Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

Ge, Xuming; Wang, Luoyu; Pan, Lei; Ye, Haiqi; Zhu, Xiaofen; Feng, Qianjin; Ding, Zhongxiang

doi:10.3389/fneur.2022.862973

Cited by 10 publications

(7 citation statements)

References 32 publications

(36 reference statements)

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“…Wilcoxon test was performed on the rad-score for detecting AD and aMCI in the train and test sets, respectively. As recommended in previous study ( Ge et al, 2022 ), P < 0.05 was considered to be statistically significant in accordance with statistical conventions. The area under the curve (AUC) of the training and test set was used to assess the discriminative accuracy of the Rad-score.…”

Section: Methodsmentioning

confidence: 87%

Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Wang

Feng

et al. 2022

Front. Neurosci.

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BackgroundTextural features of the hippocampus in structural magnetic resonance imaging (sMRI) images can serve as potential diagnostic biomarkers for Alzheimer’s disease (AD), while exhibiting a relatively poor discriminant performance in detecting early AD, such as amnestic mild cognitive impairment (aMCI). In contrast to sMRI, functional magnetic resonance imaging (fMRI) can identify brain functional abnormalities in the early stages of cerebral disorders. However, whether the textural features reflecting local functional activity in the hippocampus can improve the diagnostic performance for AD and aMCI remains unclear. In this study, we combined the textural features of the amplitude of low frequency fluctuation (ALFF) in the slow-5 frequency band and structural images in the hippocampus to investigate their diagnostic performance for AD and aMCI using multimodal radiomics technique.MethodsTotally, 84 AD, 50 aMCI, and 44 normal controls (NCs) were included in the current study. After feature extraction and feature selection, the radiomics models incorporating sMRI images, ALFF values and their combinations in the bilateral hippocampus were established for the diagnosis of AD and aMCI. The effectiveness of these models was evaluated by receiver operating characteristic (ROC) analysis. The radiomics models were further validated using the external data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database.ResultsThe results of ROC analysis showed that the radiomics models based on structural images in the hippocampus had a better diagnostic performance for AD compared with the models using ALFF, while the ALFF-based model exhibited better discriminant performance for aMCI than the models with structural images. The radiomics models based on the combinations of structural images and ALFF were found to exhibit the highest accuracy for distinguishing AD from NCs and aMCI from NCs.ConclusionIn this study, we found that the textural features reflecting local functional activity could improve the diagnostic performance of traditional structural models for both AD and aMCI. These findings may deepen our understanding of the pathogenesis of AD, contributing to the early diagnosis of AD.

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Section: Methodsmentioning

confidence: 87%

Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Wang

Feng

et al. 2022

Front. Neurosci.

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“…The three time points of rs-fMRI were before stimulating the trigger zone (baseline), within 5 s after stimulating the trigger zone (triggering-5 s), and 30 min after stimulating the trigger zone (triggering-30 min). After scanning, the patients were asked whether the stimulation caused pain and whether they experienced additional pain during the scan ( Ge et al, 2022b ).…”

Section: Methodsmentioning

confidence: 99%

“…A higher score indicated a greater pain intensity. A rating of “0” represented no pain, and a rating of “10” meant intolerable pain ( Ge et al, 2022b ).…”

Section: Methodsmentioning

confidence: 99%

“…Neurovascular compression (NVC) is the main cause of CTN ( Cruccu et al, 2020 ; Ge et al, 2022b ), and its pathogenesis is caused by nerve demyelination, which leads to a short circuit between the painful and non-painful fibers, thus causing pain ( Shankar Kikkeri and Nagalli, 2022 ). Studies on the structural and functional magnetic resonance imaging (MRI) of CTN suggested that the central nervous system is involved in the pathophysiological process of CTN ( Liu et al, 2018 ; Wu M. et al, 2020 ; Wu S. et al, 2020 ; Zhu et al, 2020 ; Shankar Kikkeri and Nagalli, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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Alteration of brain network centrality in CTN patients after a single triggering pain

Wang²,

Wang³

et al. 2023

Front. Neurosci.

