Abstract Background To evaluate the degeneration of the corticospinal tract (CST) and corpus callosum (CC) in patients with motor neuron disease and upper motor neuron (UMN) dysfunction using diffusion kurtosis imaging (DKI). Methods Twenty‐seven patients and 33 healthy controls underwent magnetic resonance imaging along with clinical and neuropsychological testing. Tractography of diffusion tensor images was performed to extract tracts of the bilateral CST and CC. Group mean differences both across the entire averaged tract and along each tract were assessed, including correlations between diffusion metrics and clinical measures. Tract‐based spatial statistics (TBSS) was performed to evaluate the spatial distribution of whole‐brain microstructural abnormalities in patients. Results In comparison to controls, patients had significantly higher mean and radial diffusivity and lower fractional anisotropy (FA), kurtosis anisotropy, mean kurtosis (MK), and radial kurtosis (RK) in the CST and CC (p < .017). Along‐the‐tract analysis revealed changes concentrated in the posterior limb of the internal capsule, corona radiata, and primary motor cortex (false‐discovery rate p < .05). FA of the left CST correlated with disease progression rate, whereas MK of the bilateral CST correlated with UMN burden (p < .01). TBSS results corroborated along‐tract analysis findings and additionally revealed reduced RK and MK in the fornix, where diffusion tensor imaging (DTI) changes were absent. Conclusion DKI abnormalities in the CST and CC are present in patients with UMN dysfunction, potentially revealing complementary information to DTI regarding the pathology and microstructural alterations occurring in such patients. DKI shows promise as a potential in vivo biomarker for cerebral degeneration in amyotrophic lateral sclerosis.

This study sought to evaluate the relationship of progressive corticospinal tract (CST) degeneration with survival in patients with amyotrophic lateral sclerosis (ALS).

OBJECTIVE:To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS).METHODS:52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants.RESULTS:Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex.CONCLUSION:In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.

Objective To evaluate progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) by assessing alterations in N-acetylaspartate (NAA) ratios in the motor and prefrontal cortex within clinical subgroups of ALS. Methods Seventy-six patients with ALS and 59 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium. Participants underwent serial clinical evaluations and magnetic resonance spectroscopy at baseline and 4 and 8 months using a harmonized protocol across 5 centers. NAA ratios were quantified in the motor cortex and prefrontal cortex. Patients were stratified into subgroups based on disease progression rate, upper motor neuron (UMN) signs, and cognitive status. Linear mixed models were used for baseline and longitudinal comparisons of NAA metabolite ratios. Results Patients with ALS had reduced NAA ratios in the motor cortex at baseline (p < 0.001). Ratios were lower in those with more rapid disease progression and greater UMN signs (p < 0.05). A longitudinal decline in NAA ratios was observed in the motor cortex in the rapidly progressing (p < 0.01) and high UMN burden (p < 0.01) cohorts. The severity of UMN signs did not change significantly over time. NAA ratios were reduced in the prefrontal cortex only in cognitively impaired patients (p < 0.05); prefrontal cortex metabolites did not change over time. Conclusions Progressive degeneration of the motor cortex in ALS is associated with more aggressive clinical presentations. These findings provide biological evidence of variable spatial and temporal cerebral degeneration linked to the disease heterogeneity of ALS. The use of standardized imaging protocols may have a role in clinical trials for patient selection or subgrouping. Classification of Evidence This study provides Class II evidence that MRS NAA metabolite ratios of the motor cortex are associated with more rapid disease progression and greater UMN signs in patients with ALS. Trial Registration Information ClinicalTrials.gov Identifier: NCT02405182.

Background: Several neuroimaging studies report structural alterations of the trigeminal nerve in trigeminal neuralgia (TN). Less attention has been paid to structural brain changes occurring in TN, even though such changes can influence the development and response to treatment of other headache and chronic pain conditions. The purpose of this study was to apply a novel neuroimaging technique—texture analysis—to identify structural brain differences between classical TN patients and healthy subjects.Methods: We prospectively recruited 14 medically refractory classical TN patients and 20 healthy subjects. 3-Tesla T1-weighted brain MRI scans were acquired in all participants. Three texture features (autocorrelation, contrast, energy) were calculated within four a priori brain regions of interest (anterior cingulate, insula, thalamus, brainstem). Voxel-wise analysis was used to identify clusters of texture difference between TN patients and healthy subjects within regions of interest (p < 0.001, cluster size >20 voxels). Median raw texture values within clusters were also compared between groups, and further used to differentiate TN patients from healthy subjects (receiver-operator characteristic curve analysis). Median raw texture values were correlated with pain severity (visual analog scale, 1–100) and illness duration.Results: Several clusters of texture difference were observed between TN patients and healthy subjects: right-sided TN patients showed reduced autocorrelation in the left brainstem, increased contrast in the left brainstem and right anterior insula, and reduced energy in right and left anterior cingulate, right midbrain, and left brainstem. Within-cluster median raw texture values also differed between TN patients and healthy subjects: TN patients could be segregated from healthy subjects using brainstem autocorrelation (p = 0.0040, AUC = 0.84, sensitivity = 89%, specificity = 70%), anterior insula contrast (p = 0.0002, AUC = 0.92, sensitivity = 78%, specificity = 100%), and anterior cingulate energy (p = 0.0004, AUC = 0.92, sensitivity = 78%, specificity = 100%). Additionally, anterior insula contrast and duration of TN were inversely correlated (p = 0.030, Spearman r = −0.73).Conclusions: Texture analysis reveals distinct brain abnormalities in TN, which relate to clinical features such as duration of illness. These findings further implicate structural brain changes in the development and maintenance of TN.

Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T0 ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T0 and Tmax (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at Tmax than at T0 . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.

We investigated cerebral degeneration and neurochemistry in patients with amyotrophic lateral sclerosis (ALS) using magnetic resonance spectroscopy (MRS).We prospectively studied 65 patients and 43 age-matched healthy controls. Participants were recruited from 4 centers as part of a study in the Canadian ALS Neuroimaging Consortium. All participants underwent single-voxel proton MRS using a protocol standardized across all sites. Metabolites reflecting neuronal integrity (total N-acetyl aspartyl moieties [tNAA]) and gliosis (myo-inositol [Ino]), as well as creatine (Cr) and choline (Cho), were quantified in the midline motor cortex and midline prefrontal cortex. Comparisons were made between patients with ALS and healthy controls. Metabolites were correlated with clinical measures of upper motor neuron dysfunction, disease progression rate, and cognitive performance.In the motor cortex, tNAA/Cr, tNAA/Cho, and tNAA/Ino ratios were reduced in the ALS group compared with controls. Group differences in tNAA/Cr and tNAA/Cho in the prefrontal cortex displayed reduced ratios in ALS patients; however, these were not statistically significant. Reduced motor cortex ratios were associated with slower foot tapping rate, whereas only motor tNAA/Ino was associated with finger tapping rate. Disease progression rate was associated with motor tNAA/Cho. Verbal fluency, semantic fluency, and digit span forwards and backwards were associated with prefrontal tNAA/Cr.This study demonstrates that cerebral degeneration in ALS is more pronounced in the motor than prefrontal cortex, that multicenter MRS studies are feasible, and that motor tNAA/Ino shows promise as a potential biomarker.

Background We investigated cerebral degeneration and neurochemistry in patients with amyo- trophic lateral sclerosis (ALS) using magnetic resonance spectroscopy (MRS). Methods We prospectively studied 65 patients and 43 age-matched healthy controls. Participants were recruited from 4 centers as part of a study in the Canadian ALS Neuroimaging Consortium. All participants underwent single-voxel proton MRS using a protocol standardized across all sites. Metabolites reflecting neuronal integrity (total N-acetyl aspartyl moieties [tNAA]) and gliosis (myo-inositol [Ino]), as well as creatine (Cr) and choline (Cho), were quantified in the midline motor cortex and midline prefrontal cortex. Comparisons were made between patients with ALS and healthy controls. Metabolites were correlated with clinical measures of upper motor neuron dysfunction, disease progression rate, and cognitive performance. Results In the motor cortex, tNAA/Cr, tNAA/Cho, and tNAA/Ino ratios were reduced in the ALS group compared with controls. Group differences in tNAA/Cr and tNAA/Cho in the prefrontal cortex displayed reduced ratios in ALS patients; however, these were not statistically significant. Reduced motor cortex ratios were associated with slower foot tapping rate, whereas only motor tNAA/Ino was associated with finger tapping rate. Disease progression rate was associated with motor tNAA/Cho. Verbal fluency, semantic fluency, and digit span forwards and backwards were associated with prefrontal tNAA/Cr. Conclusions This study demonstrates that cerebral degeneration in ALS is more pronounced in the motor than prefrontal cortex, that multicenter MRS studies are feasible, and that motor tNAA/Ino shows promise as a potential biomarker.

Liraglutide is a glucagon-like peptide-1 analogue approved for obesity management.In controlled clinical trials, high dose liraglutide (3.0 mg) has previously demonstrated efficacy and safety as a pharmacological option for weight loss in patients with obesity.The study objective was to describe various clinical scenarios where high dose liraglutide was used and led to positive outcomes in a tertiary bariatric clinic.Data was retrospectively collected from a review of patient charts.Unique cases of liraglutide use in both short-and longterm scenarios were reported.Short-term usage is observed in patients using liraglutide for weight loss prior to bariatric surgery or other medical treatments.Long-term liraglutide is used as an alternative to bariatric surgery or to treat weight recidivism in post-bariatric surgical patients.The experience in bariatric clinics has proved liraglutide is a useful adjunct to multidisciplinary diet and exercise interventions.

