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The impact of breast structure on lesion detection in breast tomosynthesis

Publication ,  Conference
Kiarashi, N; Nolte, LW; Lo, JY; Segars, WP; Ghate, SV; Samei, E
Published in: Progress in Biomedical Optics and Imaging - Proceedings of SPIE
January 1, 2015

Virtual clinical trials (VCT) can be carefully designed to inform, orient, or potentially replace clinical trials. The focus of this study was to demonstrate the capability of the sophisticated tools that can be used in the design, implementation, and performance analysis of VCTs, through characterization of the effect of background tissue density and heterogeneity on the detection of irregular masses in digital breast tomosynthesis. Twenty breast phantoms from the extended cardiactorso (XCAT) family, generated based on dedicated breast computed tomography of human subjects, were used to extract a total of 2173 volumes of interest (VOI) from simulated tomosynthesis images. Five different lesions, modeled after human subject tomosynthesis images, were embedded in the breasts, for a total of 6×2173 VOIs with and without lesions. Effects of background tissue density and heterogeneity on the detection of the lesions were studied by implementing a doubly composite hypothesis signal detection theory paradigm with location known exactly, lesion known exactly, and background known statistically. The results indicated that the detection performance as measured by the area under the receiver operating characteristic curve (ROC) deteriorated as density was increased, yielding findings consistent with clinical studies. The detection performance varied substantially across the twenty breasts. Furthermore, the log-likelihood ratio under H0 and H1seemed to be affected by background tissue density and heterogeneity differently. Considering background tissue variability can change the outcomes of a VCT and is hence of crucial importance. The XCAT breast phantoms can address this concern by offering realistic modeling of background tissue variability based on a wide range of human subjects.

Duke Scholars

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781628415025

Publication Date

January 1, 2015

Volume

9412
 

Citation

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Kiarashi, N., Nolte, L. W., Lo, J. Y., Segars, W. P., Ghate, S. V., & Samei, E. (2015). The impact of breast structure on lesion detection in breast tomosynthesis. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9412). https://doi.org/10.1117/12.2082473
Kiarashi, N., L. W. Nolte, J. Y. Lo, W. P. Segars, S. V. Ghate, and E. Samei. “The impact of breast structure on lesion detection in breast tomosynthesis.” In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 9412, 2015. https://doi.org/10.1117/12.2082473.
Kiarashi N, Nolte LW, Lo JY, Segars WP, Ghate SV, Samei E. The impact of breast structure on lesion detection in breast tomosynthesis. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2015.
Kiarashi, N., et al. “The impact of breast structure on lesion detection in breast tomosynthesis.” Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 9412, 2015. Scopus, doi:10.1117/12.2082473.
Kiarashi N, Nolte LW, Lo JY, Segars WP, Ghate SV, Samei E. The impact of breast structure on lesion detection in breast tomosynthesis. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2015.
Journal cover image

Published In

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

DOI

ISSN

1605-7422

ISBN

9781628415025

Publication Date

January 1, 2015

Volume

9412