Influence of signal-to-noise ratio and temporal stability on computer-aided detection of mammographic microcalcifications in digitized screen-film and full-field digital mammography

Abstract

Most computer-aided detection (CADe) schemes were developed for digitized screen-film mammography (dSFM) and are being transitioned to full-field digital mammography (FFDM). In this research, phantoms were used to relate image quality differences to the performance of the multiple components of our microcalcification CADe scheme, and to identify to what extent, if any, each CADe component is likely to require modification for FFDM. We compared multiple image quality metrics for a dSFM imaging chain (GE DMR, MinR-2000 and Lumisiys digitizer) and an FFDM system (GE Senographe 2000D) and related them to CADe performance for images of 1) contrast-detail phantom disks and 2) microcalcification phantoms (bone fragments and cadaver breasts). Higher object signal-to noise ratio (SNR) in FFDM compared with dSFM (p<0.05 for 62% of disks, and p>0.05 for 32% of disks) led to superior CADe signal and cluster detection FROC performance. Signal segmentation was comparable (p>0.05 for 74% of disks) in dSFM and FFDM and superior in FFDM (p<0.05) for 19% of disks. Better FFDM temporal stability led to more reproducible CADe performance. For microcalcification phantoms, seven of eight computer-calculated features performed better or comparably (p<0.05) at classifying true- and false-positive detections in FFDM. In conclusion, the image quality improvements offered by FFDM compared to dSFM led to comparable or improved performance of the multiple stages of our CADe scheme for microcalcification detection.