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

ABSTRACT: 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. © 2017 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Papinutto N

PROVIDER: S-EPMC6175276 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T<sub>1</sub> -weighted brain MRI acquisitions.

Papinutto Nico N Bakshi Rohit R Bischof Antje A Calabresi Peter A PA Caverzasi Eduardo E Constable R Todd RT Datta Esha E Kirkish Gina G Nair Govind G Oh Jiwon J Pelletier Daniel D Pham Dzung L DL Reich Daniel S DS Rooney William W Roy Snehashis S Schwartz Daniel D Shinohara Russell T RT Sicotte Nancy L NL Stern William A WA Tagge Ian I Tauhid Shahamat S Tummala Subhash S Henry Roland G RG

Magnetic resonance in medicine 20170615 3

<h4>Purpose</h4>To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T<sub>1</sub> -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.<h4>Methods</h4>A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T<sub>1</sub> -weighted protocol wi ...[more]

PMID: 28617996

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Project description:IntroductionAtrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking.MethodsFive methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3?T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3?T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations.ResultsIn dataset A, MUCCA differed between MR machines (p?<?0.001) and methods (p?<?0.001) used, but not between scan sessions. With respect to MUCCA values, Xinapse JIM showed the highest within-scanner reproducibility (ICC absolute agreement?=?0.995) while Xinapse JIM and SCT-PropSeg showed the highest between-scanner robustness (ICC consistency?=?0.981 and 0.976, respectively). Reproducibility of segmentations between scan sessions was highest in Xinapse JIM and SCT-PropSeg segmentations (median SI???0.921), with a significant main effect of method (p?<?0.001), but not of MR machine or subject group. In dataset B, SI with manual outlines did not differ between patients with or without cervical lesions for any of the segmentation methods (p?>?0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p?<?0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement?=?0.940 and median SI?=?0.962).ConclusionAlthough MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance.

Dataset Information

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

Publications

Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T<sub>1</sub> -weighted brain MRI acquisitions.

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