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The article reports on the new technology and equipment of vertical‑stack molding (VSM), created by OJSC “BELNIILIT” for the manufacture of vertical‑stack molds. The development is intended for the production of molds and cast blanks of oil, which are later used for the manufacture of piston rings of internal combustion engines.The difference between the above‑mentioned technology and traditional methods of VSM is the use of models without drafts. The development is export‑oriented and has a great economic effect for ring manufacturers due to the absence of drafts on castings, since part of the mechanical operations for their processing is excluded, the metal consumption of blanks is reduced, the production spaces required in this regard are reduced, the necessary labor supply is reduced, etc.OJSC “BELNIILIT” has successfully carried out experimental design and technological work on the new scientific and technical products creation, which are of great interest to the world manufacturers of piston rings. An industrial sample of a molding machine and a mold manipulator were manufactured.

Information on researches and design development in the field of air-sand blowing process and creation of core-blowing installations which were carried out in 1950–1960 is provided in the article. The reference is made to the scientific centers and concrete design engineers who performed the specified activities.The essence of air-sand blowing process and the principles of its realization in core-making machines by design development and manufacture executed by the experts of NIILITAVTOPROMA (JSC BELNIILIT) is briefly stated.The main ratios of the areas between elements of system the sand-blowing installation systems, the basic rules and recommendations for design and manufacture of core-making machines and equipment for them are made. The retrospective of development and improvement of design solutions of air-sand blowing process is laid out. The essence and the modern design solution of caseless option of air-sand blowing process is stated. Illustrations of standard core-making machines for production of cores in the heated equipment and with amines blow are given. Systems the air-blowing devices, hold-down unit for blast and discharge and a special design of caseless option of sand-blowing process are described.The principle of rational combination of air-blowing process and process of a purging in modern blowing technologies is designated. The current trend of transition to computer design of system the air-blowing devices and its elements is shown (reference sections for boost, ventilation, etc.).

Perfection of technology and the equipment for production of piston rings in vertical stack molds is shown.

The main problem, which the enterprises, using the technology of casting in vertical stacks, face with, is operation of dosage and automatic control of the sand blend volume update at model plate.

UP ‘'Institute BelNIILit" has 40-years operational experience in the foundry market in the field of creation of forming equipment for production of piston rings castings in vertical-stack moulds.

The information about creation of the first domestic sample of pulse-press moulding machine is presented in the article

The article describes the problems of moulding sands proportioning, the effect of the proportioning accuracy on the shape and casting, gives the auger proportioner design.

Developmental and epileptic encephalopathies (DEEs) feature altered brain development, developmental delay and seizures, with seizures exacerbating developmental delay. Here we identify a cohort with biallelic variants in DENND5A, encoding a membrane trafficking protein, and develop animal models with phenotypes like the human syndrome. We demonstrate that DENND5A interacts with Pals1/MUPP1, components of the Crumbs apical polarity complex required for symmetrical division of neural progenitor cells. Human induced pluripotent stem cells lacking DENND5A fail to undergo symmetric cell division with an inherent propensity to differentiate into neurons. These phenotypes result from misalignment of the mitotic spindle in apical neural progenitors. Cells lacking DENND5A orient away from the proliferative apical domain surrounding the ventricles, biasing daughter cells towards a more fate-committed state, ultimately shortening the period of neurogenesis. This study provides a mechanism for DENND5A-related DEE that may be generalizable to other developmental conditions and provides variant-specific clinical information for physicians and families., (© 2024. The Author(s).)

