Autoregressive moving average modeling for spectral parameter estimation from a multigradient echo chemical shift acquisition

作者：Taylor Brian A; Hwang Ken Pin; Hazle John D; Stafford R Jason^*

来源：Medical Physics, 2009, 36(3): 753-764.

DOI：10.1118/1.3075819

• autoregressive moving average processes
• biomedical MRI
• biothermics
• brain
• chemical shift
• image sampling
• iterative methods
• laser applications in medicine
• liver
• medical image processing
• radiation therapy

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 (T(2)(*)), and complex amplitudes of a multipeak system from a limited number of echoes (<= 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 T(2)(*) 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)>= 5 for echo train lengths (ETLs)>= 4 using a fixed echo spacing of 3.3 ms. T(2)(*) 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 >= 4 echoes and for T(2)(*) (< 1.0%) with >= 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 <= 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 similar to 1.6x1.6x4 mm(3) in <= 5 s.

• 出版日期2009-3