ArticleRadiology. Artificial intelligence2026
Reference Trajectories of Extra-Axial Cerebrospinal Fluid during Childhood and Adolescence Defined in a Clinically Acquired MRI Dataset.
Article in Radiology. Artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Normative modeling for quantitative brain MRI phenotyping and biomarker discovery for pediatric leukodystrophies.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Systematic protocol to identify 'clinical controls' for paediatric neuroimaging research from clinically acquired brain MRIs.BMJ open · 2025Article
- A systematic protocol to identify "clinical controls" for pediatric neuroimaging research from clinically acquired brain MRIs.bioRxiv : the preprint server for biology · 2025Article
- Charting structural brain asymmetry across the human lifespan.bioRxiv : the preprint server for biology · 2025Article
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Abstract
Purpose To build extra-axial cerebrospinal fluid (eaCSF) growth charts that define key diagnostic criteria for benign enlargement of the subarachnoid space (BESS) by providing an age-related reference benchmark to aid in assessing atypical eaCSF development. Materials and Methods In this retrospective study, T1-weighted MRI scans from patients who underwent imaging at a pediatric health care system between January 2004 and December 2023 were accessed to form a clinical control group. Nine scans from patients diagnosed with BESS by a board-certified pediatric neuroradiologist were also reviewed. T1-weighted scans were segmented into various tissue types, including eaCSF. Growth charts of eaCSF were modeled using the clinical control group. The results of patients with confirmed BESS were then benchmarked against these charts to test the performance of the eaCSF growth charts. Generalized additive models of location, scale, and shape were used. Results The eaCSF measurements were obtained for 1205 patients (619 female; age range, 0.19-19.6 years). Measurements show that eaCSF evolved dynamically with age, steadily decreasing from birth to 2 years, then trending upward in childhood. Seven of the nine patients with a clinical diagnosis of BESS had eaCSF measurements above the 97.5th percentile for at least one measurement. Percentile scores distinguished patients with BESS from controls with areas under the receiver operating characteristic curve of greater than 0.95. Conclusion MRI-derived eaCSF measurements evolved dynamically throughout early life. Patients with atypical CSF development could be differentiated from clinical controls using computational measurements paired with normative modeling.
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