Recent years have seen intensive efforts searching for relevant information from mammograms to assist the prediction of long-term breast cancer risk. While mammographic imaging is primarily used for diagnostic purposes, it has other, important uses. To save storage space, typically only for-presentation images are stored. For-presentation images are intended for visual assessment by the radiologists. Mammograms are these days acquired with full-field digital mammography systems and are provided in both for-processing (the raw imaging data) and for-presentation (a postprocessed version of the raw data) image formats. Mammography is the most used imaging modality for breast cancer screening. Our algorithm for for-presentation images performs similarly to a CAD algorithm on for-processing images, hence our algorithm can be a useful tool for research on microcalcifications and their role on breast cancer risk, based on large-scale epidemiological studies with access to for-presentation images. Meaningful measurement of potential microcalcifications, in the context of short-term breast cancer risk assessment, is feasible for for-presentation images across a range of vendors. Similar evidence of association with short-term breast cancer risk was found ( P = and P =, for our approach on for-presentation images and for the CAD measure on for-processing images, respectively) and interestingly both measures contributed independently to association with a short-term risk ( P = for the CAD measure, adjusted for our proposed method and P = for our proposed method, adjusted for the CAD measure). We found a moderate agreement between our measure of potential microcalcification clusters on for-presentation images and a CAD measure on for-processing images.
#Breast calcification clusters software#
We compared results of these analyses to those obtained using a Computer-aided Diagnosis (CAD) software (VuComp) on corresponding for-processing images (images which are used clinically, but typically not saved). Conditional logistic regression Wald tests were used to test for association with the presence of microcalcifications at study entry. In total, 373 incident breast cancer cases (diagnosed at least 3 months after a negative screen at study entry) and 1466 matched controls were included in our study. We studied association with short-term breast cancer risk using a nested case control design, with a mammography screening cohort as a source population. We designed a three-step algorithm for detecting potential microcalcification clusters in for-presentation digital mammograms. We explore using the number of potential microcalcification clusters detected in for-presentation mammographic images (the images which are typically accessible to large epidemiological studies) a marker of short-term breast cancer risk.
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