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Breast density is an independent risk factor for breast cancer, where women with denser breasts are more likely to
develop cancer. By identifying women at higher risk, healthcare providers can suggest screening at a younger age to
effectively diagnose and treat breast cancer in its earlier stages. Clinical risk assessment models currently do not
incorporate breast density, despite its strong correlation with breast cancer. Current methods to measure breast density rely
on mammography and MRI, both of which may be difficult to use as a routine risk assessment tool. We propose to use
diffuse optical tomography with structured-light to measure the dense, fibroglandular (FGT) tissue volume, which has a
different chromophore signature than the surrounding adipose tissue. To test the ability of this technique, we performed
simulations by creating numerical breast phantoms from segmented breast MR images. We looked at two different cases,
one with a centralized FGT distribution and one with a dispersed distribution. As expected, the water and lipid volumes
segmented at half-maximum were overestimated for the dispersed case. However, it was noticed that the recovered water
and lipid concentrations were lower and higher, respectively, than the centralized case. This information may provide
insight into the morphological distribution of the FGT and can be a correction in estimating the breast density.
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