Performance of Digital Breast Tomosynthesis, Synthetic Mammography, and Digital Mammography in Breast Cancer Screening: A Systematic Review and Meta-Analysis

Mostafa Alabousi; Akshay Wadera; Mohammed Kashif Al-Ghita; Rayeh Kashef Al-Ghetaa; Jean-Paul Salameh; Alex Pozdnyakov; Nanxi Zha; Lucy Samoilov; Anahita Dehmoobad Sharifabadi; Behnam Sadeghirad; Vivianne Freitas; Matthew Df McInnes; Abdullah Alabousi

doi:10.1093/jnci/djaa205

Performance of Digital Breast Tomosynthesis, Synthetic Mammography, and Digital Mammography in Breast Cancer Screening: A Systematic Review and Meta-Analysis

J Natl Cancer Inst. 2021 Jun 1;113(6):680-690. doi: 10.1093/jnci/djaa205.

Affiliations

¹ Department of Radiology, McMaster University, Hamilton, ON, Canada.
² Faculty of Biomedical Sciences, Western University, London, ON, Canada.
³ Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
⁴ Department of Radiology, University of Ottawa, Ottawa, ON, Canada.
⁵ Faculty of Medicine, McMaster University, Hamilton, ON, Canada.
⁶ Department of Health Research Methods, Evidence, and Impact (HEI), The Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada.
⁷ Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada.
⁸ Department of Radiology and Epidemiology, University of Ottawa, Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, ON, Canada.
⁹ Department of Radiology, McMaster University, St Joseph's Healthcare Hamilton, Hamilton, ON, Canada.

Abstract

Background: Our objective was to perform a systematic review and meta-analysis comparing the breast cancer detection rate (CDR), invasive CDR, recall rate, and positive predictive value 1 (PPV1) of digital mammography (DM) alone, combined digital breast tomosynthesis (DBT) and DM, combined DBT and synthetic 2-dimensional mammography (S2D), and DBT alone.

Methods: MEDLINE and Embase were searched until April 2020 to identify comparative design studies reporting on patients undergoing routine breast cancer screening. Random effects model proportional meta-analyses estimated CDR, invasive CDR, recall rate, and PPV1. Meta-regression modeling was used to compare imaging modalities. All statistical tests were 2-sided.

Results: Forty-two studies reporting on 2 606 296 patients (13 003 breast cancer cases) were included. CDR was highest in combined DBT and DM (6.36 per 1000 screened, 95% confidence interval [CI] = 5.62 to 7.14, P < .001), and combined DBT and S2D (7.40 per 1000 screened, 95% CI = 6.49 to 8.37, P < .001) compared with DM alone (4.68 per 1000 screened, 95% CI = 4.28 to 5.11). Invasive CDR was highest in combined DBT and DM (4.53 per 1000 screened, 95% CI = 3.97 to 5.12, P = .003) and combined DBT and S2D (5.68 per 1000 screened, 95% CI = 4.43 to 7.09, P < .001) compared with DM alone (3.42 per 1000 screened, 95% CI = 3.02 to 3.83). Recall rate was lowest in combined DBT and S2D (42.3 per 1000 screened, 95% CI = 37.4 to 60.4, P<.001). PPV1 was highest in combined DBT and DM (10.0%, 95% CI = 8.0% to 12.0%, P = .004), and combined DBT and S2D (16.0%, 95% CI = 10.0% to 23.0%, P < .001), whereas no difference was detected for DBT alone (7.0%, 95% CI = 6.0% to 8.0%, P = .75) compared with DM alone (7.0%, 95.0% CI = 5.0% to 8.0%).

Conclusions: Our findings provide evidence on key performance metrics for DM, DBT alone, combined DBT and DM, and combined DBT and S2D, which may inform optimal application of these modalities for breast cancer screening.

Publication types

Meta-Analysis
Systematic Review

MeSH terms

Breast
Breast Neoplasms* / diagnostic imaging
Breast Neoplasms* / epidemiology
Early Detection of Cancer* / methods
Female
Humans
Mammography / methods
Mass Screening / methods
Predictive Value of Tests
Retrospective Studies