ArticleJournal of neuroimaging : official journal of the American Society of Neuroimaging2020
Standardized Brain MRI Acquisition Protocols Improve Statistical Power in Multicenter Quantitative Morphometry Studies.
Article in Journal of neuroimaging : official journal of the American Society of Neuroimaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of the impact of type 2 diabetes on brain cortical thickness.Frontiers in dementia · 2024Pooled it
- Revealing the Neuroimaging Mechanism of Acupuncture for Poststroke Aphasia: A Systematic Review.Neural plasticity · 2022Pooled it
- Evaluating the task-specificity model of verbal memory: Regional volumetric analyses in temporal lobe epilepsy with hippocampal sclerosis.Epilepsia open · 2026Article
- Mitigating the Impact of MR Sequence Parameters: Increasing the Robustness of DL-Based Cortical Thickness Estimates.Human brain mapping · 2026Article
- Harmonization in magnetic resonance imaging: A survey of acquisition, image-level, and feature-level methods.Medical image analysis · 2026Review
- Global Socioeconomic Context and Brain Ageing in Epilepsy: an ENIGMA-Epilepsy study.medRxiv : the preprint server for health sciences · 2026Article
- On the translational potential of atlases in precision oncology.Translational cancer research · 2025Review
- An open-source repository-based tool for quality control of imaging protocol compliance: demonstration in a multicentre MRI study.The British journal of radiology · 2025Article
- Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA.Neuroinformatics · 2024Article
- Modeling the impact of MRI acquisition bias on structural connectomes: Harmonizing structural connectomes.Network neuroscience (Cambridge, Mass.) · 2024Article
- Motor cortex functional connectivity is associated with underlying neurochemistry in ALS.Journal of neurology, neurosurgery, and psychiatry · 2023Article
- Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set.Human brain mapping · 2023Article
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Authors and funding
5 authors.
Funding
Abstract
background and purposeIn this study, we used power analysis to calculate required sample sizes to detect group-level changes in quantitative neuroanatomical estimates derived from MRI scans obtained from multiple imaging centers. Sample size estimates were derived from (i) standardized 3T image acquisition protocols and (ii) nonstandardized clinically acquired images obtained at both 1.5 and 3T as part of the multicenter Human Epilepsy Project. Sample size estimates were compared to assess the benefit of standardizing acquisition protocols.
methodsCortical thickness, hippocampal volume, and whole brain volume were estimated from whole brain T1-weighted MRI scans processed using Freesurfer v6.0. Sample sizes required to detect a range of effect sizes were calculated using (i) standard t-test based power analysis methods and (ii) a nonparametric bootstrap approach.
resultsA total of 32 participants were included in our analyses, aged 29.9 ± 12.62 years. Standard deviation estimates were lower for all quantitative neuroanatomical metrics when assessed using standardized protocols. Required sample sizes per group to detect a given effect size were markedly reduced when using standardized protocols, particularly for cortical thickness changes <.2 mm and hippocampal volume changes <10%.
conclusionsThe use of standardized protocols yielded up to a five-fold reduction in required sample sizes to detect disease-related neuroanatomical changes, and is particularly beneficial for detecting subtle effects. Standardizing image acquisition protocols across scanners prior to commencing a study is a valuable approach to increase the statistical power of multicenter MRI studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.