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MRI Texture Analysis Reveals Brain Abnormalities in Medically Refractory Trigeminal Neuralgia.
Danyluk, Hayden; Ishaque, Abdullah; Ta, Daniel; Yang, Yee Hong; Wheatley, B Matthew; Kalra, Sanjay; Sankar, Tejas.
Afiliación
  • Danyluk H; Division of Surgical Research, Department of Surgery, University of Alberta, Edmonton, AB, Canada.
  • Ishaque A; Division of Neurosurgery, Department of Surgery, University of Alberta Hospital, University of Alberta, Edmonton, AB, Canada.
  • Ta D; Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
  • Yang YH; Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
  • Wheatley BM; Department of Computing Science, University of Alberta, Edmonton, AB, Canada.
  • Kalra S; Division of Neurosurgery, Department of Surgery, University of Alberta Hospital, University of Alberta, Edmonton, AB, Canada.
  • Sankar T; Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
Front Neurol ; 12: 626504, 2021.
Article en En | MEDLINE | ID: mdl-33643203
ABSTRACT

Background:

Several neuroimaging studies report structural alterations of the trigeminal nerve in trigeminal neuralgia (TN). Less attention has been paid to structural brain changes occurring in TN, even though such changes can influence the development and response to treatment of other headache and chronic pain conditions. The purpose of this study was to apply a novel neuroimaging technique-texture analysis-to identify structural brain differences between classical TN patients and healthy subjects.

Methods:

We prospectively recruited 14 medically refractory classical TN patients and 20 healthy subjects. 3-Tesla T1-weighted brain MRI scans were acquired in all participants. Three texture features (autocorrelation, contrast, energy) were calculated within four a priori brain regions of interest (anterior cingulate, insula, thalamus, brainstem). Voxel-wise analysis was used to identify clusters of texture difference between TN patients and healthy subjects within regions of interest (p < 0.001, cluster size >20 voxels). Median raw texture values within clusters were also compared between groups, and further used to differentiate TN patients from healthy subjects (receiver-operator characteristic curve analysis). Median raw texture values were correlated with pain severity (visual analog scale, 1-100) and illness duration.

Results:

Several clusters of texture difference were observed between TN patients and healthy

subjects:

right-sided TN patients showed reduced autocorrelation in the left brainstem, increased contrast in the left brainstem and right anterior insula, and reduced energy in right and left anterior cingulate, right midbrain, and left brainstem. Within-cluster median raw texture values also differed between TN patients and healthy

subjects:

TN patients could be segregated from healthy subjects using brainstem autocorrelation (p = 0.0040, AUC = 0.84, sensitivity = 89%, specificity = 70%), anterior insula contrast (p = 0.0002, AUC = 0.92, sensitivity = 78%, specificity = 100%), and anterior cingulate energy (p = 0.0004, AUC = 0.92, sensitivity = 78%, specificity = 100%). Additionally, anterior insula contrast and duration of TN were inversely correlated (p = 0.030, Spearman r = -0.73).

Conclusions:

Texture analysis reveals distinct brain abnormalities in TN, which relate to clinical features such as duration of illness. These findings further implicate structural brain changes in the development and maintenance of TN.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neurol Año: 2021 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neurol Año: 2021 Tipo del documento: Article País de afiliación: Canadá