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Malmö Breast ImaginG database: objectives and development.

Victor Dahlblom1,2, Magnus Dustler1,3, Anetta Bolejko1,2

  • 1Lund University, Department of Translational Medicine, Diagnostic Radiology, Malmö, Sweden.

Journal of Medical Imaging (Bellingham, Wash.)
|February 13, 2023
PubMed
Summary
This summary is machine-generated.

The Malmö Breast Imaging (M-BIG) database supports breast cancer research by providing linked clinical and imaging data. This resource aids studies on screening effectiveness, AI in image interpretation, and risk profiling.

Keywords:
artificial intelligencebig databreast cancer screeningdatabase management systemsmammography

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Area of Science:

  • Medical Imaging
  • Radiology
  • Oncology

Background:

  • Breast cancer screening programs are crucial for early detection and improved patient outcomes.
  • Advancements in digital mammography (DM) and digital breast tomosynthesis (DBT) have enhanced imaging capabilities.
  • Integrating diverse data sources is key to advancing breast cancer research.

Purpose of the Study:

  • To establish the Malmö Breast Imaging (M-BIG) database for breast cancer research.
  • To support investigations into breast cancer screening's impact on prognosis and mortality.
  • To facilitate the development and validation of AI/machine learning in breast image interpretation.
  • To enable the creation and validation of image-based radiological breast cancer risk profiles.

Main Methods:

  • The M-BIG database aggregates digital mammography (DM) and digital breast tomosynthesis (DBT) examinations.
  • Data spans from 2004 to 2020 from the Mammography Clinic in Malmö, Sweden.
  • Image data is linked to comprehensive clinical, diagnostic, and demographic registries.

Main Results:

  • The database currently holds 451,054 examinations from 104,791 women.
  • 95,258 unique women were screened during the inclusion period.
  • 19,968 examinations utilized DBT, with the remainder using DM.

Conclusions:

  • The M-BIG database is a well-designed, accessible resource linking medical images with extensive clinical data.
  • Ongoing efforts focus on enhancing database features and data curation.
  • M-BIG is poised to significantly contribute to breast cancer research and screening advancements.