Assessment of mass detection performance in contrast enhanced digital mammography

Ann-Katherine Carton; Pablo Milioni de Carvalho; Zhijin Li; Clarisse Dromain; Serge Muller

doi:10.1117/12.2081772

17 March 2015 Assessment of mass detection performance in contrast enhanced digital mammography

Ann-Katherine Carton, Pablo Milioni de Carvalho, Zhijin Li, Clarisse Dromain, Serge Muller

Proceedings Volume 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment; 941608 (2015) https://doi.org/10.1117/12.2081772
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

We address the detectability of contrast-agent enhancing masses for contrast-agent enhanced spectral mammography (CESM), a dual-energy technique providing functional projection images of breast tissue perfusion and vascularity using simulated CESM images. First, the realism of simulated CESM images from anthropomorphic breast software phantoms generated with a software X-ray imaging platform was validated. Breast texture was characterized by power-law coefficients calculated in data sets of real clinical and simulated images. We also performed a 2-alternative forced choice (2-AFC) psychophysical experiment whereby simulated and real images were presented side-by-side to an experienced radiologist to test if real images could be distinguished from the simulated images. It was found that texture in our simulated CESM images has a fairly realistic appearance. Next, the relative performance of human readers and previously developed mathematical observers was assessed for the detection of iodine-enhancing mass lesions containing different contrast agent concentrations. A four alternative-forced-choice (4 AFC) task was designed; the task for the model and human observer was to detect which one of the four simulated DE recombined images contained an iodineenhancing mass. Our results showed that the NPW and NPWE models largely outperform human performance. After introduction of an internal noise component, both observers approached human performance. The CHO observer performs slightly worse than the average human observer. There is still work to be done in improving model observers as predictors of human-observer performance. Larger trials could also improve our test statistics. We hope that in the future, this framework of software breast phantoms, virtual image acquisition and processing, and mathematical observers can be beneficial to optimize CESM imaging techniques.

Citation Download Citation

Ann-Katherine Carton, Pablo Milioni de Carvalho, Zhijin Li, Clarisse Dromain, and Serge Muller "Assessment of mass detection performance in contrast enhanced digital mammography", Proc. SPIE 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, 941608 (17 March 2015); https://doi.org/10.1117/12.2081772

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