Abstract
PurposeTo explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T-1-weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) the effect of vendor-implemented GNL corrections; and (iii) easily applicable methods that can be used to retrospectively correct data.
MethodsA multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T-1-weighted protocol without GNL-distortion correction. Two healthy subjects and a phantom were additionally scanned at a single site with varying table positions. The 2D and 3D vendor-implemented GNL-correction algorithms and retrospective methods based on (i) phantom data fit, (ii) normalization with C2 vertebral body diameters, and (iii) the Jacobian determinant of nonlinear registrations to a template were tested.
ResultsDepending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T-1-weighted scans when no distortion corrections were used. The 3D vendor-implemented correction methods and the three proposed methods reduced this variability to less than 3%.
ConclusionsOur results raise awareness of the significant impact that GNL can have on quantitative UCCA studies, and point the way to prospectively and retrospectively managing GNL distortions in a variety of settings, including clinical environments. Magn Reson Med 79:1595-1601, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.
