Comparison of breast percent density estimation from raw versus processed digital mammograms

Diane Li; Sara Gavenonis; Emily Conant; Despina Kontos

doi:10.1117/12.878886

8 March 2011 Comparison of breast percent density estimation from raw versus processed digital mammograms

Diane Li, Sara Gavenonis, Emily Conant, Despina Kontos

Author Affiliations +

Proceedings Volume 7963, Medical Imaging 2011: Computer-Aided Diagnosis; 79631X (2011) https://doi.org/10.1117/12.878886
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

We compared breast percent density (PD%) measures obtained from raw and post-processed digital mammographic (DM) images. Bilateral raw and post-processed medio-lateral oblique (MLO) images from 81 screening studies were retrospectively analyzed. Image acquisition was performed with a GE Healthcare DS full-field DM system. Image post-processing was performed using the PremiumView^TM algorithm (GE Healthcare). Area-based breast PD% was estimated by a radiologist using a semi-automated image thresholding technique (Cumulus, Univ. Toronto). Comparison of breast PD% between raw and post-processed DM images was performed using the Pearson correlation (r), linear regression, and Student's t-test. Intra-reader variability was assessed with a repeat read on the same data-set. Our results show that breast PD% measurements from raw and post-processed DM images have a high correlation (r=0.98, R²=0.95, p<0.001). Paired t-test comparison of breast PD% between the raw and the post-processed images showed a statistically significant difference equal to 1.2% (p = 0.006). Our results suggest that the relatively small magnitude of the absolute difference in PD% between raw and post-processed DM images is unlikely to be clinically significant in breast cancer risk stratification. Therefore, it may be feasible to use post-processed DM images for breast PD% estimation in clinical settings. Since most breast imaging clinics routinely use and store only the post-processed DM images, breast PD% estimation from post-processed data may accelerate the integration of breast density in breast cancer risk assessment models used in clinical practice.

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Diane Li, Sara Gavenonis, Emily Conant, and Despina Kontos "Comparison of breast percent density estimation from raw versus processed digital mammograms", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79631X (8 March 2011); https://doi.org/10.1117/12.878886

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