Analyzing the risk factors of unilateral trigeminal neuralgia under neurovascular compression.

Background: This study aimed to explore the risk factors and potential causes of unilateral classical or idiopathic trigeminal neuralgia (C-ITN) by comparing patients and healthy controls (HCs) with neurovascular compression (NVC) using machine learning (ML). Methods: A total of 84 C-ITN patients and 78 age- and sex-matched HCs were enrolled. We assessed the trigeminal pons angle and identified the compressing vessels and their location and severity. Machine learning was employed to analyze the cisternal segment of the trigeminal nerve (CN V). Results: Among the C-ITN patients, 53 had NVC on the unaffected side, while 25 HCs exhibited bilateral NVC, and 24 HCs showed unilateral NVC. By comparing the cisternal segment of CN V between C-ITN patients on the affected side and HCs with NVC, we identified the side of NVC, the compressing vessel, and certain texture features as risk factors for C-ITN. Additionally, four texture features differed in the structure of the cisternal segment of CN V between C-ITN patients on the unaffected side and HCs with NVC. Conclusion: Our findings suggest that the side of NVC, the compressing vessel, and the microstructure of the cisternal segment of CN V are associated with the risk of C-ITN. Furthermore, microstructural changes observed in the cisternal segment of CN V on the unaffected side of C-ITN patients with NVC indicate possible indirect effects on the CN V to some extent.

Altered trends of local brain function in classical trigeminal neuralgia patients after a single trigger pain.

OBJECTIVE: To investigate the altered trends of regional homogeneity (ReHo) based on time and frequency, and clarify the time-frequency characteristics of ReHo in 48 classical trigeminal neuralgia (CTN) patients after a single pain stimulate. METHODS: All patients underwent three times resting-state functional MRI (before stimulation (baseline), after stimulation within 5 s (triggering-5 s), and in the 30th min of stimulation (triggering-30 min)). The spontaneous brain activity was investigated by static ReHo (sReHo) in five different frequency bands and dynamic ReHo (dReHo) methods. RESULTS: In the five frequency bands, the number of brain regions which the sReHo value changed in classical frequency band were most, followed by slow 4 frequency band. The left superior occipital gyrus was only found in slow 2 frequency band and the left superior parietal gyrus was only found in slow 3 frequency band. The dReHo values were changed in midbrain, left thalamus, right putamen, and anterior cingulate cortex, which were all different from the brain regions that the sReHo value altered. There were four altered trends of the sReHo and dReHo, which dominated by decreased at triggering-5 s and increased at triggering-30 min. CONCLUSIONS: The duration of brain function changed was more than 30 min after a single pain stimulate, although the pain of CTN was transient. The localized functional homogeneity has time-frequency characteristic in CTN patients after a single pain stimulate, and the changed brain regions of the sReHo in five frequency bands and dReHo complemented to each other. Which provided a certain theoretical basis for exploring the pathophysiology of CTN.

Altered brain function in classical trigeminal neuralgia patients: ALFF, ReHo, and DC static- and dynamic-frequency study.

The present study aimed to clarify the brain function of classical trigeminal neuralgia (CTN) by analyzing 77 CTN patients and age- and gender-matched 73 healthy controls (HCs) based on three frequency bands of the static and dynamic amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality (sALFF, sReHo, sDC, dALFF, dReHo, and dDC). Compared to HCs, the number of altered brain regions was different in three frequency bands, and the classical frequency band was most followed by slow-4 in CTN patients. Cerrelellum_8_L (sReHo), Cerrelellum_8_R (sDC), Calcarine_R (sDC), and Caudate_R (sDC) were found only in classical frequency band, while Precuneus_L (sALFF) and Frontal_Inf_Tri_L (sReHo) were found only in slow-4 frequency band. Except for the above six brain regions, the others overlapped in the classical and slow-4 frequency bands. CTN seriously affects the mental health of patients, and some different brain regions are correlated with clinical parameters. The static and dynamic indicators of brain function were complementary in CTN patients, and the changing brain regions showed frequency specificity. Compared to slow-5 frequency band, slow-4 is more consistent with the classical frequency band, which could be valuable in exploring the pathophysiology of CTN.

