4.7 Review

Brain imaging in the assessment for epilepsy surgery

Journal

LANCET NEUROLOGY
Volume 15, Issue 4, Pages 420-433

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/S1474-4422(15)00383-X

Keywords

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Funding

  1. Wellcome Trust [WT106882]
  2. National Institute for Health Research
  3. Medical Research Council (MRC) [MR/L013215/1]
  4. MRC [MR/L013215/1, MR/M00841X/1]
  5. Fight for Sight
  6. Henry Smith Charity
  7. EPSRC [EP/M020533/1, NS/A000027/1, EP/K005278/1, EP/J020990/1]
  8. Wolfson Foundation
  9. European Union 7th Framework Programme for Research and Technological Development
  10. National Institute for Health Research University College London Hospitals Biomedical Research Centre
  11. Department of Health
  12. EPSRC [EP/K005278/1, EP/J020990/1, EP/M020533/1] Funding Source: UKRI
  13. MRC [MR/M00841X/1, MR/L013215/1] Funding Source: UKRI
  14. Engineering and Physical Sciences Research Council [EP/J020990/1, EP/K005278/1, EP/M020533/1] Funding Source: researchfish
  15. Medical Research Council [MR/M00841X/1, MR/L013215/1] Funding Source: researchfish

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Brain imaging has a crucial role in the presurgical assessment of patients with epilepsy. Structural imaging reveals most cerebral lesions underlying focal epilepsy. Advances in MRI acquisitions including diffusion-weighted imaging, post-acquisition image processing techniques, and quantification of imaging data are increasing the accuracy of lesion detection. Functional MRI can be used to identify areas of the cortex that are essential for language, motor function, and memory, and tractography can reveal white matter tracts that are vital for these functions, thus reducing the risk of epilepsy surgery causing new morbidities. PET, SPECT, simultaneous EEG and functional MRI, and electrical and magnetic source imaging can be used to infer the localisation of epileptic foci and assist in the design of intracranial EEG recording strategies. Progress in semi-automated methods to register imaging data into a common space is enabling the creation of multimodal three-dimensional patient-specific datasets. These techniques show promise for the demonstration of the complex relations between normal and abnormal structural and functional data and could be used to direct precise intracranial navigation and surgery for individual patients.

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