The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Sophia Zackrisson, MD, PhD. Photo.

Sophia Zackrisson

Manager

Sophia Zackrisson, MD, PhD. Photo.

Identifying and modelling clinical subpopulations from the Malmö breast tomosynthesis screening trial

Author

  • B. Torlegård
  • A. Tingberg
  • S. Zackrisson
  • B. Barufaldi
  • A. D.A. Maidment
  • M. Dustler
  • P. R. Bakic

Editor

  • Hilde Bosmans
  • Nicholas Marshall
  • Chantal Van Ongeval

Summary, in English

Virtual Clinical Trials (VCT) are an effective tool to evaluate the performance of novel imaging systems using computer simulations. VCT results depend on the selection of virtual patient populations. In the case of breast imaging, virtual patients should be matched to a desired clinical population in terms of selected anatomical or demographic descriptors. We are developing a virtual population of women who participated in the Malmö Breast Tomosynthesis Screening Trial (MBTST). We have used clinical values of the compressed breast thickness and volumetric breast density to develop a multidimensional distribution of women in MBTST. Breast density and thickness values were obtained from anonymized, previously collected tomosynthesis images of 14,746 women. In this paper, we compare several approaches to identify clinical subpopulations and select virtual patients that represent various groups of clinical subjects. We performed two methods to identify clinical subpopulations by clustering clinical data using the K-means algorithm or woman's age. The obtained clusters have been explored and compared using the silhouette mean. The K-means algorithm yielded grouping of MBTST data into two clusters; however, that grouping was, shown to be suboptimal by the silhouette analysis. The agebased clustering showed significant overlap in terms of breast thickness and density. We also compared two approaches to select sets of representative phantoms. Our analysis has emphasized benefits and limitations of different clustering methods. The preferred method depends on the specific task that should be addressed using VCTs. Simulation of representative phantoms is ongoing. Potential correlations with pathological findings and/or parenchymal properties will be investigated.

Department/s

  • LUCC: Lund University Cancer Centre
  • Medical Radiation Physics, Malmö
  • EpiHealth: Epidemiology for Health
  • Radiology Diagnostics, Malmö
  • Medical Radiation Physics, Lund
  • Diagnostic Radiology, (Lund)

Publishing year

2020

Language

English

Publication/Series

Proceedings of SPIE - The International Society for Optical Engineering

Volume

11513

Document type

Conference paper

Publisher

SPIE

Topic

  • Cancer and Oncology

Keywords

  • Anatomy simulation
  • Breast anatomy
  • Breast density
  • Compressed breast thickness
  • Malmö Breast Tomosynthesis Screening Trial
  • Virtual Clinical Trials
  • Virtual populations

Conference name

15th International Workshop on Breast Imaging, IWBI 2020

Conference date

2020-05-25 - 2020-05-27

Conference place

Leuven, Belgium

Status

Published

Project

  • Simultaneous Digital Breast Tomosynthesis and Mechanical Imaging

Research group

  • Medical Radiation Physics, Malmö
  • Radiology Diagnostics, Malmö

ISBN/ISSN/Other

  • ISSN: 1996-756X
  • ISSN: 0277-786X
  • ISBN: 9781510638310