Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936
| Autor: | Joanna M. Wardlaw, Susana Muñoz Maniega, Maria del C. Valdés Hernández, Colin R. Buchanan, Lucia Ballerini, Elliot M. Tucker-Drob, Gayle Barclay, Adele M. Taylor, Mark E. Bastin, Tom C. Russ, Ian J. Deary, Simon R. Cox |
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| Rok vydání: | 2021 |
| Předmět: |
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Intraclass correlation brain Neuroimaging multi‐site 050105 experimental psychology White matter Cohort Studies diffusion MRI 03 medical and health sciences 0302 clinical medicine Consistency (statistics) Fractional anisotropy medicine Humans 0501 psychology and cognitive sciences Radiology Nuclear Medicine and imaging Mri brain Research Articles structural MRI Mathematics Aged 80 and over reliability Radiological and Ultrasound Technology business.industry 05 social sciences connectome Magnetic Resonance Imaging Regression medicine.anatomical_structure Neurology Scotland Connectome Birth Cohort Female Neurology (clinical) Anatomy Nuclear medicine business 030217 neurology & neurosurgery Diffusion MRI Research Article |
| Zdroj: | Human Brain Mapping Buchanan, C R, Muñoz Maniega, S, Valdés Hernández, M C, Ballerini, L, Barclay, G, Taylor, A M, Russ, T C, Tucker-drob, E M, Wardlaw, J M, Deary, I J, Bastin, M E & Cox, S R 2021, ' Comparison of structural MRI brain measures between 1.5 and 3T: Data from the Lothian Birth Cohort 1936 ', Human Brain Mapping, pp. 3905-3921 . https://doi.org/10.1002/hbm.25473 |
| ISSN: | 1097-0193 |
| DOI: | 10.1002/hbm.25473 |
| Popis: | 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 1.5 T GE Signa Horizon HDx and a 3 T 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 [FA] was 33% higher at 3 T than at 1.5 T), between‐scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612–.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504–.763). Between‐scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475–.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole‐brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275−.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533–.647). Regression‐based k‐fold cross‐validation showed that, particularly for global volumes, between‐scanner differences could be largely eliminated (R 2 range .615–.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. In this comprehensive analysis, we compared T1‐weighted and diffusion MRI structural brain measures between a 1.5 and 3 T scanner using 91 participants (aged 82 years). We found that large‐scale brain structures (whole‐brain, ventricular and tissue volumes; global diffusion MRI measures; and global network metrics) can be reliably matched between these scanners, but caution is warranted when combining regional measures from different scanners. |
| Databáze: | OpenAIRE |
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