Nico Papinutto, Rohit Bakshi, Antje Bischof, Peter A. Calabresi, Eduardo Caverzasi, R. Todd Constable, Esha Datta, Gina Kirkish, Govind Nair, Jiwon Oh, Daniel Pelletier, Dzung L. Pham, Daniel S. Reich, William Rooney, Snehashis Roy, Daniel Schwartz, Russell T. Shinohara, Nancy L. Sicotte, William A. Stern, Ian Tagge, Shahamat Tauhid, Subhash Tummala, Roland G. Henry, for the North American Imaging in Multiple Sclerosis Cooperative

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. 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. 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%. 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, 2017. © 2017 International Society for Magnetic Resonance in Medicine.