Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation

Gopal Karemore; Brad M. Keller; Huen Oh; Julia Tchou; Mads Nielsen; Emily F. Conant; Despina Kontos

doi:10.1007/978-3-642-31271-7_77

Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation

Gopal Karemore, Brad M. Keller, Huen Oh, Julia Tchou, Mads Nielsen, Emily F. Conant, Despina Kontos

Datalogisk Institut

4 Citationer (Scopus)

Abstract

We investigate the potential of mammographic parenchymal texture as a surrogate marker of the risk to develop Estrogen Receptor (ER) sub-type specific breast cancer. A case-control study was performed, including 118 cancer cases stratified by ER receptor status and 354 age-matched controls. Digital mammographic (DM) images were retrospectively collected and analyzed under HIPAA and IRB approval. The performance of the texture features was compared to that of the standard mammographic density measures. We observed that breast percent density PD% and parenchymal texture features can both distinguish between cancer cases and controls (A _z > 0.70). However, for ER subtype-specific classification, PD% alone does not provide sufficient classification (A _z = 0.60), while texture features have significant classification performance (A _z = 0.70). Combining breast density with texture features achieves the best performance (A _z = 0.71). These findings suggest that mammographic texture analysis may have value for sub-type specific breast cancer risk assessment.

Originalsprog	Engelsk
Titel	Breast Imaging : 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings
Redaktører	Andrew D. A. Maidment, Predrag R. Bakic, Sara Gavenonis
Antal sider	8
Forlag	Springer
Publikationsdato	2012
Sider	596-603
ISBN (Trykt)	978-3-642-31270-0
ISBN (Elektronisk)	978-3-642-31271-7
DOI	https://doi.org/10.1007/978-3-642-31271-7_77
Status	Udgivet - 2012
Begivenhed	11th International Workshop on Breast Imaging - Philadelphia, PA, USA Varighed: 8 jul. 2012 → 11 jul. 2012 Konferencens nummer: 11

Workshop

Workshop	11th International Workshop on Breast Imaging
Nummer	11
Land/Område	USA
By	Philadelphia, PA
Periode	08/07/2012 → 11/07/2012

Navn	Lecture notes in computer science
Vol/bind	7361
ISSN	0302-9743

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Citationsformater

Karemore, G., Keller, B. M., Oh, H., Tchou, J., Nielsen, M., Conant, E. F., & Kontos, D. (2012). Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation. I A. D. A. Maidment, P. R. Bakic, & S. Gavenonis (red.), Breast Imaging: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings (s. 596-603). Springer. https://doi.org/10.1007/978-3-642-31271-7_77

Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation. / Karemore, Gopal; Keller, Brad M.; Oh, Huen et al.
Breast Imaging: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings. red. / Andrew D. A. Maidment; Predrag R. Bakic; Sara Gavenonis. Springer, 2012. s. 596-603 (Lecture notes in computer science, Bind 7361).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Karemore, G, Keller, BM, Oh, H, Tchou, J, Nielsen, M, Conant, EF & Kontos, D 2012, Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation. i ADA Maidment, PR Bakic & S Gavenonis (red), Breast Imaging: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings. Springer, Lecture notes in computer science, bind 7361, s. 596-603, 11th International Workshop on Breast Imaging, Philadelphia, PA, USA, 08/07/2012. https://doi.org/10.1007/978-3-642-31271-7_77

Karemore G, Keller BM, Oh H, Tchou J, Nielsen M, Conant EF et al. Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation. I Maidment ADA, Bakic PR, Gavenonis S, red., Breast Imaging: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings. Springer. 2012. s. 596-603. (Lecture notes in computer science, Bind 7361). doi: 10.1007/978-3-642-31271-7_77

Karemore, Gopal ; Keller, Brad M. ; Oh, Huen et al. / Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation. Breast Imaging: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012. Proceedings. red. / Andrew D. A. Maidment ; Predrag R. Bakic ; Sara Gavenonis. Springer, 2012. s. 596-603 (Lecture notes in computer science, Bind 7361).

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abstract = "We investigate the potential of mammographic parenchymal texture as a surrogate marker of the risk to develop Estrogen Receptor (ER) sub-type specific breast cancer. A case-control study was performed, including 118 cancer cases stratified by ER receptor status and 354 age-matched controls. Digital mammographic (DM) images were retrospectively collected and analyzed under HIPAA and IRB approval. The performance of the texture features was compared to that of the standard mammographic density measures. We observed that breast percent density PD% and parenchymal texture features can both distinguish between cancer cases and controls (A z > 0.70). However, for ER subtype-specific classification, PD% alone does not provide sufficient classification (A z = 0.60), while texture features have significant classification performance (A z = 0.70). Combining breast density with texture features achieves the best performance (A z = 0.71). These findings suggest that mammographic texture analysis may have value for sub-type specific breast cancer risk assessment.",

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AU - Nielsen, Mads

AU - Conant, Emily F.

AU - Kontos, Despina

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AB - We investigate the potential of mammographic parenchymal texture as a surrogate marker of the risk to develop Estrogen Receptor (ER) sub-type specific breast cancer. A case-control study was performed, including 118 cancer cases stratified by ER receptor status and 354 age-matched controls. Digital mammographic (DM) images were retrospectively collected and analyzed under HIPAA and IRB approval. The performance of the texture features was compared to that of the standard mammographic density measures. We observed that breast percent density PD% and parenchymal texture features can both distinguish between cancer cases and controls (A z > 0.70). However, for ER subtype-specific classification, PD% alone does not provide sufficient classification (A z = 0.60), while texture features have significant classification performance (A z = 0.70). Combining breast density with texture features achieves the best performance (A z = 0.71). These findings suggest that mammographic texture analysis may have value for sub-type specific breast cancer risk assessment.

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Mammographic parenchymal texture analysis for estrogen-receptor subtype specific breast cancer risk estimation

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