ArticleAJNR. American journal of neuroradiology2017
Volumetric Analysis from a Harmonized Multisite Brain MRI Study of a Single Subject with Multiple Sclerosis.
Article in AJNR. American journal of neuroradiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 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
75 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Bootstrap approach for meta-synthesis of MRI findings from multiple scanners.Journal of neuroscience methods · 2021Pooled it
- FLAIRNeuroImage. Clinical · 2019Trial
- Proteomic Age Acceleration in Multiple Sclerosis Precedes Symptom Onset and Associates with Severity.medRxiv : the preprint server for health sciences · 2026Article
- Association of Changes in Activity Patterns With Brain Atrophy and Disability Progression in People With Multiple Sclerosis.Neurology · 2026Article
- Radiomics in spinal research: a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Scanner-agnostic MRI harmonization via SSIM-guided disentanglement.Frontiers in artificial intelligence · 2026Article
- MReye-Seg: development and validation of an automated MRI pipeline for standardised ocular and orbital morphometrics.Eye (London, England) · 2025Article
- Calibration of MRI-based reference intervals to new samples.bioRxiv : the preprint server for biology · 2025Article
- Challenges and best practices when using ComBAT to harmonize diffusion MRI data.Scientific reports · 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
- Short-term changes in objectively measured activity predict brain atrophy and disability progression in multiple sclerosis.medRxiv : the preprint server for health sciences · 2025Article
- Image harmonization and de-harmonization based on singular value decomposition (SVD) in medical domain.Quantitative imaging in medicine and surgery · 2025Article
- MAMBA-BASED RESIDUAL GENERATIVE ADVERSARIAL NETWORK FOR FUNCTIONAL CONNECTIVITY HARMONIZATION DURING INFANCY.Proceedings. IEEE International Symposium on Biomedical Imaging · 2025Article
- HeteroMRI: Robust white matter abnormality classification across multi-scanner MRI data.GigaScience · 2025Article
- The role of AI for MRI-analysis in multiple sclerosis-A brief overview.Frontiers in artificial intelligence · 2025Review
- Characterizing Psychiatric Disorders Through Graph Neural Networks: A Functional Connectivity Analysis of Depression and Schizophrenia.Depression and anxiety · 2025Article
- An evaluation of image-based and statistical techniques for harmonizing brain volume measurements.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Topology Assisted Clustering of Temporal fMRI Brain Networks With Use-Case in Mitigating Non-Neural Multi-Site Variability.IEEE access : practical innovations, open solutions · 2025Article
- The impact of image contrast, resolution and reader expertise on black hole identification in Multiple Sclerosis.Neuroradiology · 2024Article
- Acquisition-invariant brain MRI segmentation with informative uncertainties.Medical image analysis · 2024Article
15 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
22 authors.
Funding
Abstract
background and purposeMR imaging can be used to measure structural changes in the brains of individuals with multiple sclerosis and is essential for diagnosis, longitudinal monitoring, and therapy evaluation. The North American Imaging in Multiple Sclerosis Cooperative steering committee developed a uniform high-resolution 3T MR imaging protocol relevant to the quantification of cerebral lesions and atrophy and implemented it at 7 sites across the United States. To assess intersite variability in scan data, we imaged a volunteer with relapsing-remitting MS with a scan-rescan at each site. MATERIALS AND
methodsAll imaging was acquired on Siemens scanners (4 Skyra, 2 Tim Trio, and 1 Verio). Expert segmentations were manually obtained for T1-hypointense and T2 (FLAIR) hyperintense lesions. Several automated lesion-detection and whole-brain, cortical, and deep gray matter volumetric pipelines were applied. Statistical analyses were conducted to assess variability across sites, as well as systematic biases in the volumetric measurements that were site-related.
resultsSystematic biases due to site differences in expert-traced lesion measurements were significant (
conclusionsEven in multicenter studies with consistent scanner field strength and manufacturer after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses.
Indexed as
Identifiers
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.