Qun-Lin Chen

Background: Spinocerebellar ataxia type 3 (SCA3) is a rare neurodegenerative condition. Prior research has established perivascular spaces (PVS) expansion has been implicated in the pathogenesis and prognosis of various neurodegenerative diseases. To examine PVS changes in SCA3 by comparing patients and matched healthy controls and to identify potential connection of PVS for clinical features. Methods: We conducted MRI scans on 91 SCA3 patients and 64 healthy controls. We utilized visual semi-quantitative methods to assess PVS in various brain regions, including the center of the semiovale (CSO), basal ganglia (BG), and midbrain-pons, as well as combinations (BG + CSO, BG + CSO + midbrain-pons). To differentiate SCA3 patients from healthy controls, we compared the area under the curve (AUC) of the receiver operating characteristic curve between the two groups. Additionally, we employed Pearson’s correlation coefficient to examine the relationship between PVS scores in each brain region and clinical indicators among SCA3 patients. Results: In the SCA3 group, we observed higher levels of PVS in the BG, CSO + BG, and three brain regions compared to the healthy control group. PVS in the CSO and CSO + BG also showed positive correlations with age and disease duration, and negative correlations with the number of CAG repeats. Furthermore, PVS in three brain regions exhibited negative correlation with the number of CAG repeats. Conclusions: This study represents an initial investigation into the relationship between PVS and SCA3 disease. Our findings suggest that PVS might indicate the degree of cerebellar ataxia to a certain extent.

The objective of this study was to review the history of magnetic resonance imaging (MRI) research on spinocerebellar ataxia (SCA) over the last 16 years. We conducted a comprehensive bibliometric analysis of relevant scientific literature that explores the use of MRI in studying SCA using CiteSpace. A total of 761 scientific manuscripts, published between January 2009 and March 2025 and available in the Web of Science (WoS) database, were included in this analysis. A total of 197 out of 761 articles were analyzed using CiteSpace to determine the number and centrality of publications, countries, institutions, journals, authors, cited references, and keywords related to MRI and SCA. Overall, the number of publications that use MRI to study SCA has gradually increased over the years. The United States, China, Italy, Germany, and Brazil are at the forefront in this research field; a total of 420 authors from 317 research institutions in these nations have published articles in neuroscience-related journals. Among the most cited publications are an article by Rezende et al. on brain structural damage in SCA3 patients and an review by Klockgether et al. on spinocerebellar ataxia. The keyword “spinocerebellar ataxia” has the highest frequency of occurrence. However, “feature” may become a research hotspot in the coming years based on the analysis of the keyword’s citation burst. The findings of this bibliometric study provide a summary of the last 16 years of SCA research using MRI technology. More importantly, the present study identifies current trends and future research hotspots in the field, helping researchers to identify new and unexplored research areas.

Repetitive transcranial magnetic stimulation (rTMS), a noninvasive neuroregulatory technique used to treat neurodegenerative diseases, holds promise for spinocerebellar ataxia type 3 (SCA3) treatment, although its efficacy and mechanisms remain unclear. This study aims to observe the short-term impact of cerebellar rTMS on motor function in SCA3 patients and utilize resting-state functional magnetic resonance imaging (RS-fMRI) to assess potential therapeutic mechanisms. Twenty-two SCA3 patients were randomly assigned to receive actual rTMS (AC group, n = 11, three men and eight women; age 32–55 years) or sham rTMS (SH group, n = 11, three men and eight women; age 26–58 years). Both groups underwent cerebellar rTMS or sham rTMS daily for 15 days. The primary outcome measured was the ICARS scores and parameters for regional brain activity. Compared to baseline, ICARS scores decreased more significantly in the AC group than in the SH group after the 15-day intervention. Imaging indicators revealed increased Amplitude of Low Frequency Fluctuation (ALFF) values in the posterior cerebellar lobe and cerebellar tonsil following AC stimulation. This study suggests that rTMS enhances motor functions in SCA3 patients by modulating the excitability of specific brain regions and associated pathways, reinforcing the potential clinical utility of rTMS in SCA3 treatment. The Chinese Clinical Trial Registry identifier is ChiCTR1800020133.

Objectives: Spinocerebellar ataxia type 3 is a disorder within the brain network. However, the relationship between the brain network and disease severity is still unclear. This study aims to investigate changes in the white matter (WM) structural motor network, both in preclinical and ataxic stages, and its relationship with disease severity.Methods: For this study, 20 ataxic, 20 preclinical SCA3 patients, and 20 healthy controls were recruited and received MRI scans. Disease severity was quantified using the SARA and ICARS scores. The WM motor structural network was created using probabilistic fiber tracking and was analyzed using graph theory and network‐based statistics at global, nodal, and edge levels. In addition, the correlations between network topological measures and disease duration or clinical scores were analyzed.Results: Preclinical patients showed increasing assortativity of the motor network, altered subnetwork including 12 edges of 11 nodes, and 5 brain regions presenting reduced nodal strength. In ataxic patients assortativity of the motor network also increased, but global efficiency, global strength, and transitivity decreased. Ataxic patients showed a wider altered subnetwork and a higher number of reduced nodal strengths. A negative correlation between the transitivity of the motor network and SARA and ICARS scores was observed in ataxic patients.Interpretation: Changes to the WM motor network in SCA3 start before ataxia onset, and WM motor network involvement increases with disease progression. Global network topological measures of the WM motor network appear to be a promising image biomarker for disease severity. This study provides new insights into the pathophysiology of disease in SCA3/MJD.

