STATISTICAL MODELING OF GLANDULARITY FROM MAMMOGRAPHY IMAGES.

Abstract

This study presents a methodology for estimation of breast glandularity, which is an important factor to assess radiological risk in mammography patients. The investigation took place in an institution located at department of Antioquia-Colombia, where 200 patients participated. The models were obtained using partial least squares regression, where Dance's model was used as reference; parameters of mammography images, equipment and patient were used as predicting variables (kV, mAs, patient's weight, breast area and mean gray value of breast images). Coefficients of correlation equal to 89 and 88 were obtained for training and validation respectively in mediolateral oblique (MLO) and 84 and 89 for craniocaudal (CC). These models were used to estimate the mean glandular dose for all patients and later to obtain the institutional reference levels, 0.87 and 0.96mGy for CC and MLO, respectively, following the recommendations of the ICRP publication No. 135. This study suggests that glandularity could be estimated with few parameters from equipment and patient.