Literature DB >> 31323635

Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia.

Matthew S Willsey1, Kelly L Collins1,2, Erin C Conrad1,3, Heather A Chubb4, Parag G Patil1.   

Abstract

OBJECTIVE: Trigeminal neuralgia (TN) is an uncommon idiopathic facial pain syndrome. To assist in diagnosis, treatment, and research, TN is often classified as type 1 (TN1) when pain is primarily paroxysmal and episodic or type 2 (TN2) when pain is primarily constant in character. Recently, diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN. In this study, the authors explored the differences in DTI parameters between subcategories of TN, specifically TN1 and TN2, in the pontine segment of the trigeminal tract.
METHODS: The authors enrolled 8 patients with unilateral TN1, 7 patients with unilateral TN2, and 23 asymptomatic controls. Patients underwent DTI with parameter measurements in a region of interest within the pontine segment of the trigeminal tract. DTI parameters were compared between groups.
RESULTS: In the pontine segment, the radial diffusivity (p = 0.0049) and apparent diffusion coefficient (p = 0.023) values in TN1 patients were increased compared to the values in TN2 patients and controls. The DTI measures in TN2 were not statistically significant from those in controls. When comparing the symptomatic to asymptomatic sides in TN1 patients, radial diffusivity was increased (p = 0.025) and fractional anisotropy was decreased (p = 0.044) in the symptomatic sides. The apparent diffusion coefficient was increased, with a trend toward statistical significance (p = 0.066).
CONCLUSIONS: Noninvasive DTI analysis of patients with TN may lead to improved diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients.

Entities:  

Keywords:  AD = axial diffusivity; ADC = apparent diffusion coefficient; AUC = area under the curve; DTI = diffusion tensor imaging; FA = fractional anisotropy; MANOVA = multivariate ANOVA; RD = radial diffusivity; REZ = root entry zone; ROC = receiver operating characteristic; ROI = region of interest; TN = trigeminal neuralgia; TN1 = TN type 1; TN2 = TN type 2; diffusion tensor imaging; facial pain; trigeminal neuralgia

Year:  2019        PMID: 31323635     DOI: 10.3171/2019.4.JNS19299

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  3 in total

1.  Brainstem trigeminal fiber microstructural abnormalities are associated with treatment response across subtypes of trigeminal neuralgia.

Authors:  Sarasa Tohyama; Matthew R Walker; Jia Y Zhang; Joshua C Cheng; Mojgan Hodaie
Journal:  Pain       Date:  2021-06-01       Impact factor: 6.961

2.  MRI Texture Analysis Reveals Brain Abnormalities in Medically Refractory Trigeminal Neuralgia.

Authors:  Hayden Danyluk; Abdullah Ishaque; Daniel Ta; Yee Hong Yang; B Matthew Wheatley; Sanjay Kalra; Tejas Sankar
Journal:  Front Neurol       Date:  2021-02-12       Impact factor: 4.003

3.  Trigeminal Nerve White Matter Fiber Abnormalities in Primary Trigeminal Neuralgia: A Diffusion Spectrum Imaging Study.

Authors:  Si-Ping Luo; Fan-Fan Chen; Han-Wen Zhang; Fan Lin; Guo-Dong Huang; Yi Lei
Journal:  Front Neurol       Date:  2022-01-20       Impact factor: 4.003

  3 in total

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