PET/MRI in the Presurgical Evaluation of Patients with Epilepsy: A Concordance Analysis

Katalin Borbély1, Miklós Emri2,3, István Kenessey4,5

  • 1PET/CT Outpatient Department, National Institute of Oncology, H1122 Budapest, Hungary.

Biomedicines
|May 28, 2022
PubMed

Insights

Hybrid [18F]-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (PET/MRI) improves clinical decisions for epilepsy patients with conflicting data. A new concordance model enhances surgical eligibility classification, aiding presurgical evaluation.

Area of Science:

  • Neurology
  • Medical Imaging
  • Nuclear Medicine

Background:

  • Epilepsy management often faces challenges with discordant electroclinical and MRI findings.
  • Presurgical evaluation for epilepsy requires accurate diagnostic tools to guide treatment decisions.

Purpose of the Study:

  • To assess the clinical impact of hybrid [18F]-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]-FDG PET/MRI) on decision-making workflows for epilepsy patients.
  • To introduce a novel mathematical model for clinical concordance calculation to aid in patient subgroup classification.

Main Methods:

  • A prospective study involving 59 epileptic patients with discordant clinical/diagnostic results or MRI negativity.
  • Comparison of [18F]-FDG PET/MRI diagnostic value against electroclinical data, PET, and MRI in presurgical evaluation.
  • Application of a novel data fusion and concordance analysis technique.

Main Results:

  • Hybrid [18F]-FDG PET/MRI demonstrated relevance within the presurgical diagnostic algorithm for epilepsy.
  • The developed concordance analysis model shows potential for more accurate classification of patients for invasive procedures.
  • Statistical analysis supported the utility of the data fusion technique for clinical decision support.

Conclusions:

  • Hybrid [18F]-FDG PET/MRI offers advantages over MRI and electroclinical data in presurgical epilepsy evaluation.
  • Concordance analysis is crucial for refining clinical and surgical decision-making in epilepsy management.
  • The novel model may lead to more precise patient stratification for interventions.

Related Concept Videos