ArticleNature communications2024
Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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
31 citing papers in PubMed.
- Feasibility and Tolerability of Performing Portable MRI for Neurological Disorders in an Outpatient Neurology Clinic: A Prospective Cohort.Annals of clinical and translational neurology · 2026Article
- Net zero emission MR imaging using a permanent 0.4 T magnet.Magma (New York, N.Y.) · 2026Article
- Ultra-low-field MRI for bedside imaging of severe multiple sclerosis.Journal of neurology · 2026Article
- The potential of low-field MRI for global dementia care.Nature reviews. Neurology · 2026Review
- From Low Field to High Value: Robust Cortical Mapping From Low-Field MRI.Human brain mapping · 2026Article
- BrainTwin-AI: A Multimodal MRI-EEG-Based Cognitive Digital Twin for Real-Time Brain Health Intelligence.Brain sciences · 2026Article
- On the accuracy of image registration in portable low-field 3D brain MRI.Research square · 2026Article
- Ultra-low fieldCommunications chemistry · 2026Article
- Portable Low-Field Magnetic Resonance Imaging in People With Human Immunodeficiency Virus.Annals of clinical and translational neurology · 2026Article
- On the accuracy of image registration in portable low-field 3D brain MRI.bioRxiv : the preprint server for biology · 2026Article
- Clinical translation of fluid, imaging, and digital biomarkers for Alzheimer's disease.Alzheimer's research & therapy · 2026Review
- Detecting patterns of atrophy in cognitively impaired individuals using portable, low-field MRI.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Brain-age in ultra-low-field MRI: How well does it work?Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Investigating the binding potential of the Melissa officinalis oil against Alzheimer's targets by molecular docking and in vitro evaluations.Scientific reports · 2025Article
- Ultra-low-field MRI: a David versus Goliath challenge in modern imaging.La Radiologia medica · 2025Review
- Low-field and portable MRI technology: advancements and innovations.European radiology experimental · 2025Review
- Predicting White Matter Hyperintensity: Leveraging Portable MRI for Accessible Brain Health Screening.AJNR. American journal of neuroradiology · 2025Article
- Translating lifestyle interventions for optimal brain health in Africa.Nature reviews. Neurology · 2025Review
- Mechanisms of interventions targeting modifiable factors for dementia risk reduction.Molecular neurodegeneration · 2025Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-noise ratio. Here, we optimize LF-MRI acquisition and develop a freely available machine learning pipeline to quantify brain morphometry and white matter hyperintensities (WMH). We validate the pipeline and apply it to outpatients presenting with mild cognitive impairment or dementia due to AD. We find hippocampal volumes from ≤ 3 mm isotropic LF-MRI scans have agreement with conventional MRI and are more accurate than anisotropic counterparts. We also show WMH volume has agreement between manual segmentation and the automated pipeline. The increased availability and reduced cost of LF-MRI, in combination with our machine learning pipeline, has the potential to increase access to neuroimaging for dementia.
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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.