Detection of potential microcalcification clusters using multivendor for-presentation digital mammograms for short-term breast cancer risk estimation

Medical Physics
Maya Alsheh AliKeith Humphreys

Abstract

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. We designed a three-step algorithm for detecting potential microcalcification clusters in for-presentation digital mammograms. We studied association with short-term breast cancer risk using a nested case control design, with a mammography screening cohort as a source population. 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. Conditional logistic regression Wald tests were used to test for association with the presence of microcalcifications at study entry. 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). We found a moderate agreement between our measure of potential microcalcification clusters on for-presentation images and a CAD measure on for-processing images. Similar evidence of association with short-term breas...Continue Reading

References

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Citations

Sep 26, 2020·International Journal of Cancer. Journal International Du Cancer·Pui San TanKamila Czene
Jul 26, 2021·Medical & Biological Engineering & Computing·Asma TouilMohamed Ali Mahjoub
Aug 10, 2021·Frontiers in Oncology·Yu-Meng LeiChristoph F Dietrich

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Methods Mentioned

BETA
hormone replacement therapy

Software Mentioned

Vu CAD
DBSCAN
VuComp M ‐ Vu

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