Explore the vast range of titles available.

Multi-site MRI studies are often necessary for recruiting sufficiently sized samples when studying rare conditions. However, they require pooling data from multiple scanners into a single data set, and therefore it is critical to evaluate the variability of quantitative MRI measures within and across scanners used in multi-site studies. The aim of this study was to evaluate the reproducibility of structural and diffusion weighted (DW) MRI measurements acquired on seven scanners at five medical centers as part of the Tuberous Sclerosis Complex Autism Center of Excellence Research Network (TACERN) multisite study. The American College of Radiology (ACR) phantom was imaged monthly to measure reproducibility of signal intensity and uniformity within and across seven 3T scanners from General Electric, Philips, and Siemens vendors. One healthy adult male volunteer was imaged repeatedly on all seven scanners under the TACERN structural and DW protocol (5 b = 0 s/mm and 30 b = 1000 s/mm ) over a period of 5 years (age 22-27 years). Reproducibility of inter- and intra-scanner brain segmentation volumes and diffusion tensor imaging metrics fractional anisotropy (FA) and mean diffusivity (MD) within white matter regions was quantified with coefficient of variation. The American College of Radiology Phantom signal intensity and uniformity were similar across scanners and changed little over time, with a mean intra-scanner coefficient of variation of 3.6 and 1.8%, respectively. The mean inter- and intra-scanner coefficients of variation of brain structure volumes derived from T1-weighted (T1w) images of the human phantom were 3.3 and 1.1%, respectively. The mean inter- and intra-scanner coefficients of variation of FA in white matter regions were 4.5 and 2.5%, while the mean inter- and intra-scanner coefficients of variation of MD in white matter regions were 5.4 and 1.5%. Our results suggest that volumetric and diffusion tensor imaging (DTI) measurements are highly reproducible between and within scanners and provide typical variation amplitudes that can be used as references to interpret future findings in the TACERN network.

Background Autism spectrum disorder (ASD) is prevalent in tuberous sclerosis complex (TSC), occurring in approximately 50% of patients, and is hypothesized to be caused by disruption of neural circuits early in life. Tubers, or benign hamartomas distributed stochastically throughout the brain, are the most conspicuous of TSC neuropathology, but have not been consistently associated with ASD. Widespread neuropathology of the white matter, including deficits in myelination, neuronal migration, and axon formation, exist and may underlie ASD in TSC. We sought to identify the neural circuits associated with ASD in TSC by identifying white matter microstructural deficits in a prospectively recruited, longitudinally studied cohort of TSC infants. Methods TSC infants were recruited within their first year of life and longitudinally imaged at time of recruitment, 12 months of age, and at 24 months of age. Autism was diagnosed at 24 months of age with the ADOS-2. There were 108 subjects (62 TSC-ASD, 55% male; 46 TSC+ASD, 52% male) with at least one MRI and a 24-month ADOS, for a total of 187 MRI scans analyzed (109 TSC-ASD; 78 TSC+ASD). Diffusion tensor imaging properties of multiple white matter fiber bundles were sampled using a region of interest approach. Linear mixed effects modeling was performed to test the hypothesis that infants who develop ASD exhibit poor white matter microstructural integrity over the first 2 years of life compared to those who do not develop ASD. Results Subjects with TSC and ASD exhibited reduced fractional anisotropy in 9 of 17 white matter regions, sampled from the arcuate fasciculus, cingulum, corpus callosum, anterior limbs of the internal capsule, and the sagittal stratum, over the first 2 years of life compared to TSC subjects without ASD. Mean diffusivity trajectories did not differ between groups. Conclusions Underconnectivity across multiple white matter fiber bundles develops over the first 2 years of life in subjects with TSC and ASD. Future studies examining brain-behavior relationships are needed to determine how variation in the brain structure is associated with ASD symptoms.

Point-of-care human milk analysis is now feasible in the neonatal intensive care unit (NICU) and allows accurate measurement of macronutrient delivery. Higher macronutrient intakes over this period may promote brain growth and development. In a prospective, observational study of 55 infants born at <32 weeks’ gestation, we used a mid-infrared spectroscopy-based human milk analyzer to measure the macronutrient content in repeated samples of human milk over the NICU hospitalization. We calculated daily nutrient intakes from unfortified milk and assigned infants to quintiles based on median intakes over the hospitalization. Infants underwent brain magnetic resonance imaging at term equivalent age to quantify total and regional brain volumes and fractional anisotropy of white matter tracts. Infants in the highest quintile of energy intake from milk, as compared with the lower four quintiles, had larger total brain volume (31 cc, 95% confidence interval [CI]: 5, 56), cortical gray matter (15 cc, 95%CI: 1, 30), and white matter volume (23 cc, 95%CI: 12, 33). Higher protein intake was associated with larger total brain (36 cc, 95%CI: 7, 65), cortical gray matter (22 cc, 95%CI: 6, 38) and deep gray matter (1 cc, 95%CI: 0.1, 3) volumes. These findings suggest innovative strategies to close nutrient delivery gaps in the NICU may promote brain growth for preterm infants.

Psychiatry is undergoing a paradigm shift from the acceptance of distinct diagnoses to a representation of psychiatric illness that crosses diagnostic boundaries. How this transition is supported by a shared neurobiology remains largely unknown. In this study, we first identify single nucleotide polymorphisms (SNPs) associated with psychiatric disorders based on 136 genome-wide association studies. We then conduct a joint analysis of these SNPs and brain structural connectomes in 678 healthy children in the PING study. We discovered a strong, robust, and transdiagnostic mode of genome–connectome covariation which is positively and specifically correlated with genetic risk for psychiatric illness at the level of individual SNPs. Similarly, this mode is also significantly positively correlated with polygenic risk scores for schizophrenia, alcohol use disorder, major depressive disorder, a combined bipolar disorder-schizophrenia phenotype, and a broader cross-disorder phenotype, and significantly negatively correlated with a polygenic risk score for educational attainment. The resulting “vulnerability network” is shown to mediate the influence of genetic risks onto behaviors related to psychiatric vulnerability (e.g., marijuana, alcohol, and caffeine misuse, perceived stress, and impulsive behavior). Its anatomy overlaps with the default-mode network, with a network of cognitive control, and with the occipital cortex. These findings suggest that the brain vulnerability network represents an endophenotype funneling genetic risks for various psychiatric illnesses through a common neurobiological root. It may form part of the neural underpinning of the well-recognized but poorly explained overlap and comorbidity between psychiatric disorders.

Objective Diffusion tensor imaging (DTI) of the white matter is a biomarker for neurological disease burden in tuberous sclerosis complex (TSC). To clarify the basis of abnormal diffusion in TSC, we correlated ex vivo high‐resolution diffusion imaging with histopathology in four tissue types: cortex, tuber, perituber, and white matter. Methods Surgical specimens of three children with TSC were scanned in a 3T or 7T MRI with a structural image isotropic resolution of 137–300 micron, and diffusion image isotropic resolution of 270‐1,000 micron. We stained for myelin (luxol fast blue, LFB), gliosis (glial fibrillary acidic protein, GFAP), and neurons (NeuN) and registered the digitized histopathology slides (0.686 micron resolution) to MRI for visual comparison. We then performed colocalization analysis in four tissue types in each specimen. Finally, we applied a linear mixed model (LMM) for pooled analysis across the three specimens. Results In white matter and perituber regions, LFB optical density measures correlated with fractional anisotropy (FA) and inversely with mean diffusivity (MD). In white matter only, GFAP correlated with MD, and inversely with FA. In tubers and in the cortex, there was little variation in mean LFB and GFAP signal intensity, and no correlation with MRI metrics. Neuronal density correlated with MD. In the analysis of the combined specimens, the most robust correlation was between white matter MD and LFB metrics. Interpretation In TSC, diffusion imaging abnormalities in microscopic tissue types correspond to specific histopathological markers. Across all specimens, white matter diffusivity correlates with myelination.

ObjectiveTo determine associations between body composition and concurrent measures of brain development including (1) Tissue-specific brain volumes and (2) White matter microstructure, among very preterm infants at term equivalent age.DesignProspective observational study.SettingSingle-centre academic level III neonatal intensive care unit.PatientsWe studied 85 infants born <33 weeks’ gestation.MethodsAt term equivalent age, infants underwent air displacement plethysmography to determine body composition, and brain MRI from which we quantified tissue-specific brain volumes and fractional anisotropy (FA) of white matter tracts. We estimated associations of fat and lean mass Z-scores with each brain outcome, using linear mixed models adjusted for intrafamilial correlation among twins and potential confounding variables.ResultsMedian gestational age was 29 weeks (range 23.4–32.9). One unit greater lean mass Z-score was associated with larger total brain volume (10.5 cc, 95% CI 3.8 to 17.2); larger volumes of the cerebellum (1.2 cc, 95% CI 0.5 to 1.9) and white matter (4.5 cc, 95% CI 0.7 to 8.3); and greater FA in the left cingulum (0.3%, 95% CI 0.1% to 0.6%), right uncinate fasciculus (0.2%, 95% CI 0.0% to 0.5%), and right posterior limb of the internal capsule (0.3%, 95% CI 0.03% to 0.6%). Fat Z-scores were not associated with any outcome.ConclusionsLean mass—but not fat—at term was associated with larger brain volume and white matter microstructure differences that suggest improved maturation. Lean mass accrual may index brain growth and development.

In this article, the authors aim to introduce the nonradiologist to diffusion tensor imaging (DTI) and its applications to both clinical and research aspects of tuberous sclerosis complex. Tuberous sclerosis complex is a genetic neurocutaneous syndrome with variable and unpredictable neurological comorbidity that includes refractory epilepsy, intellectual disability, behavioral abnormalities and autism spectrum disorder. DTI is a method for modeling water diffusion in tissue and can noninvasively characterize microstructural properties of the brain. In tuberous sclerosis complex, DTI measures reflect well-known pathological changes. Clinically, DTI can assist with detecting the epileptogenic tuber. For research, DTI has a putative role in identifying potential disease biomarkers, as DTI abnormalities of the white matter are associated with neurocognitive morbidity including autism. If indeed DTI changes parallel phenotypical changes related to the investigational treatment of epilepsy, cognition and behavior with mTOR inhibitors, it will facilitate future clinical trials.

ObjectivesThe present randomized controlled clinical study aimed to investigate if, in lateral maxillary sinus augmentation, the repositioned bony wall or the application of a collagen membrane results in more preferable new hard tissue formation.Materials and methodsForty patients were divided into two study groups. Both groups received a xenogeneic bone substitute material (BSM) during lateral sinus augmentation. In the bony wall group (BW), following piezosurgery, the retrieved bony wall was repositioned. In the collagen membrane group (CM), following rotary instrument preparation, collagen membrane coverage was applied. After 6 months, biopsies were taken to histologically analyze the percentage of BSM, connective tissue (CT), and newly formed bone (NFB) following both approaches.ResultsForty implants were placed and 29 harvested biopsies could be evaluated. Duration of surgery, membrane perforations, and VAS were detected. Histomorphometrical analysis revealed comparable amounts of all analyzed parameters in both groups in descending order: CT (BW: 39.2 ± 9%, CM: 37,9 ± 8.5%) > BSM (BW: 32.9 ± 6.3%, CM: 31.8 ± 8.8%) > NB (BW: 27.8 ± 11.2%, CM: 30.3 ± 4.5%).ConclusionsThe results of the present study show that the closure of the access window by means of the retrieved bony wall or a native collagen membrane led to comparable bone augmentation results.Clinical trialclinicaltrials.gov NCT04811768.Clinical relevanceLateral maxillary sinus augmentation with the application of a xenogeneic BSM in combination with a native collagen membrane for bony window coverage represents a reliable method for surgical reconstruction of the posterior maxilla. Piezosurgery with bony window repositioning delivers comparable outcomes without membrane coverage.