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Proceedings Paper

Heterogeneity of kinetic curve parameters as indicator for the malignancy of breast lesions in DCE MRI
Author(s): Thomas Buelow; Axel Saalbach; Martin Bergtholdt; Rafael Wiemker; Hans Buurman; Lina Arbash Meinel; Gillian Newstead
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Paper Abstract

Dynamic contrast enhanced Breast MRI (DCE BMRI) has emerged as powerful tool in the diagnostic work-up of breast cancer. While DCE BMRI is very sensitive, specificity remains to be an issue. Consequently, there is a need for features that support the classification of enhancing lesions into benign and malignant lesions. Traditional features include the morphology and the texture of a lesion, as well as the kinetic parameters of the time-intensity curves, i.e., the temporal change of image intensity at a given location. The kinetic parameters include initial contrast uptake of a lesion and the type of the kinetic curve. The curve type is usually assigned to one of three classes: persistent enhancement (Type I), plateau (Type II), and washout (Type III). While these curve types show a correlation with the tumor type (benign or malignant), only a small sub-volume of the lesion is taken into consideration and the curve type will depend on the location of the ROI that was used to generate the kinetic curve. Furthermore, it has been shown that the curve type significantly depends on which MR scanner was used as well as on the scan parameters. Recently, it was shown that the heterogeneity of a given lesion with respect to spatial variation of the kinetic curve type is a clinically significant indicator for malignancy of a tumor. In this work we compare four quantitative measures for the degree of heterogeneity of the signal enhancement ratio in a tumor and evaluate their ability of predicting the dignity of a tumor. All features are shown to have an area under the ROC curve of between 0.63 and 0.78 (for a single feature).

Paper Details

Date Published: 9 March 2010
PDF: 12 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76241H (9 March 2010); doi: 10.1117/12.844365
Show Author Affiliations
Thomas Buelow, Philips Research Hamburg (Germany)
Axel Saalbach, Philips Research Aachen (Germany)
Martin Bergtholdt, Philips Research Hamburg (Germany)
Rafael Wiemker, Philips Research Hamburg (Germany)
Hans Buurman, Philips Healthcare Best (Netherlands)
Lina Arbash Meinel, The Univ. of Chicago Medical Ctr. (United States)
Philips Research (United States)
Gillian Newstead, The Univ. of Chicago Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)

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