Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography

Advanced neuroimaging of the trigeminal nerve and the whole brain in trigeminal neuralgia: a systematic review

ABSTRACT

For trigeminal neuralgia (TN), a major role of imaging is to identify the causes, but recent studies demonstrated structural and microstructural changes in the affected nerve. Moreover, an increasing number of studies have reported central nervous system involvement in TN. In this systematic review, recent quantitative magnetic resonance imaging (MRI) studies of the trigeminal nerve and the brain in patients with TN were compiled, organized, and discussed, particularly emphasizing the possible background mechanisms and the interpretation of the results. A systematic search of quantitative MRI studies of the trigeminal nerve and the brain in patients with TN was conducted using PubMed. We included the studies of the primary TN published during 2013 to 2023, conducted for the assessment of the structural and microstructural analysis of the trigeminal nerve, and the structural, diffusion, and functional MRI analysis of the brain. Quantitative MRI studies of the affected trigeminal nerves and the trigeminal pathway demonstrated structural/microstructural alterations and treatment-related changes, which differentiated responders from nonresponders. Quantitative analysis of the brain revealed changes in the brain areas associated with pain processing/modulation and emotional networks. Studies of the affected nerve demonstrated evidence of demyelination and axonal damage, compatible with pathological findings, and have shown its potential value as a tool to assess treatment outcomes. Quantitative MRI has also revealed the possibility of dynamic microstructural, structural, and functional neuronal plasticity of the brain. Further studies are needed to understand these complex mechanisms of neuronal plasticity and to achieve a consensus on the clinical use of quantitative MRI in TN.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review

ABSTRACT

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

A novel potential measurement indicator with objective and quantitative effect for trigeminal neuralgia: fractional anisotropy in MR-DTI

Objectives

To investigate the effect of diffusivity metrics of magnetic resonance diffusion tensor imaging (MR-DTI) in the assessment of treatment effects.

Methods

MR-DTI examination for trigeminal neuralgia (TN) patients and the diffusivity metrics of the trigeminal ganglion (TG) were analyzed. Before and after the percutaneous stereotactic radiofrequency rhizotomy (PSR) operation, the treatment effect was assessed using pain scores and MR-DTI. The correlation between the diffusivity metrics of cranial nerve five (CNV) and visual analog scale (VAS) pain scores before and after treatment in TN patients was explored.

Results

In PSR patients, the fractional anisotropy (FA) of the affected TG is a significantly lower than that of the unaffected side (p < 0.01). After PSR, the diffusivity metrics on the bilateral TGs are not significantly different (p > 0.05). Following PSR treatment, both of the diffusivity metrics (FA) in the lowest area of the CNV and the VAS scores of TN patients show changes. Furthermore, diffusivity metric (FA) on the lowest area of the CNV preoperative is significantly negatively correlated with the VAS scores (p < 0.05).

Conclusion

MR-DTI is capable of investigating the longitudinal changes of FA before and after radiofrequency treatment, and diffusivity metrics could be an independent reliable efficacy indicator for TN.

Significance

The alteration of the diffusivity on TG may be correlated with the effect of radiofrequency treatment.

Application research on the diagnosis of classic trigeminal neuralgia based on VB-Net technology and radiomics

BACKGROUND

This study aims to utilize the deep learning method of VB-Net to locate and segment the trigeminal nerve, and employ radiomics methods to distinguish between CTN patients and healthy individuals.

METHODS

A total of 165 CTN patients and 175 healthy controls, matched for gender and age, were recruited. All subjects underwent magnetic resonance scans. VB-Net was used to locate and segment the bilateral trigeminal nerve of all subjects, followed by the application of radiomics methods for feature extraction, dimensionality reduction, feature selection, model construction, and model evaluation.

RESULTS

On the test set for trigeminal nerve segmentation, our segmentation parameters are as follows: the mean Dice Similarity Coefficient (mDCS) is 0.74, the Average Symmetric Surface Distance (ASSD) is 0.64 mm, and the Hausdorff Distance (HD) is 3.34 mm, which are within the acceptable range. Analysis of CTN patients and healthy controls identified 12 features with larger weights, and there was a statistically significant difference in Rad_score between the two groups (p < 0.05). The Area Under the Curve (AUC) values for the three models (Gradient Boosting Decision Tree, Gaussian Process, and Random Forest) are 0.90, 0.87, and 0.86, respectively. After testing with DeLong and McNemar methods, these three models all exhibit good performance in distinguishing CTN from normal individuals.

