Objective:To evaluate progressive white matter (WM) degeneration in ALS.Methods:Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicentre study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centres including diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALSFRS-R) and upper motor neuron (UMN) function. Voxel-wise whole brain and quantitative tractwise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers that underwent the DTI protocol at each centre.Results:ALS patients had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tractwise analysis revealed reduced FA in the CST, corticopontine/corticorubral and corticostriatal tracts. CST FA correlated with UMN function and frontal lobe FA with the ALSFRS-R. A progressive decline in CST FA correlated with a decline in the ALSFRS-R and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe.Conclusions:Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes, and to a lesser degree in the corticopontine/corticorubral tracts and the corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytical methods to address site-related variances, this study is an important milestone towards developing DTI biomarkers for cerebral degeneration in ALS.

Introduction Currently, 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. Methods A 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. Results Texture 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%. Discussion Early 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.

The purpose of this study was to investigate whether textures computed from T1‐weighted (T1W) images of the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS) are associated with degenerative changes evaluated by diffusion tensor imaging (DTI). Nineteen patients with ALS and 14 controls were prospectively recruited and underwent T1W and diffusion‐weighted magnetic resonance imaging. Three‐dimensional texture maps were computed from T1W images and correlated with the DTI metrics within the CST. Significantly correlated textures were selected and compared within the CST for group differences between patients and controls using voxel‐wise analysis. Textures were correlated with the patients' clinical upper motor neuron (UMN) signs and their diagnostic accuracy was evaluated. Voxel‐wise analysis of textures and their diagnostic performance were then assessed in an independent cohort with 26 patients and 13 controls. Results showed that textures autocorrelation, energy, and inverse difference normalized significantly correlated with DTI metrics (p < .05) and these textures were selected for further analyses. The textures demonstrated significant voxel‐wise differences between patients and controls in the centrum semiovale and the posterior limb of the internal capsule bilaterally (p < .05). Autocorrelation and energy significantly correlated with UMN burden in patients (p < .05) and classified patients and controls with 97% accuracy (100% sensitivity, 92.9% specificity). In the independent cohort, the selected textures demonstrated similar regional differences between patients and controls and classified participants with 94.9% accuracy. These results provide evidence that T1‐based textures are associated with degenerative changes in the CST.

Research in amyotrophic lateral sclerosis (ALS) suggests that executive dysfunction, a prevalent cognitive feature of the disease, is associated with abnormal structural connectivity and white matter integrity. In this exploratory study, we investigated the white matter constructs of executive dysfunction, and attempted to detect structural abnormalities specific to cognitively impaired ALS patients. Eighteen ALS patients and 22 age and education matched healthy controls underwent magnetic resonance imaging on a 4.7 Tesla scanner and completed neuropsychometric testing. ALS patients were categorized into ALS cognitively impaired (ALSci, n = 9) and ALS cognitively competent (ALScc, n = 5) groups. Tract-based spatial statistics and connectomics were used to compare white matter integrity and structural connectivity of ALSci and ALScc patients. Executive function performance was correlated with white matter FA and network metrics within the ALS group. Executive function performance in the ALS group correlated with global and local network properties, as well as FA, in regions throughout the brain, with a high predilection for the frontal lobe. ALSci patients displayed altered local connectivity and structural integrity in these same frontal regions that correlated with executive dysfunction. Our results suggest that executive dysfunction in ALS is related to frontal network disconnectivity, which potentially mediates domain-specific, or generalized cognitive impairment, depending on the degree of global network disruption. Furthermore, reported co-localization of decreased network connectivity and diminished white matter integrity suggests white matter pathology underlies this topological disruption. We conclude that executive dysfunction in ALSci is associated with frontal and global network disconnectivity, underlined by diminished white matter integrity. Hum Brain Mapp 38:1249-1268, 2017. © 2016 Wiley Periodicals, Inc.

