Neuroimaging for patient selection for medial temporal lobe epilepsy surgery: Part 1 Structural neuroimaging

Petros Stylianou*, Chen Hoffmann, Ilan Blat, Sagi Harnof

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

The objective of part one of this review is to present the structural neuroimaging techniques that are currently used to evaluate patients with temporal lobe epilepsy (TLE), and to discuss their potential to define patient eligibility for medial temporal lobe surgery. A PubMed query, using Medline and Embase, and subsequent review, was performed for all English language studies published after 1990, reporting neuroimaging methods for the evaluation of patients with TLE. The extracted data included demographic variables, population and study design, imaging methods, gold standard methods, imaging findings, surgical outcomes and conclusions. Overall, 56 papers were reviewed, including a total of 1517 patients. This review highlights the following structural neuroimaging techniques: MRI, diffusion-weighted imaging, tractography, electroencephalography and magnetoencephalography. The developments in neuroimaging during the last decades have led to remarkable improvements in surgical precision, postsurgical outcome, prognosis, and the rate of seizure control in patients with TLE. The use of multiple imaging methods provides improved outcomes, and further improvements will be possible with future studies of larger patient cohorts.

Original languageEnglish
Pages (from-to)14-22
Number of pages9
JournalJournal of Clinical Neuroscience
Volume23
DOIs
StatePublished - 1 Jan 2016
Externally publishedYes

Keywords

  • Neuroimaging
  • Patient selection
  • Structural neuroimaging
  • Surgical candidates
  • Temporal lobe epilepsy
  • Temporal lobe surgery

Fingerprint

Dive into the research topics of 'Neuroimaging for patient selection for medial temporal lobe epilepsy surgery: Part 1 Structural neuroimaging'. Together they form a unique fingerprint.

Cite this