Hybrid referenceless and multibaseline subtraction MR thermometry for monitoring thermal therapies in moving organs.
OBJECTIVE
Magnetic resonance thermometry using the proton resonance frequency (PRF) shift is a promising technique for guiding thermal ablation. For temperature monitoring in moving organs, such as the liver and the heart, problems with motion must be addressed. Multi-baseline subtraction techniques have been proposed, which use a library of baseline images covering the respiratory and cardiac cycle. However, main field shifts due to lung and diaphragm motion can cause large inaccuracies in multi-baseline subtraction. Referenceless thermometry methods based on polynomial phase regression are immune to motion and susceptibility shifts. While referenceless methods can accurately estimate temperature within the organ, in general, the background phase at organ/tissue interfaces requires large polynomial orders to fit, leading to increased danger that the heated region itself will be fitted by the polynomial and thermal dose will be underestimated. In this paper, a hybrid method for PRF thermometry in moving organs is presented that combines the strengths of referenceless and multi-baseline thermometry.


METHODS
The hybrid image model assumes that three sources contribute to image phase during thermal treatment: Background anatomical phase, spatially smooth phase deviations, and focal, heat-induced phase shifts. The new model and temperature estimation algorithm were tested in the heart and liver of normal volunteers, in a moving phantom HIFU heating experiment, and in numerical simulations of thermal ablation. The results were compared to multi-baseline and referenceless methods alone.


RESULTS
The hybrid method allows for in vivo temperature estimation in the liver and the heart with lower temperature uncertainty compared to multi-baseline and referenceless methods. The moving phantom HIFU experiment showed that the method accurately estimates temperature during motion in the presence of smooth main field shifts. Numerical simulations illustrated the method's sensitivity to algorithm parameters and hot spot features.


CONCLUSIONS
This new hybrid method for MR thermometry in moving organs combines the strengths of both multi-baseline subtraction and referenceless thermometry and overcomes their fundamental weaknesses.
Department of Radiology, Stanford University, Stanford, California 94304, USA. wgrissom@gmail.com
William A
WA
Grissom
Viola
V
Rieke
Andrew B
AB
Holbrook
Yoav
Y
Medan
Michael
M
Lustig
Juan
J
Santos
Michael V
MV
McConnell
Kim Butts
KB
Pauly
D000465:Algorithms; D006979:Hyperthermia, Induced / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D013382:Subtraction Technique; D013821:Thermometers; D013997:Time Factors