Validation of semi‐automated anatomically labeled SEEG contacts in a brain atlas for mapping connectivity in focal epilepsy. Issue 3 (15th May 2021)

• Record Type: Journal Article
• Authors: Taylor, Kenneth N.; Joshi, Anand A.; Hirfanoglu, Tugba; Grinenko, Olesya; Liu, Ping; Wang, Xiaofeng; Gonzalez‐Martinez, Jorge A.; Leahy, Richard M.; Mosher, John C.; Nair, Dileep R.
• Is Part Of: Epilepsia open. Volume 6:Issue 3(2021)
• Page Start: 493
• Page End: 503
• Publication Date: 2021-05-15
• Subjects: anatomical labeling -- epilepsy -- SEEG; Epilepsy -- Periodicals; Epilepsy -- Research -- Periodicals; Epilepsy; Periodicals; Fulltext; Internet Resources; Periodicals; 616.853005
• DOI: 10.1002/epi4.12499
• Languages: English
• ISSNs: 2470-9239

Abstract

Abstract: Objective: Stereotactic electroencephalography (SEEG) has been widely used to explore the epileptic network and localize the epileptic zone in patients with medically intractable epilepsy. Accurate anatomical labeling of SEEG electrode contacts is critically important for correctly interpreting epileptic activity. We present a method for automatically assigning anatomical labels to SEEG electrode contacts using a 3D‐segmented cortex and coregistered postoperative CT images. Method: Stereotactic electroencephalography electrode contacts were spatially localized relative to the brain volume using a standard clinical procedure. Each contact was then assigned an anatomical label by clinical epilepsy fellows. Separately, each contact was automatically labeled by coregistering the subject's MRI to the USCBrain atlas using the BrainSuite software and assigning labels from the atlas based on contact locations. The results of both labeling methods were then compared, and a subsequent vetting of the anatomical labels was performed by expert review. Results: Anatomical labeling agreement between the two methods for over 17 000 SEEG contacts was 82%. This agreement was consistent in patients with and without previous surgery ( P = .852). Expert review of contacts in disagreement between the two methods resulted in agreement with the atlas based over manual labels in 48% of cases, agreement with manual over atlas‐based labels in 36% of cases, and disagreement with both methods in 16% of cases. Labels deemed incorrect by the expert review were then categorized as either in a region directly adjacent to the correct label or as a gross error, revealing a lower likelihood of gross error from the automated method. Significance: The method for semi‐automated atlas‐based anatomical labeling we describe here demonstrates potential to assist clinical workflow by reducing both analysis time and the likelihood of gross anatomical error. Additionally, it provides a convenient means of intersubject analysis by standardizing the anatomical labels applied to SEEG contact locations across subjects.