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

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.

Citation Download Citation

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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