Brain entropy changes in classical trigeminal neuralgia.

Background: Classical trigeminal neuralgia (CTN) is a common and severe chronic neuropathic facial pain disorder. The pathological mechanisms of CTN are not fully understood. Recent studies have shown that resting-state functional magnetic resonance imaging (rs-fMRI) could provide insights into the functional changes of CTN patients and the complexity of neural processes. However, the precise spatial pattern of complexity changes in CTN patients is still unclear. This study is designed to explore the spatial distribution of complexity alterations in CTN patients using brain entropy (BEN). Methods: A total of 85 CTN patients and 79 age- and sex-matched healthy controls (HCs) were enrolled in this study. All participants underwent rs-fMRI and neuropsychological evaluations. BEN changes were analyzed to observe the spatial distribution of CTN patient complexity, as well as the relationship between these changes and clinical variables. Sixteen different machine learning methods were employed to classify the CTN patients from the HCs, and the best-performing method was selected. Results: Compared with HCs, CTN patients exhibited increased BEN in the thalamus and brainstem, and decreased BEN in the inferior semilunar lobule. Further analyses revealed a low positive correlation between the average BEN values of the thalamus and neuropsychological assessments. Among the 16 machine learning methods, the Conditional Mutual Information Maximization-Random Forest (CMIM-RF) method yielded the highest area under the curve (AUC) of 0.801. Conclusions: Our study demonstrated that BEN changes in the thalamus and pons and inferior semilunar lobule were associated with CTN and machine learning methods could effectively classify CTN patients and HCs based on BEN changes. Our findings may provide new insights into the neuropathological mechanisms of CTN and have implications for the diagnosis and treatment of CTN.

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

Objective: The 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 methods: A 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. Results: The 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. Conclusion: Both 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.

Alteration of the cortical morphology in classical trigeminal neuralgia: voxel-, deformation-, and surface-based analysis.

OBJECTIVE: This study aimed to combine voxel-based morphometry, deformation-based morphometry, and surface-based morphometry to analyze gray matter volume and cortex shape in classical trigeminal neuralgia patients. METHODS: This study included 79 classical trigeminal neuralgia patients and age- and sex-matched 81 healthy controls. The aforementioned three methods were used to analyze brain structure in classical trigeminal neuralgia patients. Spearman correlation analysis was used to analyze the correlation of brain structure with the trigeminal nerve and clinical parameters. RESULTS: The bilateral trigeminal nerve was atrophied, and the ipsilateral trigeminal nerve volume was smaller than the contralateral volume in the classical trigeminal neuralgia. The gray matter volume of Temporal_Pole_Sup_R and Precentral_R was found to be decreased using voxel-based morphometry. The gray matter volume of Temporal_Pole_Sup_R had a positive correlation with disease duration and a negative correlation with the cross-section area of the compression point and the quality-of-life score in trigeminal neuralgia. The gray matter volume of Precentral_R was negatively correlated with the ipsilateral volume of the trigeminal nerve cisternal segment, cross-section area of compression point, and visual analogue scale. The gray matter volume of Temporal_Pole_Sup_L was found to be increased using deformation-based morphometry and had a negative correlation with the self-rating anxiety scale. The gyrification of the middle temporal gyrus_L increased and the Postcentral_L thickness decreased, as detected using surface-based morphometry. CONCLUSIONS: The gray matter volume and cortical morphology of pain-related brain regions were correlated with clinical and trigeminal nerve parameters. voxel-based morphometry, deformation-based morphometry, and surface-based morphometry complemented each other in analyzing the brain structures of patients with classical trigeminal neuralgia and provided a basis for studying the pathophysiology of classical trigeminal neuralgia.

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

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.

Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning.

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 (p < 0.05). The nomogram model had optimal diagnostic power, and the area under the curve (AUC) in the training and validation cohorts was 0.76 and 0.77, respectively. The Ofv and rad_score were the risk factors for UC-ITN according to nomogram. 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.

