Evidence map›Paper›PMID 40548097›Full record

ReviewEpilepsy currents2025

Imaging Epilepsy: Past, Passing, and to Come.

William H Theodore, Sara K Inati, Sophie Adler, Philip L Pearl, Carrie R Mcdonald

Abstract readReview
In one paragraph

Review in Epilepsy currents, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

William H TheodoreNational Institutes of Health, Bethesda, MD, USA.ORCID https://orcid.org/0000-0002-4669-5747
Sara K InatiNational Institutes of Health, Bethesda, MD, USA.
Sophie AdlerDevelopmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, UK.
Philip L PearlHarvard Medical School, Boston, MA, USA.
Carrie R McdonaldDepartment of Radiation Medicine and Applied Sciences & Psychiatry, University of California, San Diego, CA, USA.ORCID https://orcid.org/0000-0002-0721-5640

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New imaging techniques appearing over the last few decades have replaced procedures that were uncomfortable, of low specificity, and prone to adverse events. While computed tomography remains useful for imaging patients with seizures in acute settings, structural magnetic resonance imaging (MRI) has become the most important imaging modality for epilepsy evaluation, with adjunctive functional imaging also increasingly well established in presurgical evaluation, including positron emission tomography (PET), single photon ictal-interictal subtraction computed tomography co-registered to MRI and functional MRI for preoperative cognitive mapping. Neuroimaging in inherited metabolic epilepsies is integral to diagnosis, monitoring, and assessment of treatment response. Neurotransmitter receptor PET and magnetic resonance spectroscopy can help delineate the pathophysiology of these disorders. Machine learning and artificial intelligence analyses based on large MRI datasets composed of healthy volunteers and people with epilepsy have been initiated to detect lesions that are not found visually, particularly focal cortical dysplasia. These methods, not yet approved for patient care, depend on careful clinical correlation and training sets that fully sample broad populations.

Indexed as

artificial intelligencegenetic epilepsy syndromesimage processingimaging

Identifiers

PMID40548097
PMCPMC12176802

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.