Imaging protocols for non-traumatic spinal cord injury: current state of the art and future directions.

INTRODUCTION: Non-traumatic spinal cord injury (NTSCI) is a term used to describe damage to the spinal cord from sources other than trauma. Neuroimaging techniques such as computerized tomography (CT) and magnetic resonance imaging (MRI) have improved our ability to diagnose and manage NTSCIs. Several practice guidelines utilize MRI in the diagnostic evaluation of traumatic and non-traumatic SCI to direct surgical intervention. AREAS COVERED: The authors review practices surrounding the imaging of various causes of NTSCI as well as recent advances and future directions for the use of novel imaging modalities in this realm. The authors also present discussions around the use of simple radiographs and advanced MRI modalities in clinical settings, and briefly highlight areas of active research that seek to advance our understanding and improve patient care. EXPERT OPINION: Although several obstacles must be overcome, it appears highly likely that novel quantitative imaging features and advancements in artificial intelligence (AI) as well as machine learning (ML) will revolutionize degenerative cervical myelopathy (DCM) care by providing earlier diagnosis, accurate localization, monitoring for deterioration and neurological recovery, outcome prediction, and standardized practice. Some intriguing findings in these areas have been published, including the identification of possible serum and cerebrospinal fluid biomarkers, which are currently in the early phases of translation.

Characterization of white matter alterations using diffusion kurtosis imaging in patients with amyotrophic lateral sclerosis.

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.

Severity of in vivo corticospinal tract degeneration is associated with survival in amyotrophic lateral sclerosis: a longitudinal, multicohort study.

BACKGROUND AND PURPOSE: This study sought to evaluate the relationship of progressive corticospinal tract (CST) degeneration with survival in patients with amyotrophic lateral sclerosis (ALS). METHODS: Forty-one ALS patients and 42 healthy controls were prospectively recruited from the Canadian ALS Neuroimaging Consortium. Magnetic resonance imaging scanning and clinical evaluations were performed on participants at three serial visits with 4-month intervals. Texture analysis was performed on T1-weighted magnetic resonance imaging scans and the texture feature 'autocorrelation' was quantified. Whole-brain group-level comparisons were performed between patient subgroups. Linear mixed models were used to evaluate longitudinal progression. Region-of-interest and 3D voxel-wise Cox proportional-hazards regression models were constructed for survival prediction. For all survival analyses, a second independent cohort was used for model validation. RESULTS: Autocorrelation of the bilateral CST was increased at baseline and progressively increased over time at a faster rate in ALS short survivors. Cox proportional-hazards regression analyses revealed autocorrelation of the CST as a significant predictor of survival at 5 years follow-up (hazard ratio 1.28, p = 0.005). Similarly, voxel-wise whole-brain survival analyses revealed that increased autocorrelation of the CST was associated with shorter survival. ALS patients stratified by median autocorrelation in the CST had significantly different survival times using the Kaplan-Meier curve and log-rank tests (χ2  = 7.402, p = 0.007). CONCLUSIONS: Severity of cerebral degeneration is associated with survival in ALS. CST degeneration progresses faster in subgroups of patients with shorter survival. Neuroimaging holds promise as a tool to improve patient management and facilitation of clinical trials.

Motor cortex functional connectivity is associated with underlying neurochemistry in 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.

Comparison of Prognostic Scoring Systems to Predict Durable Pain Relief After Microvascular Decompression for Trigeminal Neuralgia.

BACKGROUND: Microvascular decompression (MVD) is an effective treatment for trigeminal neuralgia, but pain recurs in a substantial minority of patients. Two recently published scoring systems by Hardaway et al. and Panczykowski et al. use simple preoperative clinical and imaging features to predict durable pain relief following MVD, but their predictive performance has not been independently validated. This study aimed to compare predictive performance of the Hardaway et al. score (HS) and Panczykowski et al. score (PS) for 1-year, 3-year, and long-term pain-free outcomes after MVD for trigeminal neuralgia. METHODS: HS and PS were computed for a retrospective, single-institution cohort of 68 patients with trigeminal neuralgia who underwent MVD. Primary outcome was pain recurrence after MVD. Predictive performance of HSs and PSs was evaluated with area under the curve sensitivity analysis and regression models for survival analyses at 1 year, 3 years, and last follow-up. RESULTS: Area under the curve for predicting pain-free outcome was higher for PS versus HS at 1 year (0.873 vs. 0.775) and 3 years (0.793 vs. 0.704). Cox proportional hazard models showed that PS better predicted long-term pain-free outcomes compared with HS (P < 0.05). One-year pain-free outcome was best predicted by pain type; longer-term outcomes were better predicted by presence and degree of neurovascular compression on preoperative imaging. CONCLUSIONS: PS is superior to HS in predicting pain-free outcomes after MVD, which may aid in patient selection and counseling. Overall, more significant neurovascular compression of the trigeminal nerve root, and to a lesser extent classical paroxysmal pain, are good predictors of durable pain relief after MVD.

Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis.

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.

Progressive Neurochemical Abnormalities in Cognitive and Motor Subgroups of Amyotrophic Lateral Sclerosis: A Prospective Multicenter Study.

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.

Magnetic resonance imaging analysis of human skull diploic venous anatomy.

BACKGROUND: The skull diploic venous space (DVS) represents a potential route for cerebrospinal fluid (CSF) diversion and absorption in the treatment of hydrocephalus. The goal of this study was to carry out a detailed characterization of the drainage pattern of the DVS of the skull using high-resolution MRI, especially the diploic veins draining to the lacunae laterales (LLs) since the LLs constitute an important channel for the CSF to access the superior sagittal sinus and subsequently the systemic circulation. The objective was to identify those skull regions optimally suited for an intraosseous CSF diversion system. METHODS: High-resolution, T1-weighted MRI scans from 20 adult and 16 pediatric subjects were selected for analysis. Skulls were divided into four regions, that is, frontal, parietal, temporal, and occipital. On each scan, a trained observer counted all diploic veins in every skull region. Each diploic vein was also followed to determine its final drainage pathway (i.e., dural venous sinus, dural vein, LL, or indeterminate). RESULTS: In the adult age group, the frontal and occipital skull regions showed the highest number of diploic veins. However, the highest number of draining diploic veins connecting to the lacunae lateralis was found in the frontal and parietal skull region, just anterior and just posterior to the coronal suture. In the pediatric age group, the parietal skull region, just posterior to the coronal suture, showed the highest overall number of diploic veins and also the highest number of draining diploic veins connecting to the LL. CONCLUSION: This study suggested that diploic venous density across the skull varies with age, with more parietal diploic veins in the pediatric age range, and more occipital and frontal diploic veins in adults. If the DVS is ultimately used for CSF diversion, our anatomical data point to optimal sites for the insertion of specially designed intraosseous infusion devices for the treatment of hydrocephalus. Likely the optimal sites for CSF diversion would be the parietal region just posterior to the coronal suture in children, and in adults, frontal and/or parietal just anterior or just posterior to the coronal suture.

MRI Texture Analysis Reveals Brain Abnormalities in Medically Refractory Trigeminal Neuralgia.

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.

Neuroanatomical associations of the Edinburgh cognitive and Behavioural ALS screen (ECAS).

Cognitive impairment is now recognized in a subset of patients with amyotrophic lateral sclerosis (ALS). The objective of the study was to identify group differences and neuroanatomical correlates of the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) in participants ALS. Fifty-three ALS patients and 43 healthy controls recruited as a part of our multicentre study (CALSNIC) were administered the ECAS and underwent an MRI scan. Voxel-based morphometry and tract based spatial statistics (TBSS) was performed to identify structural changes and associations with impaired ECAS scores. Lower performance in the ECAS verbal fluency and executive domains were noted in ALS patients as compared to controls (p < 0.01). Extensive white matter degeneration was noted in the corticospinal tract in all ALS patients, while ALS patients with impaired verbal fluency or executive domains (ALS-exi, n = 22), displayed additional degeneration in the corpus callosum, cingulum and superior longitudinal fasciculus as compared to controls (p < 0.05, TFCE corrected). Mild grey matter changes and associations with ECAS verbal fluency or executive performance were noted at lenient statistical thresholds (p < 0.001, uncorrected). Executive impairment was detected using the ECAS in our multicentre sample of Canadian ALS patients. White matter degeneration in motor regions was revealed in ALS patients with extensive spread to frontal regions in the ALS-exi sub-group. Mild associations between ECAS verbal fluency, executive function scores and MRI metrics suggest that reduced performance may be associated with widespread structural integrity.

A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS.

OBJECTIVE: To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS). METHODS: Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center. RESULTS: Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score 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 corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS. CLINICALTRIALSGOV IDENTIFIER: NCT02405182.

