Meeting Banner
Abstract #4087

Comparison of Logan Plot Analysis and Nested Model Selection Technique for MR Estimation of Distribution Volume in Human Brain Tumor at 3Tesla

Hassan Bagher-Ebadian 1,2 , James R Ewing 2,3 , Siamak P. Nejad-Davarani 4,5 , Hamed Moradi 6 , Reza Faghihi 6 , Rajan Jain 7 , Tom Mikkelsen 8 , Lisa Scarpace 8 , and Hamid Soltanian-Zadeh 1,9

1 Radiology, Henry Ford Hospital, Detroit, MI, United States, 2 Physics, Oakland University, Rochester, MI, United States, 3 Neurology, Henry Ford Hospital, MI, United States, 4 Neurology, Henry Ford Hospital, Detroit, MI, United States, 5 Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 6 Mechanical Engineering, Shiraz University, Fars, Iran, 7 Radiology, NYU Langone Medical Center, NY, United States, 8 Neurosurgery, Henry Ford Hospital, Detroit, MI, United States, 9 CIPCE, ECE Dept., University of Tehran, Tehran, Iran

In this study, Logan plot analysis was applied to dynamic-contrast-enhanced MRI data of 15 patients with Glioblastoma-Multiforme to estimate the tumor distribution volume (VD). BDS (W.A.Brock, W.Dechert and J.Scheinkman) statistic was used to identify the equilibrium condition of the Logan curve. Nested-Model-Selection (NMS) technique was also applied to the same dataset. Results confirm that the VD values estimated by the two techniques are quite in agreement (0.946,p<0.001) while there is considerable variation between subjects in both methods (VD:5% to 46% in Logan-plot with mean and STD of VD=0.23%0.13% and 7% to 53% in NMS with mean and STD of VD=0.27%0.14%).

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

Join Here