Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 461

The DOI matches its Crossref record.

Imaging and epilepsy

Duncan, J.·1997·Brain

Abstract

MRI has been applied to the investigation of epilepsy for 12 years. The principle role of MRI is in the definition of structural abnormalities that underly seizure disorders. Hippocampal sclerosis may be reliably identified, quantitative studies are useful for research and, in equivocal cases, for clinical purposes. A range of malformations of cortical development (MCD) may be determined. In patients with refractory partial seizures who are candidates for surgical treatment, a relevant abnormality is identifiable using MRI in 85%, it is likely that subtle MCD or gliosis accounts for the majority of the remainder. The proportion of cryptogenic cases will decrease with improvements in MRI hardware, signal acquisition techniques and post-processing methodologies. Functional MRI is used to identify the cerebral areas that are responsible for specific cognitive processes, and is of importance in planning resections close to eloquent cortical areas. Magnetic resonance spectroscopy (MRS) provides a means of investigating cerebral metabolites and some neurotransmitters, non-invasively. The concentrations of N-acetyl-aspartate (NAA), creatine and choline-containing compounds may be estimated using proton MRS. Reduction of the ratio of NAA/(creatine+choline) is a feature of cerebral regions that include epileptic foci. Cerebral concentrations of GABA and glutamate, and the effects of antiepileptic drugs on these, may be estimated. Concentrations of high energy phosphate compounds, inorganic phosphate and pH may be assessed using 31P-MRS. In general, epileptic foci are associated with an increase in pH, increased inorganic phosphate and decreased phosphate monoesters. Carbon-13 spectroscopy promises to be a useful method for investigating cerebral metabolism in vivo. PET may provide data on regional cerebral blood flow (rCBF), glucose metabolism and the binding of specific ligands to receptors. Correlation of functional and structural imaging data is necessary for adequate interpretation. The hallmark of an epileptic focus is an area of reduced glucose metabolism, identified using [18F]fluorodeoxyglucose (18FDG), that is commonly more extensive than the underlying anatomical abnormality. The clinical role of 18FDG-PET requires re-evaluation in the light of the advances in structural imaging with MRI. Specific ligands are used to investigate specific receptors. Benzodiazepine and opioid receptors have been studied most. Reduced benzodiazepine receptor binding is commonly seen at an epileptic focus, in a more restricted distribution than an area of hypometabolism. Focal increases and decreases in benzodiazepine receptor binding have been demonstrated in MCD in areas that appear normal on MRI, indicating the widespread nature of the abnormalities. It has been found that mu-opioid receptors are increased in temporal neocortex overlying mesial temporal epileptic foci. Dynamic studies of ligand-receptor binding are possible using PET, for example the release of cerebral endogenous opioids has been implied at the time of serial absences. The main use of single photon emission computed tomography (SPECT) is to produce images reflecting rCBF. Interictal studies alone are not reliable. A strength of SPECT is the ability to obtain images related to rCBF at the time of seizures. Concomitant video-EEG recording is necessary. Ictal scans need to be considered in comparison with an interictal scan and an MRI. Interpretation must be cautious, but may yield data that is useful in the investigation of patients for possible surgical treatment.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/brain/120.2.339

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 461

Metadata

Authors
Duncan, J.
Venue
Brain
Published
1997-02-01
Volume
120
Issue
2
Pages
339-377
ISSN
  • 0006-8950 (ISSN-L)
  • 1460-2156
OpenAlex
W2137989635
Cited by
461
References
0
FWCI
16.32
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Imaging and epilepsy. https://app.cochat.ai/papers/10.1093/brain/120.2.339
The paper
Duncan, J. (1997). Imaging and epilepsy. Brain. https://doi.org/10.1093/brain/120.2.339

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.