Autoregressive moving average modeling for spectral parameter estimation from a multigradient echo chemical shift acquisition.
The authors investigated the performance of the iterative Steiglitz-McBride (SM) algorithm on an autoregressive moving average (ARMA) model of signals from a fast, sparsely sampled, multiecho, chemical shift imaging (CSI) acquisition using simulation, phantom, ex vivo, and in vivo experiments with a focus on its potential usage in magnetic resonance (MR)-guided interventions. The ARMA signal model facilitated a rapid calculation of the chemical shift, apparent spin-spin relaxation time (T2*), and complex amplitudes of a multipeak system from a limited number of echoes (< or equal 16). Numerical simulations of one- and two-peak systems were used to assess the accuracy and uncertainty in the calculated spectral parameters as a function of acquisition and tissue parameters. The measured uncertainties from simulation were compared to the theoretical Cramer-Rao lower bound (CRLB) for the acquisition. Measurements made in phantoms were used to validate the T2* estimates and to validate uncertainty estimates made from the CRLB. We demonstrated application to real-time MR-guided interventions ex vivo by using the technique to monitor a percutaneous ethanol injection into a bovine liver and in vivo to monitor a laser-induced thermal therapy treatment in a canine brain. Simulation results showed that the chemical shift and amplitude uncertainties reached their respective CRLB at a signal-to-noise ratio (SNR) > or =5 for echo train lengths (ETLs) > or =4 using a fixed echo spacing of 3.3 ms. T2* estimates from the signal model possessed higher uncertainties but reached the CRLB at larger SNRs and/or ETLs. Highly accurate estimates for the chemical shift (<0.01 ppm) and amplitude (<1.0%) were obtained with > or =4 echoes and for T2*(<1.0%) with > or =7 echoes. We conclude that, over a reasonable range of SNR, the SM algorithm is a robust estimator of spectral parameters from fast CSI acquisitions that acquire < or =16 echoes for one- and two-peak systems. Preliminary ex vivo and in vivo experiments corroborated the results from simulation experiments and further indicate the potential of this technique for MR-guided interventional procedures with high spatiotemporal resolution approximately 1.6 x 1.6 x 4 mm3 in < or =5 s.
Taylor
Brian A
BA
Department of Imaging Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030, USA. jstafford@mdanderson.org
Hwang
Ken-Pin
KP
Hazle
John D
JD
Stafford
R Jason
RJ
D000818:Animals; D055592:Biophysical Phenomena; D001921:Brain / Q000473:pathology; D004285:Dogs; D006358:Hot Temperature / Q000627:therapeutic use; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data; D066298:In Vitro Techniques; D053685:Laser Therapy / Q000706:statistics & numerical data; D008099:Liver / Q000187:drug effects / Q000473:pathology; D053783:Magnetic Resonance Imaging, Interventional / Q000706:statistics & numerical data*; D015233:Models, Statistical; D019047:Phantoms, Imaging; D012044:Regression Analysis; D013696:Temperature