CONCLUSIONS

Radiomics can aid in the clinical diagnosis of CTN, and it is a more objective approach. It serves as a reliable neurobiological indicator for the clinical diagnosis of CTN and the assessment of changes in the trigeminal nerve in patients with CTN.

A novel indicator to predict the outcome of percutaneous stereotactic radiofrequency rhizotomy for trigeminal neuralgia patients: diffusivity metrics of MR-DTI

Magnetic resonance-diffusion tensor imaging (MR-DTI) has been used in the microvascular decompression and gamma knife radiosurgery in trigeminal neuralgia (TN) patients; however, use of percutaneous stereotactic radiofrequency rhizotomy (PSR) to target an abnormal trigeminal ganglion (ab-TG) is unreported. Fractional anisotropy (FA), mean and radial diffusivity (MD and RD, respectively), and axial diffusivity (AD) of the trigeminal nerve (CNV) were measured in 20 TN patients and 40 healthy control participants immediately post PSR, at 6-months, and at 1 year. Longitudinal alteration of the diffusivity metrics and any correlation with treatment effects, or prognoses, were analyzed. In the TN group, either low FA (value < 0.30) or a decreased range compared to the adjacent FA (dFA) > 17% defined an ab-TG. Two-to-three days post PSR, all 15 patients reported decreased pain scores with increased FA at the ab-TG (P < 0.001), but decreased MD and RD (P < 0.01 each). Treatment remained effective in 10 of 14 patients (71.4%) and 8 of 12 patients (66.7%) at the 6-month and 1-year follow-ups, respectively. In patients with ab-TGs, there was a significant difference in treatment outcomes between patients with low FA values (9 of 10; 90%) and patients with dFA (2 of 5; 40%) (P < 0.05). MR-DTI with diffusivity metrics correlated microstructural CNV abnormalities with PSR outcomes. Of all the diffusivity metrics, FA could be considered a novel objective quantitative indicator of treatment effects and a potential indicator of PSR effectiveness in TN patients.

The role of artificial intelligence in the management of trigeminal neuralgia

Trigeminal neuralgia (TN) is the most frequent facial pain. It is difficult to treat pharmacologically and a significant amount of patients can become drug-resistant requiring surgical intervention. From an etiologically point of view TN can be distinguished in a classic form, usually due to a neurovascular conflict, a secondary form (for example related to multiple sclerosis or a cerebello-pontine angle tumor) and an idiopathic form in which no anatomical cause is identifiable. Despite numerous efforts to treat TN, many patients experience recurrence after multiple operations. This fact reflects our incomplete understanding of TN pathogenesis. Artificial intelligence (AI) uses computer technology to develop systems for extension of human intelligence. In the last few years, it has been a widespread of AI in different areas of medicine to implement diagnostic accuracy, treatment selection and even drug production. The aim of this mini-review is to provide an up to date of the state-of-art of AI applications in TN diagnosis and management.

Functional MRI-Guided Motor Cortex and Deep Brain Stimulation for Intractable Facial Pain: A Novel, Personalized Approach in 1 Patient

BACKGROUND

Facial neuropathic pain syndromes such as trigeminal neuralgia are debilitating disorders commonly managed by medications, vascular decompression, and/or ablative procedures. In trigeminal neuralgia cases unresponsive to these interventions, trigeminal deafferentation pain syndrome (TDPS) can emerge and remain refractory to any further attempts at these conventional therapies. Deep brain stimulation (DBS) and motor cortex stimulation are 2 neuromodulatory treatments that have demonstrated efficacy in small case series of TDPS yet remain largely underutilized. In addition, functional MRI (fMRI) is a tool that can help localize central processing of evoked stimuli such as mechanically triggered facial pain. In this study, we present a case report and operative technique in a patient with TDPS who underwent fMRI to guide the operative management and placement of dual targets in the sensory thalamus and motor cortex.

OBJECTIVE

To evaluate the safety, efficacy, and outcome of a novel surgical approach for TDPS in a single patient.

METHODS

The fMRI and operative technique of unilateral DBS targeting the ventroposteromedial nucleus of the thalamus and facial motor cortex stimulator placement through a single burr hole is illustrated as well as the patient's clinical outcome.

RESULTS

In less than 1 year, the patient had near complete resolution of his facial pain with no postoperative complications.

CONCLUSION

We present the first published case of successful treatment of TDPS using simultaneous DBS of the ventroposteromedial and motor cortex stimulation. fMRI can be used as an effective imaging modality to guide neuromodulation in this complex disorder.