ObjectiveTo evaluate cerebral degenerative changes in ALS and their correlates with survival using 3D texture analysis.MethodsA total of 157 participants were included in this analysis from four neuroimaging studies. Voxel‐wise texture analysis on T1‐weighted brain magnetic resonance images (MRIs) was conducted between patients and controls. Patients were divided into long‐ and short‐survivors using the median survival of the cohort. Neuroanatomical differences between the two survival groups were also investigated.ResultsWhole‐brain analysis revealed significant changes in image texture (FDR P < 0.05) bilaterally in the motor cortex, corticospinal tract (CST), insula, basal ganglia, hippocampus, and frontal regions including subcortical white matter. The texture of the CST correlated (P < 0.05) with finger‐ and foot‐tapping rate, measures of upper motor neuron function. Patients with a survival below the media of 19.5 months demonstrated texture change (FDR P < 0.05) in the motor cortex, CST, basal ganglia, and the hippocampus, a distribution which corresponds to stage 4 of the distribution TDP‐43 pathology in ALS. Patients with longer survival exhibited texture changes restricted to motor regions, including the motor cortex and the CST.InterpretationWidespread gray and white matter pathology is evident in ALS, as revealed by texture analysis of conventional T1‐weighted MRI. Length of survival in patients with ALS is associated with the spatial extent of cerebral degeneration.

Background: Amyotrophic lateral sclerosis (ALS) is a disabling and rapidly progressive neurodegenerative disorder. Increasing age is an important risk factor for developing ALS, thus the societal impact of this devastating disease will become more profound as the population ages. A significant hurdle to finding effective treatment has been an inability to accurately quantify cerebral degeneration associated with ALS in humans. Advanced magnetic resonance imaging (MRI) techniques hold promise in providing a set of biomarkers to assist in aiding diagnosis and in efficiently evaluating new drugs to treat ALS. Methods: The Canadian ALS Neuroimaging Consortium (CALSNIC) was founded to develop and evaluate advanced MRI-based biomarkers that delineate biological heterogeneity, track disease progression, and predict survival in a large and heterogeneous sample of ALS patients. Findings: CALSNIC has launched two studies to date (CALSINC-1, CALSNIC-2), acquiring multimodal neuroimaging, neurological, neuropsychological data, and neuropathological data from ALS patients and healthy controls in a prospective and longitudinal fashion from multiple centres in Canada and, more recently, the United States. Clinical and MRI protocols are harmonized across research centres and different MR vendors. Interpretation: CALSNIC provides a multicentre platform for studying ALS biology and developing MRI-based biomarkers. Funding: Canadian Institutes of Health Research, ALS Society of Canada, Brain Canada Foundation, Shelly Mrkonjic Research Fund

Clinician-scientists are physicians with training in both clinical medicine and research that enables them to occupy a unique niche as specialists in basic and translational biomedical research. While there is widespread acknowledgement of the importance of clinician-scientists in today's landscape of evidence-based medical practice, training of clinician-scientists in Canada has been on the decline, with fewer opportunities to obtain funding. With the increasing length of training and lower financial compensation, fewer medical graduates are choosing to pursue such a career. MD-PhD programs, in which trainees receive both medical and research training, have the potential to be an important tool in training the next generation of clinician-scientists; however, MD-PhD trainees in Canada face barriers that include an increase in medical school tuition and a decrease in the amount of financial support. We examined the available data on MD-PhD training in Canada and identified a lack of oversight, a lack of funding and poor mentorship as barriers experienced by MD-PhD trainees. Specific recommendations are provided to begin the process of addressing these challenges, starting with the establishment of an overseeing national body that would track long-term outcome data for MD-PhD trainees. This national body could then function to implement best practices from individual programs across the country and to provide further mentorship and support for early-career physician-scientists. MD-PhD programs have the potential to address Canada's growing shortage of clinician-scientists, and strengthening MD-PhD programs will help to effect positive change. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45

Background: Most of the studies of obesity and postoperative outcome have looked predominantly at coronary artery bypass grafting with fewer focused on valvular disease. The purpose of this study was to compare the outcomes of patients undergoing aortic valve replacement stratified by body mass index (BMI, kg/m^2). Methods: The Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease registry captured 4780 aortic valve replacements in Alberta, Canada from January 2004 to December 2018. All recipients were stratified by BMI into five groups (BMI: < 20, 20-24.9, 25-29.9, 30-34.9, and > = 35). Log-rank test and Cox regression were used to examine the crude and adjusted survival differences. Results: Intra-operative clamp time and pump time were similar among the five groups. Significant statistical differences between groups existed for the incidence of isolated AVR, AVR and CABG, hemorrhage, septic infection, and deep sternal infection (p < 0.05). While there was no significant statistical difference in the mortality rate across the BMI groups, the underweight AVR patients (BMI < 20) were associated with increased hazard ratio (1.519; 95% confidence interval: 1.028-2.245) with regards to all-cause mortality at the longest follow-up compared with normal weight patients. Conclusion: Overweight and obese patients should be considered as readily for AVR as normal BMI patients.