Comparison of structural MRI brain measures between 1.5T and 3T: data from the Lothian Birth Cohort 1936
Colin R. Buchanan,
Susana Munoz Maniega,
Maria del Carmen Valdes Hernandez,
Adele M. Taylor,
Tom C Russ,
Elliot M Tucker-Drob,
Joanna M Wardlaw,
Ian J Deary,
Mark E Bastin,
Simon R Cox
Posted 26 Apr 2021
medRxiv DOI: 10.1101/2021.04.23.21256000
Posted 26 Apr 2021
Multi-scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T1-weighted and diffusion MRI (dMRI) structural brain measures between a 1.5T GE Signa Horizon HDx and a 3T Siemens Magnetom Prisma using 91 community-dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6-11% higher and fractional anisotropy was 33% higher at 3T than at 1.5T), between-scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: 0.612-0.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: 0.504-0.763). Between-scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: 0.475-0.564), and the general factors of these tracts provided excellent consistency (ICC > 0.769). Whole-brain structural networks provided good to excellent consistency for global metrics (ICC > 0.612). Although consistency was poor for individual network connections (mean ICCs: 0.275-0.280), this was driven by a large difference in network sparsity (0.599 versus 0.334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: 0.533-0.647). Regression-based k-fold cross-validation showed that, particularly for global volumes, between-scanner differences could be largely eliminated (R2 range 0.615-0.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.
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