Combining atlas-based parcellation of regional brain data acquired across scanners at 1.5T and 3.0T field strengths

• Published in: NeuroImage (Orlando, Fla.) Vol. 60; no. 2; pp. 940 - 951
• Main Authors: Pfefferbaum, Adolf, Rohlfing, Torsten, Rosenbloom, Margaret J., Sullivan, Edith V.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 02.04.2012; Elsevier Limited
• Subjects: Aging; Agreements; Atlas-based parcellation; Automation; Brain; Confidence intervals; Field strength; FreeSurfer; HIV; Human immunodeficiency virus; Image registration; Longitudinal; Medical imaging; MRI; NMR; Nuclear magnetic resonance; Scanners; SRI24; Studies; Field strength; Atlas-based parcellation; Brain; Image registration; Longitudinal; MRI; SRI24; FreeSurfer
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2012.01.092

Longitudinal brain morphometric studies designed for data acquisition at a single MRI field strength can be seriously limited by system replacements from lower to higher field strength. Merging data across field strengths has not been endorsed for a variety of reasons, yet the ability to combine such data would broaden longitudinal investigations. To determine whether structural T1-weighted MRI data acquired across MR field strengths could be merged, parcellations of archival SPGR data acquired in 114 individuals at 1.5T and at 3.0T within 3weeks of each other were compared. The first set of analyses examined 1) the correspondence between regional tissue volumes derived from data collected at 1.5T and 3.0T and 2) whether there were systematic differences for which a correction factor could be determined and applied to improve measurement agreement. Comparability of regional volume determination at 1.5T and 3.0T was assessed with intraclass correlation (ICC) computed on volumes derived from the automated and unsupervised SRI24 atlas registration and parcellation method. A second set of analyses measured the reliability of the registration and quantification using the same approach on longitudinal data acquired in 69 healthy adults at a single field strength, 1.5T, at an interval <2years. The mainstay of the analyses was based on the SRI24 method; to examine the potential of merging data across field strengths and across image analysis packages, a secondary set of analyses used FreeSurfer instead of the SRI24 method. For both methods, a regression-based linear correction function significantly improved correspondence. The results indicated high correspondence between most selected cortical, subcortical, and CSF-filled spaces; correspondence was lowest in the globus pallidus, a region rich in iron, which in turn has a considerable field-dependent effect on signal intensity. Thus, the application of a regression-based correction function that improved the correspondence in regional volume estimations argues well for the proposition that selected T1-weighted regional anatomical brain data can be reliably combined across 1.5T and 3.0T field strengths with the application of an appropriate correction procedure. ► SPGR data acquired in 114 adults at 1.5T and 3T were registered, parcellated, and merged. ► Regression-based correction functions improved correspondence in volume estimations across field strengths. ► Selected regional SPGR data can be combined across field strengths and analysis packages with appropriate correction procedures.