Meeting Banner
Abstract #2462

An Indirect Echo Compensated Reconstruction Algorithm for T2 Mapping of the Liver from Highly Undersampled Radial FSE Data

Chuan Huang1, 2, Abhishek Pandey3, Tomoe Barr4, Ali Bilgin3, 4, Maria I. Altbach1

1Department of Medical Imaging, University of Arizona, Tucson, AZ, United States; 2Center for Advanced Radiological Sciences, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; 3Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States; 4Biomedical Engineering, University of Arizona, Tucson, AZ, United States

Early detection and classification of hepatic tumors and chronic liver disease are two important clinical problems. T2 mapping has been used to improve the characterization of pathologies in the liver. One promising sequence for fast T2 mapping is radial FSE. Most of the reconstruction methods for undersampled radFSE data do not take into account the effects of indirect echoes; this leads to T2 estimates that are dependent on the refocusing pulse slice profile and/or B1 inhomogeneities. Recently, we proposed a reconstruction algorithm CURLIE (CUrve Reconstruction via pca-based Linearization with Indirect Echo compensation) combines a principal component model-based algorithm with a slice-resolved extended phase graph signal model. In this work, we demonstrate the ability to obtain accurate T2 maps with indirect echo compensated from liver radFSE data acquired in a single breath hold. The algorithm is also evaluated using phantom and in vivo data. It is also shown that this technique is immune to B1 inhomogeneities and B1 mis-calibration.