Mammographic density in relation to breast cancer Tumor characteristics, mode of detection, and density assessments
Author
Summary, in English
Mammographic density reflects the composition of the breast tissue and can be measured by different methods. Mammography has a lower sensitivity in women with dense breasts, and women with dense breasts have a higher incidence of breast cancer than do women with non–dense breasts. Furthermore, there has been an increased interest in improving the measurement of mammographic density.
The aim of this thesis was to study how mammographic density relates to breast cancer in terms of mammographic tumor features, pathological tumor characteristics, and mode of detection. An additional aim was to assess the agreement between two methods of measuring mammographic density.
In Papers I-III, we used 826 breast cancer cases from the population-based, prospective Malmö Diet and Cancer Study. Our findings imply that the spiculated mammographic tumor feature was related to invasiveness, and ill-defined mass was related to large tumor size, regardless of the mode of detection and mammographic density. Second, higher mammographic density was associated with larger tumor size, as well as axillary lymph node involvement in invasive breast cancer. Furthermore, in screening detected breast cancer, higher mammographic density was associated with lower histological grade, although the evidence for this was weak. Finally, our findings in clinically detected breast cancer, but not in cancers detected during screening, imply that higher mammographic density was associated with estrogen receptor-negative and triple-negative breast cancers.
In Paper IV, we used 8,889 mammography examinations from the Malmö Breast Tomosynthesis Screening Trial. There was substantial agreement between the Breast Imaging-Reporting and Data System (BI-RADS) score from different radiologists and moderate agreement between the BI-RADS score and the fully automated volumetric assessment (Volpara software) of mammographic density.
This thesis shows that some of the mammographic tumor features and the pathological tumor characteristics in breast cancer tend to differ with mammographic density and the mode of detection. Further, there was moderate agreement between a fully automated volumetric assessment and the radiologists’ qualitative classification of mammographic density.
The aim of this thesis was to study how mammographic density relates to breast cancer in terms of mammographic tumor features, pathological tumor characteristics, and mode of detection. An additional aim was to assess the agreement between two methods of measuring mammographic density.
In Papers I-III, we used 826 breast cancer cases from the population-based, prospective Malmö Diet and Cancer Study. Our findings imply that the spiculated mammographic tumor feature was related to invasiveness, and ill-defined mass was related to large tumor size, regardless of the mode of detection and mammographic density. Second, higher mammographic density was associated with larger tumor size, as well as axillary lymph node involvement in invasive breast cancer. Furthermore, in screening detected breast cancer, higher mammographic density was associated with lower histological grade, although the evidence for this was weak. Finally, our findings in clinically detected breast cancer, but not in cancers detected during screening, imply that higher mammographic density was associated with estrogen receptor-negative and triple-negative breast cancers.
In Paper IV, we used 8,889 mammography examinations from the Malmö Breast Tomosynthesis Screening Trial. There was substantial agreement between the Breast Imaging-Reporting and Data System (BI-RADS) score from different radiologists and moderate agreement between the BI-RADS score and the fully automated volumetric assessment (Volpara software) of mammographic density.
This thesis shows that some of the mammographic tumor features and the pathological tumor characteristics in breast cancer tend to differ with mammographic density and the mode of detection. Further, there was moderate agreement between a fully automated volumetric assessment and the radiologists’ qualitative classification of mammographic density.
Department/s
- Radiology Diagnostics, Malmö
- BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
Publishing year
2015
Language
English
Publication/Series
Lund University Faculty of Medicine Doctoral Dissertation Series
Volume
2015:91
Full text
Document type
Dissertation
Publisher
Medical Radiology Unit
Topic
- Radiology, Nuclear Medicine and Medical Imaging
Status
Published
Research group
- Radiology Diagnostics, Malmö
ISBN/ISSN/Other
- ISSN: 1652-8220
- ISBN: 978-91-7619-170-5
Defence date
15 October 2015
Defence time
09:00
Defence place
Room 2005-2007, Inga Marie Nilssons gata 49, Skåne University Hospital, Malmö
Opponent
- Malin Sund