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Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography.
Chen, David Qixiang; Zhong, Jidan; Chu, Powell P W; Fei Li, Cathy Meng; Hodaie, Mojgan.
Afiliação
  • Chen DQ; Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Zhong J; Krembil Research Institute, University Health Network, Toronto, ON, Canada.
  • Chu PPW; Krembil Research Institute, University Health Network, Toronto, ON, Canada.
  • Fei Li CM; Division of Neurosurgery, Toronto Western Hospital, University of Toronto, ON, Canada.
  • Hodaie M; Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Pain ; 162(2): 361-371, 2021 02 01.
Article em En | MEDLINE | ID: mdl-32701655
ABSTRACT
ABSTRACT Imaging of trigeminal neuralgia (TN) has demonstrated key diffusion tensor imaging-based diffusivity alterations in the trigeminal nerve; however, imaging has primarily focused on the peripheral nerve segment because of previous limitations in reliably segmenting small fiber bundles across multiple subjects. We used Selective Automated Group Integrated Tractography to study 36 subjects with TN (right-sided pain) and 36 sex-matched controls to examine the trigeminal nerve (fifth cranial nerve [CN V]), pontine decussation (TPT), and thalamocortical fibers (S1). Gaussian process classifiers were trained by scrolling a moving window over CN V, TPT, and S1 tractography centroids. Fractional anisotropy (FA), generalized FA, radial diffusivity, axial diffusivity, and mean diffusivity metrics were evaluated for both groups, analyzing TN vs control groups and affected vs unaffected sides. Classifiers that performed at greater-than-or-equal-to 70% accuracy were included. Gaussian process classifier consistently demonstrated bilateral trigeminal changes, differentiating them from controls with an accuracy of 80%. Affected and unaffected sides could be differentiated from each other with 75% accuracy. Bilateral TPT could be distinguished from controls with at least 85% accuracy. TPT left-right classification achieved 98% accuracy. Bilateral S1 could be differentiated from controls, where the affected S1 radial diffusivity classifier achieved 87% accuracy. This is the first TN study that combines group-wise merged tractography, machine learning classification, and analysis of the complete trigeminal pathways from the peripheral fibers to S1 cortex. This analysis demonstrates that TN is characterized by bilateral abnormalities throughout the trigeminal pathway compared with controls and abnormalities between affected and unaffected sides. This full pathway tractography study of TN demonstrates bilateral changes throughout the trigeminal pathway and changes between affected and unaffected sides.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Neuralgia do Trigêmeo Limite: Humans Idioma: En Revista: Pain Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Neuralgia do Trigêmeo Limite: Humans Idioma: En Revista: Pain Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Canadá