The effects of body mass index on outcomes for patients undergoing surgical aortic valve replacement.

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.

Reliability of 3D texture analysis: A multicenter MRI study of the brain.

BACKGROUND: Texture 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. PURPOSE: To assess the intrasite and intersite reliability of a novel 3D TA method from data acquired systematically from the Canadian ALS Neuroimaging Consortium (CALSNIC). STUDY TYPE: Prospective multicenter data with harmonized MR sequence parameters acquired from five sites. POPULATION: Six healthy subjects. FIELD STRENGTH: 3T 3D-MPRAGE and 3D-SPGR T1 -weighted MRI of the brain. ASSESSMENT: Voxel-based 3D TA was performed on the whole brain to produce texture maps. STATISTICAL TESTS: Intra- 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. RESULTS: In 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 CONCLUSION: Overall, 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: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1200-1209.

Quantifying changes on susceptibility weighted images in amyotrophic lateral sclerosis using MRI texture analysis.

Objective: Susceptibility-weighted imaging (SWI) has been used to identify neurodegeneration in amyotrophic lateral sclerosis (ALS) through qualitative gross visual comparison of signal intensity. The aim of this study was to quantitatively identify cerebral degeneration in ALS on SWI using texture analysis. Methods: SW images were acquired from 17 ALS patients (58.4 ± 10.3 years, 13M/4F, ALSFRS-R 41.2 ± 4.1) and 18 healthy controls (56.3 ± 17.6 years, 9M/9F) at 4.7 tesla. Textures were computed within the precentral gyrus and basal ganglia and compared between patients and controls using ANCOVA with age and gender as covariates. Texture features were correlated with clinical measures in patients. Texture features found to be significantly different between patients and controls in the precentral gyrus were then used in a whole-brain 3D texture analysis. Results: The texture feature autocorrelation was significantly higher in ALS patients compared to healthy controls in the precentral gyrus and basal ganglia (p < 0.05). Autocorrelation correlated significantly with clinical measures such as disease progression rate and finger tapping speed (p < 0.05). Whole brain 3D texture analysis using autocorrelation revealed differences between ALS patients and controls within the precentral gyrus on SWI images (p < 0.001). Conclusion: Texture analysis on SWI can quantitatively identify cerebral differences between ALS patients and controls.

Corticospinal tract degeneration in ALS unmasked in T1-weighted images using texture analysis.

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.

Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis.

OBJECTIVE: To evaluate cerebral degenerative changes in ALS and their correlates with survival using 3D texture analysis. METHODS: A 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. RESULTS: Whole-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. INTERPRETATION: Widespread 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.

Alzheimer's disease: 3-Dimensional MRI texture for prediction of conversion from mild cognitive impairment.

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.

Scientific overview on CSCI-CITAC Annual General Meeting and 2017 Young Investigators' Forum.

The 2017 Annual General Meeting of the Canadian Society of Clinician Investigators (CSCI) and Clinician Investigator Trainee Association of Canada/Association des Cliniciens-Chercheurs en Formation du Canada (CITAC/ACCFC) was a national Annual General Meeting (AGM) held in Toronto, Ontario November 20-22, 2017, in conjunction with the University of Toronto Clinician Investigator Program Research Day. The theme for this year's meeting was "Roll up your sleeves-How to manage your physician scientist career", emphasizing lectures and workshops that were designed to provide tools for being proactive and successful in career planning. The keynote speakers were Dr. Rod McInnes (McGill University and Canadian Institutes of Health Research Acting President), who was the Distinguished Scientist Award recipient, Dr. David Goltzman (McGill University), who was the 2017 Henry Friesen Award recipient, Dr. Gillian Hawker (University of Toronto), Dr. Mike Sapieha (Université de Montréal), who was the 2017 Joe Doupe Award recipient, and Dr. Alex MacKenzie (Children's Hospital of Eastern Ontario Research Institute, University of Ottawa). The workshops, focusing on career development for clinician scientists, were hosted by Dr. Lisa Robinson, Dr. Nicola Jones, Kevin Vuong, Fran Brunelle, Dr. Jason Berman and Dr. Alan Underhill. Further to this, the Young Investigators' Forum encompasses presentations from scientist-clinician trainees from across the country. All scientific abstracts are summarized in this review. There were over 100 abstracts showcased at this year's meeting during the highlighted poster sessions, with six outstanding abstracts selected for oral presentations during the President's Forum.