Structural magnetic resonance imaging in dystonia: A systematic review of methodological approaches and findings.

BACKGROUND AND PURPOSE: Structural magnetic resonance techniques have been widely applied in neurological disorders to better understand tissue changes, probing characteristics such as volume, iron deposition and diffusion. Dystonia is a hyperkinetic movement disorder, resulting in abnormal postures and pain. Its pathophysiology is poorly understood, with normal routine clinical imaging in idiopathic forms. More advanced tools provide an opportunity to identify smaller scale structural changes which may underpin pathophysiology. This review aims to provide an overview of methodological approaches undertaken in structural brain imaging of dystonia cohorts, and to identify commonly identified pathways, networks or regions that are implicated in pathogenesis. METHODS: Structural magnetic resonance imaging studies of idiopathic and genetic forms of dystonia were systematically reviewed. Adhering to strict inclusion and exclusion criteria, PubMed and Embase databases were searched up to January 2022, with studies reviewed for methodological quality and key findings. RESULTS: Seventy-seven studies were included, involving 1945 participants. The majority of studies employed diffusion tensor imaging (DTI) (n = 45) or volumetric analyses (n = 37), with frequently implicated areas of abnormality in the brainstem, cerebellum, basal ganglia and sensorimotor cortex and their interconnecting white matter pathways. Genotypic and motor phenotypic variation emerged, for example fewer cerebello-thalamic tractography streamlines in genetic forms than idiopathic and higher grey matter volumes in task-specific than non-task-specific dystonias. DISCUSSION: Work to date suggests microstructural brain changes in those diagnosed with dystonia, although the underlying nature of these changes remains undetermined. Employment of techniques such as multiple diffusion weightings or multi-exponential relaxometry has the potential to enhance understanding of these differences.

MRI: how to understand it.

MRI is a staple of the neurologist's armoury when facing diagnostic challenges. At times, it can reveal or confirm the diagnosis with clarity, at others it brings us no further forwards, or even muddies the water. We rely on the expertise of neuroradiology colleagues to interpret MR images, but the choice of protocol for MR acquisition and its interpretation hinge crucially on the clinical information we provide. Having a degree of understanding about how MRI works, its limitations and pitfalls, can help to optimise what we learn from a scan.

Pearls & Oy-sters: AARS2 Leukodystrophy-Tremor and Tribulations.

A 35-year-old woman with a progressive, bilateral upper limb tremor, personality change, behavioral disturbance, and primary ovarian insufficiency was found to have AARS2-related leukodystrophy. She had congenital nystagmus which evolved to head titubation by age 8 years and then developed an upper limb tremor in her mid-teens. These symptoms stabilized during her 20s, but soon after this presentation at age 35 years, neurologic and behavioral disturbances progressed rapidly over a 12-month period requiring transition to an assisted living facility with care support (4 visits/day) and assistance for all activities of daily living. MRI of the brain demonstrated confluent white matter changes predominantly involving the frontal lobes consistent with a leukodystrophy. All other investigations were unremarkable. Nongenetic causes of a leukodystrophy including sexually transmitted diseases and recreational drug use were excluded. Family history was negative for similar symptoms. Gene panel testing identified compound heterozygous pathogenic AARS2 mutations. This case highlights the importance of MRI brain imaging in progressive tremor syndromes, the utility of gene panels in simultaneous testing of multiple disorders with overlapping phenotypes, and the need for awareness of comorbid endocrinological disorders in many of the genetic leukodystrophies, whose identification may aid in clinical diagnosis.

White Matter Microstructural Changes Using Ultra-Strong Diffusion Gradient MRI in Adult-Onset Idiopathic Focal Cervical Dystonia.

