Meeting Banner
Abstract #3066

DCE-MRI Analysis using Model-Based Classification Shapes with Non-Negative Least-Squares

Zaki Ahmed 1 and Ives R Levesque 1,2

1 Medical Physics Unit, McGill University, Montreal, Quebec, Canada, 2 Research Institute of the McGill University Health Center, Montreal, Quebec, Canada

We describe a new analysis method for DCE-MRI which is based on shape analysis and uses the Tofts model to define the classification shapes. Non-negative least-squares (NNLS) is used to identify the weight of these shapes in measured data. We apply this method to a dataset of breast cancer patients undergoing neoadjuvant chemotherapy, and show that our method can predict pathologic complete response (pCR) in images from pre-treatment or after one cycle of therapy. Our results also suggest that the method is robust to inaccuracies in the T1 and arterial input function (AIF).

This abstract and the presentation materials are available to members only; a login is required.

Join Here