ArticleBMJ open2025
Systematic protocol to identify 'clinical controls' for paediatric neuroimaging research from clinically acquired brain MRIs.
Article in BMJ open, 2025. 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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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.
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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.
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Who cites it
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
- Brain charts for neuroanatomical sex differences across the human lifespan.bioRxiv : the preprint server for biology · 2026Article
- Charting Brain Structure in 22q11.2 Deletion Syndrome with Clinical Neuroimaging.medRxiv : the preprint server for health sciences · 2026Article
- White Matter Bundle Reconstruction From Single-Shell Diffusion Magnetic Resonance Imaging: Test-Retest Reliability and Predictive Capability Across Orientation Distribution Function Reconstruction Methods.Human brain mapping · 2025Article
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23 authors.
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Abstract
introductionProgress at the intersection of artificial intelligence and paediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and generalisable models. Retrospective analysis of clinical brain MRI scans offers a promising avenue to augment prospective research datasets, leveraging the extensive repositories of scans routinely acquired by hospital systems in the course of clinical care. Here, we present a systematic protocol for identifying 'scans with limited imaging pathology' through machine-assisted manual review of radiology reports. METHODS AND ANALYSIS: The protocol employs a standardised grading scheme developed with expert neuroradiologists and implemented by non-clinician graders. Categorising scans based on the presence or absence of significant pathology and image quality concerns facilitates the repurposing of clinical brain MRI data for brain research. Such an approach has the potential to harness vast clinical imaging archives-exemplified by over 250 000 brain MRIs at the Children's Hospital of Philadelphia-to address demographic biases in research participation, to increase sample size and to improve replicability in neurodevelopmental imaging research. Ultimately, this protocol aims to enable scalable, reliable identification of clinical control brain MRIs, supporting large-scale, generalisable neuroimaging studies of typical brain development and neurogenetic conditions. ETHICS AND DISSEMINATION: Studies using datasets generated from this protocol will be disseminated in peer-reviewed journals and at academic conferences.
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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 Socratic graph.