BACKGROUND AND OBJECTIVES: Adult-onset idiopathic focal cervical dystonia (AOIFCD) involves abnormal posturing of the cervical musculature and, in some individuals, an associated head tremor. Existing neuroimaging studies have implicated key motor networks. However, measures used to date lack specificity toward underlying pathophysiologic differences. We aim to assess white matter motor pathways for localized, microstructural differences, which may aid in understanding underlying mechanisms. METHODS: Individuals diagnosed with AOIFCD and an age- and sex-matched control group were prospectively recruited through the Welsh Movement Disorders Research Network. All participants underwent in-depth clinical phenotyping and MRI (structural and diffusion sequences) using ultra-strong diffusion gradients. Tractography (whole-tract median values) and tractometry (along tract profiling) were performed for key white matter motor pathways assessing diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and standard model parameters. Groups were compared using linear model analysis with Bonferroni multiple comparison correction. RESULTS: Fifty participants with AOIFCD and 30 healthy control participants were recruited, with 46 with AOIFCD and 30 healthy controls included for analysis (33 without head tremor, 13 with head tremor). Significant differences were observed in the anterior thalamic radiations (lower mid-tract fractional anisotropy [estimate = -0.046, p = 3.07 × 10-3], radial kurtosis [estimate = -0.165, p = 1.42 × 10-4], f-intra-axonal signal fraction [estimate = -0.044, p = 2.78 × 10-3], p2 orientation coherence [estimate = -0.043, p = 1.64 × 10-3], higher Orientation Dispersion Index [ODI, estimate = 0.023, p = 2.22 × 10-3]) and thalamopremotor tracts (higher mid-tract mean kurtosis [estimate = 0.064, p = 7.56 × 10-4], lower Neurite Density Index [estimate = 0.062, p = 2.1 × 10-3], higher distal tract ODI [estimate = 0.062, p = 3.1 × 10-3], lower f [estimate = -0.1, p = 2.3 × 10-3], and striatopremotor tracts [proximal lower f: estimate = -0.075, p = 1.06 × 10-3]). These measures correlated with clinical measures: dystonia duration (right thalamopremotor distal ODI: r = -0.9, p = 1.29 × 10-14), psychiatric symptoms (obsessive compulsive symptoms: left anterior thalamic radiation p2 r = 0.92, p = 2.797 × 10-11), sleep quality (Sleep Disorders Questionnaire Score: left anterior thalamic radiation ODI: r = -0.84, p = 4.84 × 10-11), pain (left anterior thalamic radiation ODI: r = -0.89, p = 1.4 × 10-13), and cognitive functioning (paired associated learning task p2, r = 0.94, p = 6.68 × 10-20). DISCUSSION: Overall, localized microstructural differences were identified within tracts linking the prefrontal and premotor cortices with thalamic and basal ganglia regions, suggesting pathophysiologic processes involve microstructural aberrances of motor system modulatory pathways, particularly involving intra-axonal and fiber orientation dispersion measures.

Macro- and micro-structural insights into primary dystonia: a UK Biobank study.

BACKGROUND: Dystonia is a hyperkinetic movement disorder with key motor network dysfunction implicated in pathophysiology. The UK Biobank encompasses > 500,000 participants, of whom 42,565 underwent brain MRI scanning. This study applied an optimized pre-processing pipeline, aimed at better accounting for artifact and improving data reliability, to assess for grey and white matter structural MRI changes between individuals diagnosed with primary dystonia and an unaffected control cohort. METHODS: Individuals with dystonia (n = 76) were identified from the UK Biobank using published algorithms, alongside an age- and sex-matched unaffected control cohort (n = 311). Grey matter morphometric and diffusion measures were assessed, together with white matter diffusion tensor and diffusion kurtosis metrics using tractography and tractometry. Post-hoc Neurite Orientation and Density Distribution Imaging (NODDI) was also undertaken for tracts in which significant differences were observed. RESULTS: Grey matter tremor-specific striatal differences were observed, with higher radial kurtosis. Tractography identified no white matter differences, however segmental tractometry identified localised differences, particularly in the superior cerebellar peduncles and anterior thalamic radiations, including higher fractional anisotropy and lower orientation distribution index in dystonia, compared to controls. Additional tremor-specific changes included lower neurite density index in the anterior thalamic radiations. CONCLUSIONS: Analysis of imaging data from one of the largest dystonia cohorts to date demonstrates microstructural differences in cerebellar and thalamic white matter connections, with architectural differences such as less orientation dispersion potentially being a component of the morphological structural changes implicated in dystonia. Distinct tremor-related imaging features are also implicated in both grey and white matter.

