Sophia Zackrisson
Research group manager, Principal investigator, Professor, MD
Malmö Breast ImaginG database: objectives and development
Author
Summary, in English
Purpose
We describe the design and implementation of the Malmö Breast ImaginG (M-BIG) database, which will support research projects investigating various aspects of current and future breast cancer screening programs. Specifically, M-BIG will provide clinical data to:
1. investigate the effect of breast cancer screening on breast cancer prognosis and mortality;
2. develop and validate the use of artificial intelligence and machine learning in breast image interpretation; and
3. develop and validate image-based radiological breast cancer risk profiles.
Approach
The M-BIG database is intended to include a wide range of digital mammography (DM) and digital breast tomosynthesis (DBT) examinations performed on women at the Mammography Clinic in Malmö, Sweden, from the introduction of DM in 2004 through 2020. Subjects may be included multiple times and for diverse reasons. The image data are linked to extensive clinical, diagnostic, and demographic data from several registries.
Results
To date, the database contains a total of 451,054 examinations from 104,791 women. During the inclusion period, 95,258 unique women were screened. A total of 19,968 examinations were performed using DBT, whereas the rest used DM.
Conclusions
We describe the design and implementation of the M-BIG database as a representative and accessible medical image database linked to various types of medical data. Work is ongoing to add features and curate the existing data.
We describe the design and implementation of the Malmö Breast ImaginG (M-BIG) database, which will support research projects investigating various aspects of current and future breast cancer screening programs. Specifically, M-BIG will provide clinical data to:
1. investigate the effect of breast cancer screening on breast cancer prognosis and mortality;
2. develop and validate the use of artificial intelligence and machine learning in breast image interpretation; and
3. develop and validate image-based radiological breast cancer risk profiles.
Approach
The M-BIG database is intended to include a wide range of digital mammography (DM) and digital breast tomosynthesis (DBT) examinations performed on women at the Mammography Clinic in Malmö, Sweden, from the introduction of DM in 2004 through 2020. Subjects may be included multiple times and for diverse reasons. The image data are linked to extensive clinical, diagnostic, and demographic data from several registries.
Results
To date, the database contains a total of 451,054 examinations from 104,791 women. During the inclusion period, 95,258 unique women were screened. A total of 19,968 examinations were performed using DBT, whereas the rest used DM.
Conclusions
We describe the design and implementation of the M-BIG database as a representative and accessible medical image database linked to various types of medical data. Work is ongoing to add features and curate the existing data.
Department/s
- LUCC: Lund University Cancer Centre
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
- eSSENCE: The e-Science Collaboration
- LU Profile Area: Light and Materials
- LTH Profile Area: Photon Science and Technology
- EpiHealth: Epidemiology for Health
Publishing year
2023-02-08
Language
English
Publication/Series
Journal of Medical Imaging
Volume
10
Issue
6
Document type
Journal article
Publisher
SPIE
Topic
- Radiology, Nuclear Medicine and Medical Imaging
- Cancer and Oncology
Status
Published
Research group
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
ISBN/ISSN/Other
- ISSN: 2329-4302