ReviewPolish journal of radiology2025
Quantitative brain volumetry in neurological disorders: from disease mechanisms to software solutions.
Review in Polish journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Longitudinal MRI studies of children with attention-deficit/hyperactivity disorder: A systematic review.Psychiatry and clinical neurosciences · 2026Pooled it
- Structural and social determinants of health shape the impact of neurodegeneration and cerebrovascular pathology on cognitive functioning in black adults.Social science & medicine (1982) · 2026Article
- Age-Related Volumetric Changes of the Posterior Cranial Fossa and its Structures in Stroke Patients.Cerebellum (London, England) · 2026Article
- Reliability and diagnostic performance of an automated MRI-based classifier compared with radiologists in Alzheimer's disease.Frontiers in neuroinformatics · 2026Article
- Ultra-High Resolution 9.4T Brain MRI Segmentation via a Newly Engineered Multi-Scale Residual Nested U-Net with Gated Attention.Bioengineering (Basel, Switzerland) · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative magnetic resonance imaging (MRI) volumetry has become a pivotal component in modern neurology, bridging the gap between detailed neuroimaging and clinical decision-making. By employing advanced imaging techniques like 3D T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) sequences, MRI volumetry enables clinicians to objectively quantify brain volume changes associated with neurological conditions such as Alzheimer's disease, multiple sclerosis, epilepsy, and myotonic dystrophy. Automated segmentation tools, including FreeSurfer, NeuroQuant, volBrain, and AccuBrain, facilitate precise and reproducible analysis of structural brain changes, contributing significantly to early diagnosis, patient monitoring, and therapeutic planning. In Alzheimer's disease, volumetric MRI enables the detection of early hippocampal and temporal lobe atrophy, providing a crucial biomarker for diagnosis and monitoring disease progression. Similarly, in multiple sclerosis, volumetric analyses quantify grey and white matter degeneration, reflecting motor and cognitive impairment severity. Moreover, quantitative MRI techniques precisely delineate structural abnormalities like hippocampal sclerosis and focal cortical dysplasia in epilepsy, crucial for accurate surgical intervention. Ongoing advances in artificial intelligence and machine learning are set to further enhance these volumetric approaches, addressing current limitations such as inter-observer variability and expanding their clinical applicability. This review outlines the existing landscape and future trajectory of quantitative MRI volumetry, underscoring its expanding role in clinical neurology and personalised medicine.
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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.