Combining in vivo proton exchange rate (k ex) MRI with quantitative susceptibility mapping to further stratify the gadolinium-negative multiple sclerosis lesions.

Background: Conventional gadolinium (Gd)-enhanced MRI is currently used for stratifying the lesion activity of multiple sclerosis (MS) despite limited correlation with disability and disease activity. The stratification of MS lesion activity needs further improvement to better support clinics. Purpose: To investigate if the novel proton exchange rate (k ex ) MRI combined with quantitative susceptibility mapping (QSM) may help to further stratify non-enhanced (Gd-negative) MS lesions. Materials and methods: From December 2017 to December 2020, clinically diagnosed relapsing-remitting MS patients who underwent MRI were consecutively enrolled in this IRB-approved retrospective study. The customized MRI protocol covered conventional T2-weighted, T2-fluid-attenuated-inversion-recovery, pre- and post-contrast T1-weighted imaging, and quantitative sequences, including k ex MRI based on direct-saturation removed omega plots and QSM. Each MS lesion was evaluated based on its Gd-enhancement as well as its susceptibility and k ex elevation compared to the normal appearing white matter. The difference and correlation concerning lesion characteristics and imaging contrasts were analyzed using the Mann-Whitney U test or Kruskal-Wallis test, and Spearman rank analysis with p < 0.05 considered significant. Results: A total of 322 MS lesions from 30 patients were identified with 153 Gd-enhanced and 169 non-enhanced lesions. We found that the k ex elevation of all lesions significantly correlated with their susceptibility elevation (r = 0.30, p < 0.001). Within the 153 MS lesions with Gd-enhancement, ring-enhanced lesions showed higher k ex elevation than the nodular-enhanced ones' (p < 0.001). Similarly, lesions with ring-hyperintensity in QSM also had higher k ex elevation than the lesions with nodular-QSM-hyperintensity (p < 0.001). Of the 169 Gd-negative lesions, three radiological patterns were recognized according to lesion manifestations on the k ex map and QSM images: Pattern I (k ex + and QSM+, n = 114, 67.5%), Pattern II (only k ex + or QSM+, n = 47, 27.8%) and Pattern III (k ex - and QSM-, n = 8, 4.7%). Compared to Pattern II and III, Pattern I had higher k ex (p < 0.001) and susceptibility (p < 0.05) elevation. The percentage of Pattern I of each subject was negatively correlated with the disease duration (r = -0.45, p = 0.015). Conclusion: As a potential imaging biomarker for inflammation due to oxidative stress, in vivo k ex MRI combined with QSM is promising in extending the clinical classification of MS lesions beyond conventional Gd-enhanced MRI.

Radiomics analysis of unaffected side changes in classic trigeminal neuralgia.

OBJECTIVE: To investigate the subtle differences in the structure of the unaffected trigeminal nerve between patients with classic trigeminal neuralgia (CTN) and healthy controls (HCs) by means of radiomics, so as to further explore the etiological mechanism of trigeminal neuralgia (TN). METHODS: The imagine data of 95 CTN patients and 89 matched HCs were collected and retrospectively analyzed. They were assigned to four groups according to the presence or absence of neurovascular compression (NVC) of the unaffected trigeminal nerve (HCs with and without NVC; CTN patients with and without NVC on the unaffected side). All patients underwent magnetic resonance imaging (MRI) scans. Bilateral trigeminal cisternal segments were manually delineated, followed by feature extraction, dimensionality reduction, feature selection, model construction and model evaluation. RESULTS: Six weighted textural signatures (sphericity, maximum 2D diameter, skewness, robust mean absolute deviation, large dependence low gray level emphasis, and surface-to-volume ratio) were found in HCs with and without NVC, while 7 were found in CTN patients without NVC on the unaffected side and HCs without NVC. The Rad_score was statistically different between the two groups (P < 0.05). The AUC of the training set was consistent with that of the validation set. The calibration curves of the training and validation sets demonstrated the high accuracy of the model. CONCLUSIONS: NVC can alter trigeminal nerve structure and cause alterations in related characteristics; but NVC is not a necessary condition for the formation of CTN, and its incidence is also high in asymptomatic healthy people, and thus it is necessary to grade the severity of NVC. In addition, there are differences in the characteristics of the unaffected side between CTN patients and HCs, which may be due to congenital or secondary factors.

