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Abstract #0414

Automated Arterial Input Function Detection in Ascending Aorta for Breast DCE-MRI

Venkata Veerendranadh Chebrolu 1 , Dattesh D Shanbhag 1 , Sheshadri Thiruvenkadam 1 , Sandeep Kaushik 1 , Uday Patil 1 , Patrice Hervo 2 , Sandeep N Gupta 3 , and Rakesh Mullick 4

1 Medical Image Analysis Lab, GE Global Research, Bangalore, Karnataka, India, 2 GE Healthcare, Buc, France, 3 Biomedical Image Processing Lab, GE Global Research, Niskayuna, NY, United States, 4 Diagnostics and Biomedical Technologies, GE Global Research, Bangalore, Karnataka, India

DCE-MRI and pharmacokinetic (pK) model parameters derived from the DCE data have been commonly used for characterizing tumor vascular properties quantitatively. The accuracy of pK parameters depends on the choice of arterial input function (AIF). Partial volume effects due to horizontal course of the axillary artery in the axial plane, motion from pulsation and breathing may reduce the accuracy of the AIF selected from the axillary arteries. In this work we demonstrate a completely automated method for detection of AIF in the ascending aorta for breast DCE MRI and compare the results with AIF manually selected by an experienced radiologist.

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