ArticleNeuroImage2010
Impact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort.
Article in NeuroImage, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
88 citing papers in PubMed, 1 synthesis or guideline pooled it, 172 citations in OpenAlex.
- Accuracy of MRI-Based Radiomics in Diagnosis of Placenta Accreta Spectrum: A PRISMA Systematic Review and Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2024Pooled it
- Boosting power for clinical trials using classifiers based on multiple biomarkers.Neurobiology of aging · 2010Trial
- Characterizing the MRI signature of hippocampal sclerosis of aging.Alzheimer's research & therapy · 2026Article
- Mitigating the Impact of MR Sequence Parameters: Increasing the Robustness of DL-Based Cortical Thickness Estimates.Human brain mapping · 2026Article
- ComBat-Predict Enhances Generalizability of Neuroimaging Models to New Sites.Human brain mapping · 2026Article
- Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals.Nature communications · 2026Article
- Comparison of observed image quality and technical image quality parameters in 3D-FLAIR images.Magma (New York, N.Y.) · 2026Article
- Magnetic resonance imaging volumetry in atypical parkinsonism: current evidence and neuroradiological perspectives.Frontiers in aging neuroscience · 2026Review
- Brain Volumetric Changes Post-COVID-19: A Systematic Review.Brain sciences · 2025Review
- Automatic detection of simulated artifacts on T1w magnetic resonance images: comparing performance of different QC strategies.medRxiv : the preprint server for health sciences · 2025Article
- Easy-to-use and easy-to-interpret quality control of 3D gradient echo T1-weighted MR acquisition sequences for improved test-retest stability of MRI-based hippocampus volumetry.Journal of Alzheimer's disease : JAD · 2025Article
- gammaSTAR: A framework for the development of dynamic, real-time capable MR sequences.Magnetic resonance in medicine · 2025Article
- Analysis of Factors Affecting Quality in Structural Magnetic Resonance Images.Human brain mapping · 2025Article
- 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
- Visual rating of brain atrophy in structural MRI: Is its time over?European radiology · 2025Article
- Cross-Modality Image Translation of 3 Tesla Magnetic Resonance Imaging to 7 Tesla Using Generative Adversarial Networks.Human brain mapping · 2025Article
- A generalist model for enhancing brain MRIs.Nature biomedical engineering · 2025Article
- Article
- Optimizing ultra-rapid compressed-sensing MPRAGE acquisitions for brain morphometry.Frontiers in neuroimaging · 2025Article
- BrainSuite BIDS App: Containerized Workflows for MRI Analysis.bioRxiv : the preprint server for biology · 2024Article
28 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Morphometry of brain structures based on magnetic resonance imaging (MRI) data has become an important tool in neurobiology. Recent multicenter studies in neurodegenerative diseases raised the issue of the precision of volumetric measures, and their dependence on the scanner properties and imaging protocol. A large dataset consisting of 1073 MRI examinations in 843 subjects, acquired on 90 scanners at 58 sites, is analyzed here. A comprehensive set of image quality and content measures is used to describe the influence of the scanner hardware and imaging protocol on the variability of morphometric measures. Scanners equipped with array coils show a remarkable advantage over conventional coils in terms of image quality measures. The signal- and contrast-to-noise ratio in similar systems is equal or slightly better at 1.5 T than 3.0 T, while the white/grey matter tissue contrast is generally better on high-field systems. Repeated MRI investigations on the same scanner were available in 41 subjects, on different scanners in 172 subjects. The retest reliability of repeated volumetric measures under the same conditions was found as sufficient to track changes in longitudinal examinations in individual subjects. Using different acquisition conditions in the same subject, however, the variance of volumetric measures was up to 10 times greater. Two likely factors explaining this finding are scanner-dependent geometrical inaccuracies and differences in the white/grey matter tissue contrast.
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What OpenQuestion holds
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.