05-10       Impact factor: 2.344

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

Authors:  Alistair Mackenzie; Emma L Thomson; Melissa Mitchell; Premkumar Elangovan; Chantal van Ongeval; Lesley Cockmartin; Lucy M Warren; Louise S Wilkinson; Matthew G Wallis; Rosalind M Given-Wilson; David R Dance; Kenneth C Young
Journal:  Eur Radiol       Date:  2021-07-30       Impact factor: 5.315

Review 10.  Digital Breast Tomosynthesis: an Overview.

Authors:  Ekta Dhamija; Malvika Gulati; S V S Deo; Ajay Gogia; Smriti Hari
Journal:  Indian J Surg Oncol       Date:  2021-05-15
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