Application of Sequential Thresholding-Based Automated Reconstruction of the Trigeminal Nerve in Trigeminal Neuralgia.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
Jan 2024
Historique:
received: 13 10 2023
accepted: 20 10 2023
medline: 18 1 2024
pubmed: 28 10 2023
entrez: 27 10 2023
Statut: ppublish

Résumé

High-resolution magnetic resonance imaging (MRI) of the trigeminal nerve is indispensable for workup of trigeminal neuralgia (TN) before microvascular decompression; however, the evaluation is often subjective and prone to variability. We aim to develop and assess sequential thresholding-based automated reconstruction of the trigeminal nerve (STAR-TN) as an algorithm for segmenting the trigeminal nerve and contacting structures that will allow for a structured method for assessing neurovascular conflict. A total of 42 patients with TN who underwent high-resolution MRI before microvascular decompression in 2022 were included in our study. Segmentation of the trigeminal nerve and contacting structures was performed on preoperative MRI scans using STAR-TN. The segmentations were then evaluated for neurovascular conflict and compared to the preoperative radiology and operative notes. Geometric features, including the area of contact and distance to conflict, were extracted. Of the 42 patients, 32 (76.2%) were found to show neurovascular conflict based solely on their STAR-TN segmentations and 10 (23.8%) were found to not show neurovascular conflict. Compared with the intraoperative findings, this resulted in a sensitivity of 78.0% and specificity of 100%. In contrast, assessments of neurovascular conflict by radiologists using only 2-dimensional MRI views had a sensitivity of 68.3% and specificity of 100%. Of the 32 patients with neurovascular conflict, 29 (90.9%) had conflict within the root entry zone. Overall, the patients had a median area of contact of 10.66 mm STAR-TN allows for 3-dimensional visualization and identification of neurovascular conflict with improved sensitivity compared with neuroradiologist assessments from MRI slices.

Identifiants

pubmed: 37890771
pii: S1878-8750(23)01501-2
doi: 10.1016/j.wneu.2023.10.095
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e567-e577

Subventions

Organisme : NIGMS NIH HHS
ID : T32 GM136577
Pays : United States

Informations de copyright

Copyright © 2023 Elsevier Inc. All rights reserved.

Auteurs

Michael E Xie (ME)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Kyra Halbert-Elliott (K)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Sumil K Nair (SK)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Judy Huang (J)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Vivek S Yedavalli (VS)

Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Chetan Bettegowda (C)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Risheng Xu (R)

Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address: rxu4@jhmi.edu.

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