TY - JOUR
T1 - Optimal decay rate constant estimates from phased array data utilizing joint Bayesian analysis
AU - Quirk, James D.
AU - Sukstanskii, Alexander L.
AU - Bretthorst, G. Larry
AU - Yablonskiy, Dmitriy A.
N1 - Funding Information:
This work was supported by NIH Grants R01HL70037 and P30NS048056.
PY - 2009/5
Y1 - 2009/5
N2 - Since their initial description, phased array coils have become increasingly popular due to their ease of customization for various applications. Numerous methods for combining data from individual channels have been proposed that attempt to optimize the SNR of the resultant images. One issue that has received comparatively little attention is how to apply these combination techniques to a series of images obtained from phased array coils that are then analyzed to produce quantitative estimates of tissue parameters. Herein, instead of the typical goal of maximizing the SNR in a single image, we are interested in maximizing the accuracy and precision of parameter estimates that are obtained from a series of such images. Our results demonstrate that a joint Bayesian analysis offers a "worry free" method for obtaining optimal parameter estimates from data generated by multiple coils (channels) from a single object (source). We also compare the properties of common channel combination techniques under different conditions to the results obtained from the joint Bayesian analysis. If the noise variance is constant for all channels, a sensitivity weighted average provides parameter estimates equivalent to the joint analysis. If both the noise variance and signal intensity are similar in all channels, a simple channel average gives an adequate result. However, if the noise variance differs between channels, an "ideal weighted" approach should be applied, where data are combined after weighting by the channel amplitude divided by the noise variance. Only this "ideal weighting" provides results similar to the automatic-weighting inherent in the joint Bayesian approach.
AB - Since their initial description, phased array coils have become increasingly popular due to their ease of customization for various applications. Numerous methods for combining data from individual channels have been proposed that attempt to optimize the SNR of the resultant images. One issue that has received comparatively little attention is how to apply these combination techniques to a series of images obtained from phased array coils that are then analyzed to produce quantitative estimates of tissue parameters. Herein, instead of the typical goal of maximizing the SNR in a single image, we are interested in maximizing the accuracy and precision of parameter estimates that are obtained from a series of such images. Our results demonstrate that a joint Bayesian analysis offers a "worry free" method for obtaining optimal parameter estimates from data generated by multiple coils (channels) from a single object (source). We also compare the properties of common channel combination techniques under different conditions to the results obtained from the joint Bayesian analysis. If the noise variance is constant for all channels, a sensitivity weighted average provides parameter estimates equivalent to the joint analysis. If both the noise variance and signal intensity are similar in all channels, a simple channel average gives an adequate result. However, if the noise variance differs between channels, an "ideal weighted" approach should be applied, where data are combined after weighting by the channel amplitude divided by the noise variance. Only this "ideal weighting" provides results similar to the automatic-weighting inherent in the joint Bayesian approach.
KW - Bayesian probability theory
KW - Exponential parameter estimation
KW - Magnetic resonance
KW - Magnetic resonance imaging
KW - Phased array coil
UR - http://www.scopus.com/inward/record.url?scp=63349084535&partnerID=8YFLogxK
U2 - 10.1016/j.jmr.2009.01.001
DO - 10.1016/j.jmr.2009.01.001
M3 - Article
C2 - 19181549
AN - SCOPUS:63349084535
SN - 1090-7807
VL - 198
SP - 49
EP - 56
JO - Journal of Magnetic Resonance
JF - Journal of Magnetic Resonance
IS - 1
ER -