In Vivo Proton Exchange Rate (kex ) MRI for the Characterization of Multiple Sclerosis Lesions in Patients.

BACKGROUND: Currently available radiological methods do not completely capture the diversity of multiple sclerosis (MS) lesion subtypes. This lack of information hampers the understanding of disease progression and potential treatment stratification. For example, inflammation persists in some lesions after gadolinium (Gd) enhancement resolves. Novel metabolic and molecular imaging methods may improve the current assessments of MS pathophysiology. PURPOSE: To compare the in vivo proton exchange rate (kex ) MRI with Gd-enhanced MRI for characterizing MS lesions. STUDY TYPE: Retrospective. SUBJECTS: Sixteen consecutively diagnosed relapsing-remitting multiple sclerosis (RRMS) patients. FIELD STRENGTH/SEQUENCE: 3.0T MRI with T2 -weighted imaging, postcontrast T1 -weighted imaging, and single-slice chemical exchange saturation transfer imaging. ASSESSMENT: MS lesions in white matter were assessed for Gd enhancement and kex elevation compared to normal-appearing white matter (NAWM). STATISTICAL TESTS: Student's t-test was used for analyzing the difference of kex values between lesions and NAWM, with statistical significance set at 0.05. RESULTS: Of all 153 MS lesions, 78 (51%) lesions were Gd-enhancing and 75 (49%) were Gd-negative. Without exception, all 78 Gd-enhancing lesions showed significantly elevated kex values compared to NAWM (924 ± 130 s-1 vs. 735 ± 61 s-1 , P < 0.05). Of 75 Gd-negative lesions, 18 lesions (24%) showed no kex elevation (762 ± 29 s-1 vs. 755 ± 28 s-1 , P = 0.47) and 57 (76%) showed significant kex elevation (950 ± 124 s-1 vs. 759 ± 48 s-1 , P < 0.05) compared to NAWM. MS lesions with kex elevation appeared nodular (118, 87.4%), ring-like (15, 11.1%), or irregular-shaped (2, 1.5%). DATA CONCLUSION: For Gd-enhancing lesions, kex MRI is highly consistent with Gd-enhanced images by showing 100% of elevated kex . For all Gd-negative lesions, the discrepancy on kex MRI may further differentiate active slowly expanding lesions or chronic inactive lesions, supporting kex as an imaging biomarker for tissue oxidative stress and inflammation. Level of Evidence 2 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:408-415.

In vivo quantification of proton exchange rate in healthy human brains with omega plot.

BACKGROUND: To implement omega plot method for in vivo mapping of proton exchange rates in human brain by taking into account the water direct saturation (DS) effect and multiple saturation transfer exchanging species in vivo. METHODS: Four Z-spectra were collected with chemical exchange saturation transfer (CEST) saturation power =1, 2, 3 & 4 µT. Water DS was estimated by fitting the Z-spectrum to a linear combination of multiple Lorentzian components and its contribution to the signal was subsequently removed. Exchange rate maps were derived by the omega plot, consisting of fitting the inverse of the signal intensity, Mz /(M 0-Mz ), as a function of 1/(γB1)2. RESULTS: The exchange rate values quantified with the DS removed omega plot were significantly higher in the GM region than in the WM region (616±29 vs. 575±20 s-1, P<0.001). Phantom studies confirmed that the exchange rates from DS-removed plots varied linearly with pH (R2=0.998) for the pH range of 6.2 to 7.4, whereas exchange rates from conventional omega plots failed to show such linearity in the entire physiological pH range. CONCLUSIONS: The calculated exchange rate with DS-corrected omega plot is a weighted average for all saturation transfer exchanging proton species which contribute to Z-spectral signal. The healthy brain exchange rate map provided by DS-removed omega plots may serve as a baseline for detecting any pathological changes.