Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils.
Measures of structural brain change based on longitudinal MR imaging are increasingly important but can be degraded by intensity non-uniformity. This non-uniformity can be more pronounced at higher field strengths, or when using multichannel receiver coils. We assessed the ability of the non-parametric non-uniform intensity normalization (N3) technique to correct non-uniformity in 72 volumetric brain MR scans from the preparatory phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Normal elderly subjects (n=18) were scanned on different 3-T scanners with a multichannel phased array receiver coil at baseline, using magnetization prepared rapid gradient echo (MP-RAGE) and spoiled gradient echo (SPGR) pulse sequences, and again 2 weeks later. When applying N3, we used five brain masks of varying accuracy and four spline smoothing distances (d=50, 100, 150 and 200 mm) to ascertain which combination of parameters optimally reduces the non-uniformity. We used the normalized white matter intensity variance (standard deviation/mean) to ascertain quantitatively the correction for a single scan; we used the variance of the normalized difference image to assess quantitatively the consistency of the correction over time from registered scan pairs. Our results showed statistically significant (p<0.01) improvement in uniformity for individual scans and reduction in the normalized difference image variance when using masks that identified distinct brain tissue classes, and when using smaller spline smoothing distances (e.g., 50-100 mm) for both MP-RAGE and SPGR pulse sequences. These optimized settings may assist future large-scale studies where 3-T scanners and phased array receiver coils are used, such as ADNI, so that intensity non-uniformity does not influence the power of MR imaging to detect disease progression and the factors that influence it.
Dementia Research Centre, Institute of Neurology, Box 16, University College London, Queen Square, London, UK. r.boyes@ucl.ac.uk
Richard G
RG
Boyes
Jeff L
JL
Gunter
Chris
C
Frost
Andrew L
AL
Janke
Thomas
T
Yeatman
Derek L G
DL
Hill
Matt A
MA
Bernstein
Paul M
PM
Thompson
Michael W
MW
Weiner
Norbert
N
Schuff
Gene E
GE
Alexander
Ronald J
RJ
Killiany
Charles
C
DeCarli
Clifford R
CR
Jack
Nick C
NC
Fox
D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000473:pathology; D002138:Calibration; D003072:Cognition Disorders / Q000473:pathology; D003627:Data Interpretation, Statistical; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D015203:Reproducibility of Results