Paper
11 March 2014 Pursuing optimal thresholds to recommend breast biopsy by quantifying the value of tomosynthesis
Yirong Wu, Oguzhan Alagoz, David J. Vanness, Amy Trentham-Dietz, Elizabeth S. Burnside
Author Affiliations +
Abstract
A 2% threshold has been traditionally used to recommend breast biopsy in mammography. We aim to characterize how the biopsy threshold varies to achieve the maximum expected utility (MEU) of tomosynthesis for breast cancer diagnosis. A cohort of 312 patients, imaged with standard full field digital mammography (FFDM) and digital breast tomosynthesis (DBT), was selected for a reader study. Fifteen readers interpreted each patient’s images and estimated the probability of malignancy using two modes: FFDM versus FFDM + DBT. We generated receiver operator characteristic (ROC) curves with the probabilities for all readers combined. We found that FFDM+DBT provided improved accuracy and MEU compared with FFDM alone. When DBT was included in the diagnosis along with FFDM, the optimal biopsy threshold increased to 2.7% as compared with the 2% threshold for FFDM alone. While understanding the optimal threshold from a decision analytic standpoint will not help physicians improve their performance without additional guidance (e.g. decision support to reinforce this threshold), the discovery of this level does demonstrate the potential clinical improvements attainable with DBT. Specifically, DBT has the potential to lead to substantial improvements in breast cancer diagnosis since it could reduce the number of patients recommended for biopsy while preserving the maximal expected utility.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yirong Wu, Oguzhan Alagoz, David J. Vanness, Amy Trentham-Dietz, and Elizabeth S. Burnside "Pursuing optimal thresholds to recommend breast biopsy by quantifying the value of tomosynthesis", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370U (11 March 2014); https://doi.org/10.1117/12.2042905
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Cited by 3 scholarly publications.
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KEYWORDS
Biopsy

Breast cancer

Digital breast tomosynthesis

Breast

Mammography

Tumor growth modeling

Biological research

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