Evidence map›Paper›PMID 28123950›Full record

ArticleNeuroImage. Clinical2017

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy.

Sophie Adler, Konrad Wagstyl, Roxana Gunny, Lisa Ronan, David Carmichael, J Helen Cross, Paul C Fletcher, Torsten Baldeweg

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 3 pooled it
7.7field-weighted citation impact, top 2% of its field
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

52 citing papers in PubMed, 3 syntheses or guidelines pooled it, 121 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Sophie AdlerDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Great Ormond Street Hospital for Children, London, UK.
Konrad WagstylDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Brain Mapping Unit, Institute of Psychiatry, University of Cambridge, UK.
Roxana GunnyGreat Ormond Street Hospital for Children, London, UK.
Lisa RonanBrain Mapping Unit, Institute of Psychiatry, University of Cambridge, UK.
David CarmichaelDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Great Ormond Street Hospital for Children, London, UK.
J Helen CrossDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Great Ormond Street Hospital for Children, London, UK.
Paul C FletcherBrain Mapping Unit, Institute of Psychiatry, University of Cambridge, UK; Cambridge & Peterborough NHS Foundation Trust, Cambridgeshire, UK.
Torsten BaldewegDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK; Great Ormond Street Hospital for Children, London, UK.
University College London · GBUniversity of Cambridge · GBGreat Ormond Street Hospital · GB

Funding

Medical Research Council G0300117Medical Research Council G1002276Wellcome Trust WT095692MA
6 · The paper itself

Abstract

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.

Indexed as

Brain MappingAdolescentArea Under CurveCerebral CortexChildChild, PreschoolEpilepsyFemaleHumansImaging, Three-DimensionalMachine LearningMagnetic Resonance ImagingMaleMalformations of Cortical Development, Group IOxygenOxygenAUC, area under the curveAutomated classificationFCDFCD, focal cortical dysplasiaFLAIR, fluid-attenuated inversion recoveryIntractable epilepsyLCD, local cortical deformationLGI, local gyrification indexPaediatricPCA, principal component analysisROC, receiver operator characteristicStructural MRI

Identifiers

PMID28123950
PMCPMC5222951
OpenAlexW2567150859

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.