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders.

Structural brain MRI has proven invaluable in understanding movement disorder pathophysiology. However, most work has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong spherical tensor encoding diffusion-weighted MRI, a persistent MRI signal was seen in healthy cerebellar grey matter even at high diffusion-weightings (b ​≥ 10,000 s/mm2). Quantifying the proportion of this signal (denoted fs), previously ascertained to originate from inside small spherical spaces, provides a potential proxy for cell body density. In this work, this approach was applied for the first time to a clinical cohort, including patients with diagnosed movement disorders in which the cerebellum has been implicated in symptom pathophysiology. Five control participants (control group 1, median age 24.5 years (20-39 years), imaged at two timepoints, demonstrated consistency in measurement of all three measures - MD (Mean Diffusivity) fs, and Ds (dot diffusivity)- with intraclass correlation coefficients (ICC) of 0.98, 0.86 and 0.76, respectively. Comparison with an older control group (control group 2 (n = 5), median age 51 years (43-58 years)) found no significant differences, neither with morphometric nor microstructural (MD (p = 0.36), fs (p = 0.17) and Ds (p = 0.22)) measures. The movement disorder cohort (Parkinson's Disease, n = 5, dystonia, n = 5. Spinocerebellar Ataxia 6, n = 5) when compared to the age-matched control cohort (Control Group 2) identified significantly lower MD (p < 0.0001 and p < 0.0001) and higher fs values (p < 0.0001 and p < 0.0001) in SCA6 and dystonia cohorts respectively. Lobar division of the cerebellum found these same differences in the superior and inferior posterior lobes, while no differences were seen in either the anterior lobes or with Ds measurements. In contrast to more conventional measures from diffusion tensor imaging, this framework provides enhanced specificity to differences in restricted spherical spaces in grey matter (including small cells) by eliminating signals from cerebrospinal fluid and axons. In the context of human and animal histopathology studies, these findings potentially implicate the cerebellar Purkinje and granule cells as contributors to the observed signal differences, with both cell types having been implicated in several neurological disorders through both postmortem and animal model studies. This novel microstructural imaging approach shows promise for improving movement disorder diagnosis, prognosis, and treatment.

Internet-based cognitive behavioural therapy as a feasible treatment of adult-onset, focal, isolated, idiopathic cervical dystonia.

INTRODUCTION: Psychiatric symptoms are well recognised co-morbid traits in adult-onset idiopathic, isolated, focal cervical dystonia (AOIFCD), although few studies have sought to address their management. Internet-based cognitive behavioural therapy (iCBT) may provide an accessible solution. Here, we determine the feasibility of using iCBT in the management of non-motor symptoms for individuals with AOIFCD. METHODS: Participants were randomised to receive an 8-week iCBT programme (n = 10) or not (n = 10), both alongside routine clinical care. All participants underwent assessments at baseline, 3-, and 6- months for anxiety, depression, quality of life and motor symptoms, and engagement with iCBT was recorded. Group differences over time were determined using two-way mixed ANOVA, and simple statistics evaluated change on an individual participant level. RESULTS: Over half of participants receiving iCBT (6/10) showed high engagement, with feedback indicating most participants found iCBT useful (6/8), would continue to use it (7/8), and try it again if offered (7/8). Although no between-group significant differences were observed (e.g. Beck's Depression Inventory p = 0.067) anxiety and depression levels showed trends towards improvement at 3-months in those receiving iCBT. Individual level analysis also indicated higher percentage level improvements in these symptoms, with this sustained in 86% participants. CONCLUSION: iCBT represents a feasible therapeutic option in the management of co-morbid anxiety and depression in AOIFCD. Further work is needed to replicate these findings in a larger cohort, identify those most likely to benefit from this form of therapy and overcome barriers hindering those less likely to engage with this form of treatment.