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ObjectiveThe central nervous system may also be involved in the pathogenesis of classical trigeminal neuralgia (CTN). The present study aimed to explore the characteristics of static degree centrality (sDC) and dynamic degree centrality (dDC) at multiple time points after a single triggering pain in CTN patients.Materials and methodsA total of 43 CTN patients underwent resting-state function magnetic resonance imaging (rs-fMRI) before triggering pain (baseline), within 5 s after triggering pain (triggering-5 s), and 30 min after triggering pain (triggering-30 min). Voxel-based degree centrality (DC) was used to assess the alteration of functional connection at different time points.ResultsThe sDC values of the right caudate nucleus, fusiform gyrus, middle temporal gyrus, middle frontal gyrus, and orbital part were decreased in triggering-5 s and increased in triggering-30 min. The sDC value of the bilateral superior frontal gyrus were increased in triggering-5 s and decreased in triggering-30 min. The dDC value of the right lingual gyrus was gradually increased in triggering-5 s and triggering-30 min.ConclusionBoth the sDC and dDC values were changed after triggering pain, and the brain regions were different between the two parameters, which supplemented each other. The brain regions which the sDC and dDC values were changing reflect the global brain function of CTN patients, and provides a basis for further exploration of the central mechanism of CTN.

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“…Neurovascular compression (NVC) is considered to be the main cause of CTN [8], and demonstration on MRI or during surgery of neurovascular compression (not simply contact), with morphological changes in the trigeminal nerve root [7]. That is, the offending vessel compresses the trigeminal nerve root entry zone, which results in the demyelination and axonal loss of the trigeminal nerve, resulting in a short circuit between pain fibers and non-pain fibers, and thus causing pain [9,10].…”

Section: Introductionmentioning

confidence: 99%

Amplitude of low-frequency fluctuation after a single-trigger pain in patients with classical trigeminal neuralgia

Wang

Pan

et al. 2022

J Headache Pain

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Objective This study aimed to explore the central mechanism of classical trigeminal neuralgia (CTN) by analyzing the static amplitude of low-frequency fluctuation (sALFF) and dynamic amplitude of low-frequency fluctuation (dALFF) in patients with CTN before and after a single-trigger pain. Methods This study included 48 patients (37 women and 11 men, age 55.65 ± 11.41 years) with CTN. All participants underwent 3D-T1WI and three times resting-state functional magnetic resonance imaging. The images were taken before stimulating the trigger zone (baseline), within 5 s after stimulating the trigger zone (triggering-5 s), and in the 30th minute after stimulating the trigger zone (triggering-30 min). The differences between the three measurements were analyzed using a repeated-measures analysis of variance. Results The sALFF values of the bilateral middle occipital gyrus and right cuneus gradually increased, and the values of the left posterior cingulum gyrus and bilateral superior frontal gyrus gradually decreased in triggering-5 s and triggering-30 min. The values of the right middle temporal gyrus and right thalamus decreased in triggering-5 s and subsequently increased in triggering-30 min. The sALFF values of the left superior temporal gyrus increased in triggering-5 s and then decreased in triggering-30 min. The dALFF values of the right fusiform gyrus, bilateral lingual gyrus, left middle temporal gyrus, and right cuneus gyrus gradually increased in both triggering-5 s and triggering-30 min. Conclusions The sALFF and dALFF values changed differently in multiple brain regions in triggering-5 s and triggering-30 min of CTN patients after a single trigger of pain, and dALFF is complementary to sALFF. The results might help explore the therapeutic targets for relieving pain and improving the quality of life of patients with CTN.

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Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

Cited by 10 publications

References 32 publications

Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer’s disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Alteration of brain network centrality in CTN patients after a single triggering pain

Amplitude of low-frequency fluctuation after a single-trigger pain in patients with classical trigeminal neuralgia

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