ArticleFrontiers in neuroscience2025
Automatic brain quantification in children with unilateral cerebral palsy.
Article in Frontiers in neuroscience, 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.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Assessing brain damage in children with spastic unilateral cerebral palsy (uCP) is challenging, particularly in clinical settings. In this study, we developed and validated a deep learning-based pipeline to automatically quantify lesion-free brain volumes. Using T1-weighted and FLAIR MRI data from 35 patients (aged 5-15 years), we trained models to segment brain structures and lesions, utilizing an automatic label generation workflow. Validation was performed on 54 children with CP (aged 7-16 years) using quantitative and qualitative metrics, as well as an independent dataset of 36 children with congenital or acquired brain anatomy distortions (aged 1-17 years). Clinical evaluation examined the correlation of lesion-free volumes with visual-based assessments of lesion extent and motor and visual outcomes. The models achieved robust segmentation performance in brains with severe anatomical alterations and heterogeneous lesion appearances, identifying reduced volumes in the affected hemisphere, which correlated with lesion extent (
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.