Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T₁-weighted brain MRI acquisitions

Purpose: To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T₁-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. Methods: A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T₁-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. Results: Depending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T₁-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%. Conclusions: Our 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.