Evidence map›Paper›PMID 28130467›Full record

ArticleNeurology2017

Multimodal MRI profiling of focal cortical dysplasia type II.

Seok-Jun Hong, Boris C Bernhardt, Benoit Caldairou, Jeffery A Hall, Marie C Guiot, Dewi Schrader, Neda Bernasconi, Andrea Bernasconi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Seok-Jun HongFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Boris C BernhardtFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Benoit CaldairouFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Jeffery A HallFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Marie C GuiotFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Dewi SchraderFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Neda BernasconiFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada.
Andrea BernasconiFrom the Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital (S.-J.H., B.C.B., B.C., J.A.H., M.C.G., N.B., A.B.), Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre (S.-J.H., B.C.B., B.C., D.S., N.B., A.B.), and Department of Pathology (M.C.G.), McGill University, Montreal, Canada. andrea@bic.mni.mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo characterize in vivo MRI signatures of focal cortical dysplasia (FCD) type IIA and type IIB through combined analysis of morphology, intensity, microstructure, and function.

methodsWe carried out a multimodal 3T MRI profiling of 33 histologically proven FCD type IIA (9) and IIB (24) lesions. A multisurface approach operating on manual consensus labels systematically sampled intracortical and subcortical lesional features. Geodesic distance mapping quantified the same features in the lesion perimeter. Logistic regression assessed the relationship between MRI and histology, while supervised pattern learning was used for individualized subtype prediction.

resultsFCD type IIB was characterized by abnormal morphology, intensity, diffusivity, and function across all surfaces, while type IIA lesions presented only with increased fluid-attenuated inversion recovery signal and reduced diffusion anisotropy close to the gray-white matter interface. Similar to lesional patterns, perilesional anomalies were more marked in type IIB extending up to 16 mm. Structural MRI markers correlated with categorical histologic characteristics. A profile-based classifier predicted FCD subtypes with equal sensitivity of 85%, while maintaining a high specificity of 94% against healthy and disease controls.

conclusionsImage processing applied to widely available MRI contrasts has the ability to dissociate FCD subtypes at a mesoscopic level. Integrating in vivo staging of pathologic traits with automated lesion detection is likely to provide an objective definition of lesional boundary and assist emerging approaches, such as minimally invasive thermal ablation, which do not supply tissue specimen.

Indexed as

Image Interpretation, Computer-AssistedMagnetic Resonance ImagingMultimodal ImagingAdultBrainDiagnosis, DifferentialDrug Resistant EpilepsyEpilepsyFemaleFollow-Up StudiesGray MatterHumansLogistic ModelsMaleMalformations of Cortical Development, Group IPattern Recognition, Automated

Identifiers

PMID28130467
PMCPMC5344077

What OpenQuestion holds

Textmetadata
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.