Filtration-Histogram Based Magnetic Resonance Texture Analysis (MRTA) for the Distinction of Primary Central Nervous System Lymphoma and Glioblastoma.

Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre-treatment MRI sequences (T1-weighted contrast-enhanced (T1CE), T2-weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2-6 mm) and unfiltered (SSF = 0) histogram parameters were compared using Mann-Whitney U non-parametric testing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with >1/3 necrosis masses, ADC permitted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE-derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross-sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction.

Seasonal variation in multiple sclerosis relapse.

Relapses are a characteristic clinical feature of multiple sclerosis (MS), but an appreciation of factors that cause them remains elusive. In this study, we have examined seasonal variation of relapse in a large population-based MS cohort and correlated observed patterns with age, sex, disease course, and climatic factors. Relapse data were recorded prospectively in 2076 patients between 2005 and 2014. 3902 events were recorded in 1158 patients (range 0-24). There was significant seasonal variation in relapse rates (p < 0.0001) and this was associated with monthly hours of sunshine (odds ratio OR 1.08, p = 0.02). Relapse rates were highest in patients under the age of 30 (OR 1.42, p = 0.0005) and decreased with age. There was no evidence of different relapse rates for males compared to females (OR 0.90, p = 0.19). Identification of potentially modifiable environmental factors associated with temporal variation in relapse rates may allow alteration of risk on a population basis and alteration of outcome of established disease once established. Future epidemiological studies should examine dynamic environmental factors with serial prospective measurements and biological sampling. Significant seasonal differences in relapse rates highlight the importance of environmental factors in disease expression and should be taken into account when planning clinical trials in which relapse frequency is an outcome. In addition, identification of potentially modifiable factors associated with this variation may offer unique opportunities for alteration of risk of relapse and long-term outcome on a population level, and suggest putative biological mechanisms for relapse initiation.

Association between the preoperative fasting and postprandial C-peptide AUC with resolution of type 2 diabetes 6 months following bariatric surgery.

BACKGROUND AND AIMS: Bariatric surgery results in the remission of type 2 diabetes mellitus (T2DM) in morbidly obese subjects. The aim of the study was to investigate the predictive value of both static and dynamic measures of C-peptide in relation to T2DM resolution 6 months after bariatric surgery regardless of the operation type. METHODS AND RESULTS: A non-randomized prospective study of 24 participants with T2DM undergoing bariatric surgery. Measurements of fasting and 2-hour plasma glucose, insulin, C-peptide and measures of insulin sensitivity were recorded temporally during an oral glucose tolerance test pre-operatively and 6 months post-operatively. A responder was defined with a fasting glucose <5.6 mmol/L and HbA1c <6.0% postoperatively. Within the sample there were 11 responders and 13 non-responders at 6 months. There was a significant difference in the duration of diabetes between the groups. Fasting C-peptide (P≤0.05) and 2-hour C-peptide (P≤0.05) were higher in responders compared to non-responders. Significantly higher C-peptide levels were observed preoperatively at all time points for responders, with significantly higher area under the curve (AUC0-60 and AUC0-120). Using the lower quartiles for C-peptide levels, both fasting C-peptide (>2.5 ng/mL [0.83 nmol/L]) and 2-hour C-peptide (>5.2 ng/mL [1.73 nmol/L]) had a sensitivity and negative predictive value of 100% to predict T2DM remission. Logistic regression showed that C-peptide, duration of diabetes and BMI were associated with response. The area under the ROC curve was 0.94 and a regression model predicted diabetes remission with a sensitivity of 85.7% and a specificity of 88.9%. CONCLUSIONS: This study demonstrated that static (fasting) and dynamic (AUC, 2-hour) C-peptide measurements predict T2DM resolution 6 months following bariatric surgery. This work provides insight into C-peptide dynamics as a predictor of response to bariatric surgery.