Resection of the piriform cortex for temporal lobe epilepsy: a Novel approach on imaging segmentation and surgical application.

Epilepsy surgery imaging piriform cortex segmentation temporal lobe epilepsy

Journal

British journal of neurosurgery
ISSN: 1360-046X
Titre abrégé: Br J Neurosurg
Pays: England
ID NLM: 8800054

Informations de publication

Date de publication:
18 Aug 2021
Historique:
entrez: 18 8 2021
pubmed: 19 8 2021
medline: 19 8 2021
Statut: aheadofprint

Résumé

The piriform cortex (PC) occupies both banks of the endorhinal sulcus and has an important role in the pathophysiology of temporal lobe epilepsy (TLE). A recent study showed that resection of more than 50% of PC increased the odds of becoming seizure free by a factor of 16. We report the feasibility of manual segmentation of PC and application of the Geodesic Information Flows (GIF) algorithm to automated segmentation, to guide resection. Manual segmentation of PC was performed by two blinded independent examiners in 60 patients with TLE (55% Left TLE, 52% female) with a median age of 35 years (IQR, 29-47 years) and 20 controls (60% Women) with a median age of 39.5 years (IQR, 31-49). The GIF algorithm was used to create an automated pipeline for parcellating PC which was used to guide excision as part of temporal lobe resection for TLE. Right PC was larger in patients and controls. Parcellation of PC was used to guide anterior temporal lobe resection, with subsequent seizure freedom and no visual field or language deficit. Reliable segmentation of PC is feasible and can be applied prospectively to guide neurosurgical resection that increases the chances of a good outcome from temporal lobe resection for TLE.

Sections du résumé

BACKGROUND BACKGROUND
The piriform cortex (PC) occupies both banks of the endorhinal sulcus and has an important role in the pathophysiology of temporal lobe epilepsy (TLE). A recent study showed that resection of more than 50% of PC increased the odds of becoming seizure free by a factor of 16.
OBJECTIVE OBJECTIVE
We report the feasibility of manual segmentation of PC and application of the Geodesic Information Flows (GIF) algorithm to automated segmentation, to guide resection.
METHODS METHODS
Manual segmentation of PC was performed by two blinded independent examiners in 60 patients with TLE (55% Left TLE, 52% female) with a median age of 35 years (IQR, 29-47 years) and 20 controls (60% Women) with a median age of 39.5 years (IQR, 31-49). The GIF algorithm was used to create an automated pipeline for parcellating PC which was used to guide excision as part of temporal lobe resection for TLE.
RESULTS RESULTS
Right PC was larger in patients and controls. Parcellation of PC was used to guide anterior temporal lobe resection, with subsequent seizure freedom and no visual field or language deficit.
CONCLUSION CONCLUSIONS
Reliable segmentation of PC is feasible and can be applied prospectively to guide neurosurgical resection that increases the chances of a good outcome from temporal lobe resection for TLE.

Identifiants

pubmed: 34406102
doi: 10.1080/02688697.2021.1966385
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-6

Commentaires et corrections

Type : CommentIn

Auteurs

Jose E Leon-Rojas (JE)

NeurALL Research Group, Medical School, Universidad Internacional del Ecuador, Quito, Ecuador.
UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

Sabahat Iqbal (S)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

Sjoerd B Vos (SB)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.
Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, UK.

Roman Rodionov (R)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

Anna Miserocchi (A)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.

Andrew W McEvoy (AW)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.

Vejay N Vakharia (VN)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.

Laura Mancini (L)

Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

Marian Galovic (M)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.
Department of Neurology, Zurich University Hospital, Zurich, Switzerland.

Rachel E Sparks (RE)

School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK.

Sebastien Ourselin (S)

School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK.

Jorge M Cardoso (JM)

School of Biomedical Engineering and Imaging Sciences, Kings College, St Thomas Hospital, London, UK.

Matthias J Koepp (MJ)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

John S Duncan (JS)

UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.
Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK.

Classifications MeSH