Keyhole Dixon method for faster, perceptually equivalent fat suppression.
OBJECTIVE
To reduce the acquisition time associated with the two-point Dixon fat suppression technique by combining a keyhole in-phase (Water + Fat) k-space data set with a full out-of-phase (Water - Fat) k-space data set and optimizing the keyhole size with a perceptual difference model.


METHODS
A set of keyhole Dixon images was created by varying the number of lines in the keyhole data set. Off-resonance correction was incorporated into the image reconstruction process to improve the homogeneity of the fat suppression. A perceptual difference model (PDM) was validated with human observer experiments and used to compare the keyhole images to images from a full two-point Dixon acquisition. The PDM was used to determine the smallest keyhole width required to obtain perceptual equivalence to images obtained from the full two-point Dixon method.


RESULTS
In experimental phantom studies, the keyhole Dixon image reconstructed from 96 of 192 Water + Fat k-space lines and 192 Water - Fat k-space lines was perceptually equivalent to the full (192 + 192) two-point Dixon images, resulting in a 25% reduction in scan time. Clinical images of a volunteer's knee, orbits, and abdomen created from the smallest, perceptually equivalent keyhole width resulted in a 27%-38% reduction in total scan time.


CONCLUSIONS
This method improves the temporal efficiency of the conventional two-point Dixon technique and may prove especially useful for high-field systems where specific absorption rate (SAR) limits will constrain radiofrequency (RF)-based fat suppression techniques.
Flask
Chris A
CA
Case Western Reserve University and University Hospitals of Cleveland, Department of Radiology, Ohio 44106, USA.
Salem
Kyle A
KA
Moriguchi
Hisamoto
H
Lewin
Jonathan S
JS
Wilson
David L
DL
Duerk
Jeffrey L
JL
D000273:Adipose Tissue; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging