Early Onset Diffusion Abnormalities in Refractory Headache Disorders.

Objective: This study sought to determine if individuals with medically refractory migraine headache have volume or diffusion abnormalities on neuroimaging compared to neurotypical individuals. Background: Neuroimaging biomarkers in headache medicine continue to be limited. Early prediction of medically refractory headache and migraine disorders could result in earlier administration of high efficacy therapeutics. Methods: A single-center, retrospective, case control study was performed. All patients were evaluated clinically between 2014 and 2018. Individuals with medically refractory migraine headache (defined by ICDH-3 criteria) without any other chronic medical diseases were enrolled. Patients had to have failed more than two therapeutics and aura was not exclusionary. The initial MRI study for each patient was reviewed. Multiple brain regions were analyzed for volume and apparent diffusion coefficient values. These were compared to 81 neurotypical control patients. Results: A total of 79 patients with medically refractory migraine headache were included and compared to 74 neurotypical controls without headache disorders. Time between clinical diagnosis and neuroimaging was a median of 24 months (IQR: 12.0-37.0). Comparison of individuals with medically refractory migraine headache to controls revealed statistically significant differences in median apparent diffusion coefficient (ADC) in multiple brain subregions (p < 0.001). Post-hoc pair-wise analysis comparing individuals with medically refractory migraine headache to control patients revealed significantly decreased median ADC values for the thalamus, caudate, putamen, pallidum, amygdala, brainstem, and cerebral white matter. No volumetric differences were observed between groups. Conclusions: In individuals with medically refractory MH, ADC changes are measurable in multiple brain structures at an early age, prior to the failure of multiple pharmacologic interventions and the diagnosis of medically refractory MH. This data supports the hypothesis that structural connectivity issues may predispose some patients toward more medically refractory pain disorders such as MH.

Attention-guided deep learning for gestational age prediction using fetal brain MRI.

Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly changing appearance of the fetal brain, variable image quality, and frequent motion artifacts. Here we present an end-to-end, attention-guided deep learning model that predicts gestational age with R2 score of 0.945, mean absolute error of 6.7 days, and concordance correlation coefficient of 0.970. The convolutional neural network was trained on a heterogeneous dataset of 741 developmentally normal fetal brain images ranging from 19 to 39 weeks in gestational age. We also demonstrate model performance and generalizability using independent datasets from four academic institutions across the U.S. and Turkey with R2 scores of 0.81-0.90 after minimal fine-tuning. The proposed regression algorithm provides an automated machine-enabled tool with the potential to better characterize in utero neurodevelopment and guide real-time gestational age estimation after the first trimester.

Effects of Age on White Matter Microstructure in Children With Neurofibromatosis Type 1.

Children with neurofibromatosis type 1 (NF1) often report cognitive challenges, though the etiology of such remains an area of active investigation. With the advent of treatments that may affect white matter microstructure, understanding the effects of age on white matter aberrancies in NF1 becomes crucial in determining the timing of such therapeutic interventions. A cross-sectional study was performed with diffusion tensor imaging from 18 NF1 children and 26 age-matched controls. Fractional anisotropy was determined by region of interest analyses for both groups over the corpus callosum, cingulate, and bilateral frontal and temporal white matter regions. Two-way analyses of variance were done with both ages combined and age-stratified into early childhood, middle childhood, and adolescence. Significant differences in fractional anisotropy between NF1 and controls were seen in the corpus callosum and frontal white matter regions when ages were combined. When stratified by age, we found that this difference was largely driven by the early childhood (1-5.9 years) and middle childhood (6-11.9 years) age groups, whereas no significant differences were appreciable in the adolescence age group (12-18 years). This study demonstrates age-related effects on white matter microstructure disorganization in NF1, suggesting that the appropriate timing of therapeutic intervention may be in early childhood.

Association of Pediatric Acute-Onset Neuropsychiatric Syndrome With Microstructural Differences in Brain Regions Detected via Diffusion-Weighted Magnetic Resonance Imaging.

Importance: Epidemiological studies indicate a link between obsessive-compulsive disorder and infections, particularly streptococcal pharyngitis. Pediatric acute-onset neuropsychiatric syndrome (PANS) manifests suddenly with obsessions, compulsions, and other behavioral disturbances, often after an infectious trigger. The current working model suggests a unifying inflammatory process involving the central nervous system, particularly the basal ganglia. Objective: To investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects microstructural abnormalities across the brain regions of children with PANS. Design, Setting, and Participants: Case-control study performed at a single-center, multidisciplinary clinic in the United States focusing on the evaluation and treatment of children with PANS. Sixty consecutive patients who underwent 3 Tesla (T) magnetic resonance imaging (MRI) before immunomodulation from September 3, 2012, to March 30, 2018, were retrospectively reviewed for study inclusion. Six patients were excluded by blinded investigators because of imaging or motion artifacts, 3 patients for major pathologies, and 17 patients for suboptimal atlas image registration. In total, 34 patients with PANS before initiation of treatment were compared with 64 pediatric control participants. Main Outcomes and Measures: Using atlas-based MRI analysis, regional brain volume, diffusion, and cerebral blood flow were measured in the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem. An age and sex-controlled multivariable analysis of covariance was used to compare patients with control participants. Results: This study compared 34 patients with PANS (median age, 154 months; age range, 55-251 months; 17 girls and 17 boys) and 64 pediatric control participants (median age, 139 months; age range, 48-213 months); 41 girls and 23 boys). Multivariable analysis demonstrated a statistically significant difference in MRI parameters between patients with PANS and control participants (F21,74 = 6.91; P < .001; partial η2 = 0.662). All assessed brain regions had statistically significantly increased median diffusivity compared with 64 control participants. Specifically, the deep gray matter (eg, the thalamus, basal ganglia, and amygdala) demonstrated the most profound increases in diffusivity consistent with the cardinal clinical symptoms of obsessions, compulsions, emotional dysregulation, and sleep disturbances. No statistically significant differences were found regarding volume and cerebral blood flow. Conclusions and Relevance: This study identifies cerebral microstructural differences in children with PANS in multiple brain structures, including the deep gray matter structures (eg, the thalamus, basal ganglia, and amygdala). Further study of MRI is warranted in prospective, clinical trials as a potential quantitative method for assessing patients under evaluation for PANS.

Age-Dependent White Matter Characteristics of the Cerebellar Peduncles from Infancy Through Adolescence.

Cerebellum-cerebrum connections are essential for many motor and cognitive functions and cerebellar disorders are prevalent in childhood. The middle (MCP), inferior (ICP), and superior cerebellar peduncles (SCP) are the major white matter pathways that permit communication between the cerebellum and the cerebrum. Knowledge about the microstructural properties of these cerebellar peduncles across childhood is limited. Here, we report on a diffusion magnetic resonance imaging tractography study to describe age-dependent characteristics of the cerebellar peduncles in a cross-sectional sample of infants, children, and adolescents from newborn to 17 years of age (N = 113). Scans were collected as part of clinical care; participants were restricted to those whose scans showed no abnormal findings and whose history and exam had no risk factors for cerebellar abnormalities. A novel automated tractography protocol was applied. Results showed that mean tract-FA increased, while mean tract-MD decreased from infancy to adolescence in all peduncles. Rapid changes were observed in both diffusion measures in the first 24 months of life, followed by gradual change at older ages. The shape of the tract profiles was similar across ages for all peduncles. These data are the first to characterize the variability of diffusion properties both across and within cerebellar white matter pathways that occur from birth through later adolescence. The data represent a rich normative data set against which white matter alterations seen in children with posterior fossa conditions can be compared. Ultimately, the data will facilitate the identification of sensitive biomarkers of cerebellar abnormalities.