Diagnostic methods to effectively image dense breast tissue (DBT) can pose challenges for breast cancer screening. While conventional mammography is the gold standard for breast cancer screening, this technique has a low sensitivity to DBT and can miss about 78% of cancers in DBT, but magnetic resonance imaging (MRI) has a high sensitivity for imaging DBT, and produces a smaller number of false positives. The purpose of this study was to determine the extent to which conventional mammograms can miss breast cancer in women with DBT and to determine if an adjunct method of imaging DBT might detect breast cancers that are missed by mammography alone. Quantitative data were collected from a sample of 300 randomly selected participants using surveys. SPSS statistical software was used to analyze the data with the factor analysis method. Qualitative data were collected by telephone interviews from 10 women who were patients of a breast cancer center. NVivo software was used to analyze the data with the thematic analysis method. All analyses were guided by theoretical framework of von Bertalanffy's general systems theory, Miller's living systems theory, and the theory of intelligent medical diagnosis. Key results determined that a significant number of women with DBT had breast cancer that was undetected by mammograms; results also showed that women with DBT can benefit from breast cancer screening by adding an adjunct screening method (e.g., MRI). This study may contribute to social change by making the breast cancer screening community aware of the potential benefit of adding MRI as an adjunct to conventional screening so that more breast cancers are detected in the early stages of the disease.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-1389 |
| Date | 01 January 2015 |
| Creators | Connett, Rachel Sunmattie |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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