Evidence map›Paper›PMID 28763455›Full record

ArticlePloS one2017

Identifying relevant biomarkers of brain injury from structural MRI: Validation using automated approaches in children with unilateral cerebral palsy.

Alex M Pagnozzi, Nicholas Dowson, James Doecke, Simona Fiori, Andrew P Bradley, Roslyn N Boyd, Stephen Rose

Abstract readValidation Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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  5. BMJ open · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Alex M PagnozziCSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.ORCID http://orcid.org/0000-0001-7931-1204
Nicholas DowsonCSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.
James DoeckeCSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.
Simona FioriStella Maris Scientific Institute, Pisa, Italy.
Andrew P BradleyThe School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.
Roslyn N BoydQueensland Cerebral Palsy and Rehabilitation Research Centre, School of Medicine and Science, Centre for Children's Health Research, The University of Queensland, Brisbane, Australia.
Stephen RoseCSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have proposed that the early elucidation of brain injury from structural Magnetic Resonance Images (sMRI) is critical for the clinical assessment of children with cerebral palsy (CP). Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5-17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p<0.008), indicating significant associations with clinical function. The measured prevalence of injury, including ventricular enlargement (70%), white and grey matter lesions (55%) and cortical malformations (30%), were similar to the prevalence observed in other cohorts of children with unilateral CP. These findings support the early characterisation of injury from sMRI into previously defined aetiologies as part of standard clinical assessment. Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships.

Indexed as

AdolescentAutomationBrain InjuriesCerebral PalsyChildChild, PreschoolCohort StudiesFemaleGray MatterHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleReproducibility of ResultsStructure-Activity RelationshipWhite Matter

Identifiers

PMID28763455
PMCPMC5538741

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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.