Abstract
Detectability of invasive cancerous lesions in mammography is diminished in breasts with dense and complex fibroglandular tissue. If masking were locally quantified in mammograms, radiologists could potentially use this information to clear the region using targeted adjuvant screening techniques. We present a method to quantify localized masking using a model observer to detect virtual objects of varying thickness and size convoluted into the clinical mammogram. Contrast detail curves are used to create an Image Quality Factor (IQF) at high resolution throughout the breast. We report on preliminary findings of how IQF is related to measures of breast density and textural complexity in a cohort of women who experienced screening detected and interval (masked) cancers. This measure of masking using a localized contrast detail curve approach should provide a means to target adjuvant screening resources for faster and more effective determination of cancer status for women with dense breast.
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Acknowledgements
I would like to thank the CBCRP for their generous grant that made this work possible under grant #21IB-0130. I would further like to thank the Shepherd Lab, Bo Fan, Jesus Avila, Bennett Ng, and the NSF GRFP for various types of support: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1144247. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.
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Hinton, B. et al. (2016). A Measure of Regional Mammographic Masking Based on the CDMAM Phantom. In: Tingberg, A., Lång, K., Timberg, P. (eds) Breast Imaging. IWDM 2016. Lecture Notes in Computer Science(), vol 9699. Springer, Cham. https://doi.org/10.1007/978-3-319-41546-8_66
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DOI: https://doi.org/10.1007/978-3-319-41546-8_66
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