Study of Adaptability of Breast Density Analysis System Developed for Screen Film Mammograms (SFMs) to Full-Field Digital Mammograms (FFDMs): Robustness of Parenchymal Texture Analysis

Mammography is in the transition to full-field digital mammograms (FFDM). It is important to evaluate the adaptability of image analysis methods and computer-aided diagnosis (CAD) systems developed with screen-film mammograms (SFM) to FFDMs. In addition, prior SFMs are more readily available for development of new techniques that involve long-term follow up such as breast cancer risk prediction. We have previously developed a texture-feature-based method for mammographic parenchymal pattern (MPP) analysis on SFMs. The MPP measure was found to be more predictive of breast cancer risk than percent dense area on mammograms. In this study, we investigated the correlation of computerized texture features extracted from matched pairs of SFM and FFDM obtained from the same patient using the same algorithms without retraining for MPP analysis. The computerized texture features from the two modalities demonstrated strong correlation, indicating that the MPP analysis system that we developed with SFMs for breast cancer risk prediction can be readily adapted to FFDMs with at most minor retraining.