American Association for Cancer Research
10559965epi141362-sup-142220_1_supp_0_nm73pg.doc (65.5 kB)

Supplementary Figure 1 from Pectoral Muscle Attenuation as a Marker for Breast Cancer Risk in Full-Field Digital Mammography

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journal contribution
posted on 2023-03-31, 13:47 authored by Abbas Cheddad, Kamila Czene, Per Hall, Keith Humphreys

Supplementary Figure 1: MIP distributions across the different machine types reported in this study.



Background: Mammographic percent density is an established marker of breast cancer risk. In a study of screen film mammograms, we recently reported a novel feature from the pectoral muscle region to be associated with breast cancer risk independently of area percent density (APD). We now investigate whether our novel feature is associated with risk in a study based on full-field digital mammography (FFDM).Methods: We carried out a breast cancer risk analysis using a data set of 3,552 healthy controls and 278 cases. We included three image-based measures in our analyses: volumetric percent density (VPD), APD, and the mean intensity of the pectoral muscle (MIP). The datasets comprised different machine vendors and models. In addition, the controls dataset was used to test for the association of our measures against rs10995190, in the ZNF365 gene, a genetic variant known to be associated with mammography density and breast cancer risk.Results: MIP was associated with breast cancer risk [per SD OR, 0.811; 95% confidence interval (CI), 0.707–0.930; P = 0.0028] after adjusting for conventional covariates and VPD. It was also associated with the genetic variant rs10995190 after adjusting for VPD and other covariates (per allele effect = 0.111; 95% CI, 0.053–0.170; P = 1.8 × 10−4). Results were similar when adjusting for APD instead of VPD.Conclusion: MIP is a novel mammographic marker, which is associated with breast cancer risk and the genetic variant rs10995190 independently of PD measures.Impact: Inclusion of MIP in risk models should be considered for studies using PD from FFDM. Cancer Epidemiol Biomarkers Prev; 24(6); 985–91. ©2015 AACR.

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