ArticleFrontiers in neurology2022
Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Radiomic Applications in Skull Base Pathology: A Systematic Review of Potential Clinical Uses.Journal of neurological surgery. Part B, Skull base · 2025Article
- Glymphatic and neurofluidic dysfunction in classical trigeminal neuralgia: a multimodal MRI study of brain-CSF functional and structural dynamics.BMC medical imaging · 2025Article
- Application research on the diagnosis of classic trigeminal neuralgia based on VB-Net technology and radiomics.BMC medical imaging · 2024Article
- Review
- Altered trends of local brain function in classical trigeminal neuralgia patients after a single trigger pain.BMC medical imaging · 2024Article
- Editorial: Functional approach to neurosurgery: current research and future perspectives.Frontiers in surgery · 2024Article
- Analyzing the risk factors of unilateral trigeminal neuralgia under neurovascular compression.Frontiers in human neuroscience · 2024Article
- Brain entropy changes in classical trigeminal neuralgia.Frontiers in neurology · 2023Article
- Alteration of brain network centrality in CTN patients after a single triggering pain.Frontiers in neuroscience · 2023Article
- The role of artificial intelligence in the management of trigeminal neuralgia.Frontiers in surgery · 2023Review
- Development and validation of radiomics models for the prediction of diagnosis of classic trigeminal neuralgia.Frontiers in neuroscience · 2023Article
- Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease.Frontiers in neurology · 2023Article
- 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.Frontiers in neuroscience · 2022Article
- Radiomics analysis of unaffected side changes in classic trigeminal neuralgia.American journal of translational research · 2022Article
- Article
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7 authors.
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Abstract
Purpose: Neurovascular compression (NVC) is considered as the main factor leading to the classical trigeminal neuralgia (CTN), and a part of idiopathic TN (ITN) may be caused by NVC (ITN-nvc). This study aimed to explore the risk factors for unilateral CTN or ITN-nvc (UC-ITN), which have bilateral NVC, using machine learning (ML). Methods: A total of 89 patients with UC-ITN were recruited prospectively. According to whether there was NVC on the unaffected side, patients with UC-ITN were divided into two groups. All patients underwent a magnetic resonance imaging (MRI) scan. The bilateral cisternal segment of the trigeminal nerve was manually delineated, which avoided the offending vessel (Ofv), and the features were extracted. Dimensionality reduction, feature selection, model construction, and model evaluation were performed step-by-step. Results: Four textural features with greater weight were selected in patients with UC-ITN without NVC on the unaffected side. For UC-ITN patients with NVC on the unaffected side, six textural features with greater weight were selected. The textural features (rad_score) showed significant differences between the affected and unaffected sides ( Conclusion: Besides NVC, the texture features of trigeminal-nerve cisternal segment and Ofv were also the risk factors for UC-ITN. These findings provided a basis for further exploration of the microscopic etiology of UC-ITN.
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