BackgroundTexture analysis (TA) is an image‐analysis technique that detects complex intervoxel statistical patterns. 3D TA has shown potential in detecting cerebral degeneration not perceptible to the human eye in many neurological disorders. The reliability of this method's application in a multicenter study is unknown.PurposeTo assess the intrasite and intersite reliability of a novel 3D TA method from data acquired systematically from the Canadian ALS Neuroimaging Consortium (CALSNIC).Study TypeProspective multicenter data with harmonized MR sequence parameters acquired from five sites.PopulationSix healthy subjects.Field Strength3T 3D‐MPRAGE and 3D‐SPGR T1‐weighted MRI of the brain.AssessmentVoxel‐based 3D TA was performed on the whole brain to produce texture maps.Statistical TestsIntra‐ and intersite reliability of texture features was assessed using a two‐way mixed‐effects model for intraclass correlation coefficients (ICC). ICCs were calculated in a region‐of‐interest (ROI) analysis of predetermined anatomically relevant areas. A voxelwise approach was used to assess the whole brain.ResultsIn the ROI analyses, intrasite reliability was excellent (ICC > 0.75) across most regions and texture features (autocorrelation [autoc], contrast [contr], energy [energ]). Intersite reliability was excellent for most regions with autoc, ranging from fair to excellent for contr, and ICCs ranging from poor to good (<0.40–0.75) for energ. Voxelwise analyses revealed a large range in ICC across the brain for both intrasite and intersite ICCs (0.0–0.90), with higher reliability in the cortical gray matter compared with deeper subcortical structures.Data ConclusionOverall, the reliability of 3D TA was highly dependent on texture feature, region studied, and method of analysis (ROI or voxelwise). Intrasite reproducibility was good to excellent, and better than intersite. ROI‐based analyses present higher reliability in comparison with voxelwise analyses. Autoc has overall excellent reliability. These factors might be considered when designing future 3D TA studies.Level of Evidence: 2Technical Efficacy: Stage 1J. Magn. Reson. Imaging 2020;51:1200–1209.

AbstractIntroductionCurrently, there are no tools that can accurately predict which patients with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD). Texture analysis uses image processing and statistical methods to identify patterns in voxel intensities that cannot be appreciated by visual inspection. Our main objective was to determine whether MRI texture could be used to predict conversion of MCI to AD.MethodsA method of 3‐dimensional, whole‐brain texture analysis was used to compute texture features from T1‐weighted MR images. To assess predictive value, texture changes were compared between MCI converters and nonconverters over a 3‐year observation period. A predictive model using texture and clinical factors was used to predict conversion of patients with MCI to AD. This model was then tested on ten randomly selected test groups from the data set.ResultsTexture features were found to be significantly different between normal controls (n = 225), patients with MCI (n = 382), and patients with AD (n = 183). A subset of the patients with MCI were used to compare between MCI converters (n = 98) and nonconverters (n = 106). A composite model including texture features, APOE‐ε4 genotype, Mini‐Mental Status Examination score, sex, and hippocampal occupancy resulted in an area under curve of 0.905. Application of the composite model to ten randomly selected test groups (nonconverters = 26, converters = 24) predicted MCI conversion with a mean accuracy of 76.2%.DiscussionEarly texture changes are detected in patients with MCI who eventually progress to AD dementia. Therefore, whole‐brain 3D texture analysis has the potential to predict progression of patients with MCI to AD.

Objective: To characterize cerebral degeneration in vivo in mild cognitive impairment (MCI) and Alzheimer’s Disease (AD) using MRI-based texture analysis and to determine whether MRI texture can be used to predict conversion of MCI to AD. Background: AD is a neurodegenerative disorder that is characterized by progressive cognitive decline. Currently, there are no tools that accurately predict which patients with MCI will progress to AD. Texture analysis utilizes image processing and statistical analysis methods to identify patterns in voxel intensities that can not be appreciated by visual inspection alone. Here we use texture analysis to determine early MRI changes in AD. Design/Methods: MRI and clinical data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used for this study. A novel method of 3-dimensional texture analysis (VGLCM-TOP-3D) was used to identify texture features in T1-weighted MR images. A voxel-wise statistical comparison of features between groups (controls, MCI, AD) was done to characterize spatial differences in cerebral degeneration. To assess its predictive value, texture changes were compared between patients with MCI who did or did not progress to AD over a 3 year observation period. Results: Texture features were significantly different (p Conclusions: MRI texture analysis revealed patterns of cerebral degeneration that differentiates subjects according to their clinical status (control, MCI, AD). Further, early texture changes are detected in those MCI patients that eventually progress to AD dementia. Therefore, whole brain 3-dimensional texture analysis has the potential to predict progression of MCI to AD. Disclosure: Dr. Luk has nothing to disclose. Dr. Ishaque has nothing to disclose. Dr. Khan has nothing to disclose. Dr. Ta has nothing to disclose. Dr. Mah has nothing to disclose. Dr. Yang has nothing to disclose. Dr. Kalra has nothing to disclose.