ReviewNature protocols2025
Versatile MRI acquisition and processing protocol for population-based neuroimaging.
Review in Nature protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Blood-derived microRNA signatures associated with hippocampal structure and atrophy rate: findings from the Rhineland Study.Molecular psychiatry · 2026Article
- Effects of Physical Activity on Brain White Matter Integrity Are Region-, Dose-, and Age-Dependent: Findings From the Population-Based Rhineland Study.Aging cell · 2026Article
- Olfactory Bulb Volume Reflects Olfactory Dysfunction and Network Organization: Insights From the Population-Based Rhineland Study.International forum of allergy & rhinology · 2026Article
- Tandem repeat polymorphisms are associated with brain structure: results of two large population-based studies.Genome medicine · 2026Article
- Regression Is All You Need for Medical Image Translation.IEEE transactions on medical imaging · 2026Article
- Plasma complex lipids in relation to cortical thickness and brain volumes: results from the population-based Rhineland study.Lipids in health and disease · 2026Article
- Sex-specific relations of ceramides and white matter hyperintensities in the Rhineland study.Scientific reports · 2025Article
- Rapid prospective motion correction using free induction decay and stationary field probe navigators at 7T.Magnetic resonance in medicine · 2025Article
- Enhancing consistency in brain imaging research for population neuroimaging.Nature protocols · 2025Article
- The insula represents a key neurobiological pain hub in psoriatic arthritis.Arthritis research & therapy · 2025Article
- Neuropathology determines whether brain systems segregation benefits cognitive performance.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- FastSurfer-CC: A robust, accurate, and comprehensive framework for corpus callosum morphometry.Imaging neuroscience (Cambridge, Mass.)Article
- Learning-based segmentation of diffusion-weighted MR images with arbitraryImaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Neuroimaging has an essential role in studies of brain health and of cerebrovascular and neurodegenerative diseases, requiring the availability of versatile magnetic resonance imaging (MRI) acquisition and processing protocols. We designed and developed a multipurpose high-resolution MRI protocol for large-scale and long-term population neuroimaging studies that includes structural, diffusion-weighted and functional MRI modalities. This modular protocol takes almost 1 h of scan time and is, apart from a concluding abdominal scan, entirely dedicated to the brain. The protocol links the acquisition of an extensive set of MRI contrasts directly to the corresponding fully automated data processing pipelines and to the required quality assurance of the MRI data and of the image-derived phenotypes. Since its successful implementation in the population-based Rhineland Study (ongoing, currently more than 11,000 participants, target participant number of 20,000), the proposed MRI protocol has proved suitable for epidemiological and clinical cross-sectional and longitudinal studies, including multisite studies. The approach requires expertise in magnetic resonance image acquisition, in computer science for the data management and the execution of processing pipelines, and in brain anatomy for the quality assessment of the MRI data. The protocol takes ~1 h of MRI acquisition and ~20 h of data processing to complete for a single dataset, but parallelization over multiple datasets using high-performance computing resources reduces the processing time. By making the protocol, MRI sequences and pipelines available, we aim to contribute to better comparability, interoperability and reusability of large-scale neuroimaging data.
Indexed as
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Registered trials
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.