2.4. Statistical analysis

Final assessments using 2DSM and FFDM were divided into two categories based on BI-RADS score as positive (score of 3–5) or negative (score of 1–2), and true or false interpretations of the observers were assessed in both 2DSM and FFDM images according to the pathologic reference standard and reference mammographic findings. Cancer detection rates (percentage of detected cancers per total cancers) and conspicuity scores of 2DSM and FFDM were also compared. For subgroup analyses, patients were grouped according to breast density (non-dense, n = 52; dense, n = 84), tumor size (≤1 cm, n = 15; 1–2 cm, n = 72; >2 cm, n = 49), or presence of calcification (calcified cancers, n = 42; non-calcified, n = 94). Breast density was categorized as either dense breasts, including heterogeneous or extremely dense breasts, or non-dense breasts, including almost fatty or fibro-glandular scattered breasts. Non-calcified cancers included cancers that appeared as a mass, with focal asymmetry, asymmetry, or architectural distortion.

The kappa test was used to assess inter-observer variability in terms of the final assessment (BI-RADS category assignment) and agreement between 2DSM and FFDM images based on mammographic features (calcified and non-calcified cancer) and breast density (dense and non-dense breasts). Degrees of agreement were categorized as follows: k values of 0.00–0.20 indicated poor agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, good agreement; and 0.81–1.00, excellent agreement.

Differences in cancer detection rates between 2DSM and FFDM images were analyzed using the McNemar test. Wilcoxon’s signed rank test was used to compare visibility scores. These analyses were performed using SAS statistical software (SAS system for Windows, version 9.1.3; SAS Institute, Cary, NC, USA). A p-value < 0.05 was considered statistically significant.