Background: Spinocerebellar ataxia type 3 (SCA3) is the most common autosomal dominant hereditary ataxia, and, thus far, effective treatment remains low. Repetitive transcranial magnetic stimulation (rTMS) can improve the symptoms of spinal cerebellar ataxia, but the mechanism is unclear; in addition, whether any improvement in the symptoms is related to cerebellar metabolism has not yet been investigated. Therefore, the purpose of this study was to investigate the effects of low-frequency rTMS on local cerebellar metabolism in patients with SCA3 and the relationship between the improvement in the symptoms and cerebellar metabolism.Methods: A double-blind, prospective, randomized, sham-controlled trial was carried out among 18 SCA3 patients. The participants were randomly assigned to the real stimulation group (n = 9) or sham stimulation group (n = 9). Each participant in both the groups underwent 30 min of 1 Hz rTMS stimulation (a total of 900 pulses), differing only in terms of stimulator placement, for 15 consecutive days. To separately compare pre- and post-stimulation data (magnetic resonance spectroscopy (MRS) data and the International Cooperative Ataxia Rating Scale (ICARS) score) in the real and sham groups, paired-sample t-tests and Wilcoxon’s signed-rank tests were used in the analyses. The differences in the ICARS and MRS data between the two groups were analyzed with independent t-tests and covariance. To explore the association between the changes in the concentration of cerebellar metabolism and ICARS, we applied Pearson’s correlation analysis.Results: After 15 days of treatment, the ICARS scores significantly decreased in both the groups, while the decrease was more significant in the real stimulation group compared to the sham stimulation group (p < 0.001). The analysis of covariance further confirmed that the total ICARS scores decreased more dramatically in the real stimulation group after treatment compared to the sham stimulation group (F = 31.239, p < 0.001). The values of NAA/Cr and Cho/Cr in the cerebellar vermis, bilateral dentate nucleus, and bilateral cerebellar hemisphere increased significantly in the real stimulation group (p < 0.05), but no significant differences were found in the sham stimulation group (p > 0.05). The analysis of covariance also confirmed the greater change in the real stimulation group. This study also demonstrated that there was a negative correlation between NAA/Cr in the right cerebellar hemisphere and ICARS in the real stimulation group (r = − 0.831, p = 0.02).Conclusion: The treatment with rTMS over the cerebellum was found to induce changes in the cerebellar local metabolism and microenvironment in the SCA3 patients. The alterations may contribute to the improvement of the symptoms of ataxia in SCA3 patients.

The analysis of structural covariance has emerged as a powerful tool to explore the morphometric correlations among broadly distributed brain regions. However, little is known about the interactions between the damaged primary motor cortex (M1) and other brain regions in stroke patients with motor deficits. This study is aimed at investigating the structural covariance pattern of the ipsilesional M1 in chronic subcortical stroke patients with motor deficits. High-resolution T1-weighted brain images were acquired from 58 chronic subcortical stroke patients with motor deficits (29 with left-sided lesions and 29 with right-sided lesions) and 50 healthy controls. Structural covariance patterns were identified by a seed-based structural covariance method based on gray matter (GM) volume. Group comparisons between stroke patients (left-sided or right-sided groups) and healthy controls were determined by a permutation test. The association between alterations in the regional GM volume and motor recovery after stroke was investigated by a multivariate regression approach. Structural covariance analysis revealed an extensive increase in the structural interactions between the ipsilesional M1 and other brain regions in stroke patients, involving not only motor-related brain regions but also non-motor-related brain regions. We also identified a slightly different pattern of structural covariance between the left-sided stroke group and the right-sided stroke group, thus indicating a lesion-side effect of cortical reorganization after stroke. Moreover, alterations in the GM volume of structural covariance brain regions were significantly correlated to the motor function scores in stroke patients. These findings indicated that the structural covariance patterns of the ipsilesional M1 in chronic subcortical stroke patients were induced by motor-related plasticity. Our findings may help us to better understand the neurobiological mechanisms of motor impairment and recovery in patients with subcortical stroke from different perspectives.

Objective: To develop a machine learning (ML)-based classifier for discriminating between low-grade (ISUP I-II) and high-grade (ISUP III-IV) clear cell renal cell carcinomas (ccRCCs) using MRI textures.Materials and Methods: We retrospectively evaluated a total of 99 patients (with 61 low-grade and 38 high-grade ccRCCs), who were randomly divided into a training set (n = 70) and a validation set (n = 29). Regions of interest (ROIs) of all tumors were manually drawn three times by a radiologist at the maximum lesion level of the cross-sectional CMP sequence images. The quantitative texture analysis software, MaZda, was used to extract texture features, including histograms, co-occurrence matrixes, run-length matrixes, gradient models, and autoregressive models. Reproducibility of the texture features was assessed with the intra-class correlation coefficient (ICC). Features were chosen based on their importance coefficients in a random forest model, while the multi-layer perceptron algorithm was used to build a classifier on the training set, which was later evaluated with the validation set.Results: The ICCs of 257 texture features were equal to or higher than 0.80 (0.828–0.998. Six features, namely Kurtosis, 135dr_RLNonUni, Horzl_GLevNonU, 135dr_GLevNonU, S(4,4)Entropy, and S(0,5)SumEntrp, were chosen to develop the multi-layer perceptron classifier. A three-layer perceptron model, which has 229 nodes in the hidden layer, was trained on the training set. The accuracy of the model was 95.7% with the training set and 86.2% with the validation set. The areas under the receiver operating curves were 0.997 and 0.758 for the training and validation sets, respectively.Conclusions: A machine learning-based grading model was developed that can aid in the clinical diagnosis of clear cell renal cell carcinoma using MRI images.