ReviewBrain & spine2025
Closing the diagnostic gap: A narrative review of recent advances in functional MRI diagnostics in spinal cord injury.
Review in Brain & spine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Emerging advances in spinal cord injury: An introductory overview.Brain & spine · 2025Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Conventional MRI (T1 and T2-weighted sequences) is the standard for diagnosing spinal cord injuries but often lacks specificity, showing limited correlation with microstructural changes and function. This creates a diagnostic gap, especially in patients with mild or ambiguous symptoms, delaying early intervention. Research question: Can advanced MRI techniques-such as quantitative MRI (qMRI), functional MRI (fMRI), Magnetic Resonance Spectroscopy (MRS), and Transmagnetic Stimulation (TMS)-address the limitations of conventional MRI by providing enhanced diagnostic metrics and biomarkers of spinal cord integrity? Material and methods: This study reviews advanced MRI modalities and their potential to provide quantifiable insights into spinal cord microstructure and function. It also explores the role of artificial intelligence (AI) in analyzing complex datasets to support more comprehensive diagnostics. Results: Advanced MRI techniques show promise in improving diagnostic accuracy and enabling individualized prognostic assessments. Parameters specific to each modality could serve as biomarkers for injury extent and neurological recovery, supporting their potential as clinical endpoints in therapy trials. Discussion and conclusion: These advanced imaging techniques, combined with AI for data integration, offer a transformative potential for personalized diagnostics in spinal cord injury. Yet, significant technical and validation challenges remain, requiring large, multicenter studies to confirm their effectiveness and enable clinical application. Successfully addressing these challenges could close the diagnostic gap, optimize patient outcomes, and redefine spinal cord injury management.
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.