Nucleus Basalis of Meynert (NbM), a crucial source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), has shown sensitivity to neurofibrillary degeneration in the early stages of Alzheimer's Disease. Using deformation-based morphometry (DBM) on up-sampled MRI scans from 1447 Alzheimer's Disease Neuroimaging Initiative participants, we aimed to quantify NbM degeneration along the disease trajectory. Results from cross-sectional analysis revealed significant differences of NbM volume between cognitively normal and early mild cognitive impairment cohorts, confirming recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. Longitudinal linear mixed-effect models were then used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results indicated the earliest deviations in NbM volumes from the cognitively healthy trajectory, challenging the prevailing idea that Alzheimer's originates in the EC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline., Competing Interests: Declaration of Competing Interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The Small Optic Lobe (SOL) family of calpains are intracellular cysteine proteases that are expressed in the nervous system and play an important role in neuronal development in both Drosophila, where loss of this calpain leads to the eponymous small optic lobes, and in mouse and human, where loss of this calpain leads to eye anomalies. Some human individuals with biallelic variants in CAPN15 also have developmental delay and autism. However, neither the specific effect of the loss of the Capn15 protein on brain development nor the brain regions where this calpain is expressed in the adult is known. Here we show using small animal MRI that mice with the complete loss of Capn15 have smaller brains overall with larger decreases in the thalamus and subregions of the hippocampus. These losses are not seen in Capn15 conditional knockout (KO) mice where Capn15 is knocked out only in excitatory neurons in the adult. Based on β-galactosidase expression in an insert strain where lacZ is expressed under the control of the Capn15 promoter, we show that Capn15 is expressed in adult mice, particularly in neurons involved in plasticity such as the hippocampus, lateral amygdala and Purkinje neurons, and partially in other non-characterized cell types. The regions of the brain in the adult where Capn15 is expressed do not correspond well to the regions of the brain most affected by the complete knockout suggesting distinct roles of Capn15 in brain development and adult brain function., (Copyright © 2021 IBRO. Published by Elsevier Ltd. All rights reserved.)

Background: The operative environment poses many challenges to studying the relationship between surgical acts and patient outcomes in intracranial oncological neurosurgery. We sought to develop a framework in which neurosurgical performance and extent of resection could be precisely quantified in a controlled setting., Methods: The stiffness of an alginate hydrogel-based tumor was modified with differing concentrations of the cross-linking agent calcium sulfate until biomechanical properties similar to those of human primary brain tumors measured at resection were achieved. The artificial tumor was subsequently incorporated into an ex-vivo animal brain as a final model. Magnetic resonance imaging enhancement and ultraviolet fluorescence was achieved by incorporating gadolinium and fluorescein solution, respectively. Video recordings from the operative microscope, ceiling cameras, and instrument-mounted fiducial markers within a surgical suite environment captured operative performance., Results: A total of 24 rheometer measurements were conducted on alginate hydrogels containing 10-, 11-, and 12-mM concentrations of calcium sulfate. Sixty-eight stiffness measurements were conducted on eight patient tumor samples. No differences were found between the alginate and brain tumor stiffness values [Kruskal-Wallis χ 2 (4) = 9.187; P = 0.057]. Tumor was identified using ultraviolet fluorescence and ultrasonography. The volume and location of the resected white and gray matter and residual tumor could be quantified in 0.003-mm 3 increments using a 7T magnetic resonance imaging coil. Ultrasonic aspirator and bipolar electrocautery movement data were successfully transformed into performance metrics., Conclusion: The developed framework can offer clinicians, learners, and researchers the ability to perform operative rehearsal, teaching, and studies involving brain tumor surgery in a controlled laboratory environment and represents a crucial step in the understanding and training of expertise in neurosurgery., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Accurate anatomical atlases are recognized as important tools in brain-imaging research. They are widely used to estimate disease-specific changes and therefore, are of great relevance in extracting regional information on volumetric variations in clinical cohorts in comparison to healthy populations. The use of high spatial resolution magnetic resonance imaging and the improvement in data preprocessing methods have enabled the study of structural volume changes on a wide range of disorders, particularly in neurodegenerative diseases where different brain morphometry analyses are being broadly used in an effort to improve diagnostic biomarkers. In the present dataset, we introduce the Cerebrum Atlas (CerebrA) along with the MNI-ICBM2009c average template. MNI-ICBM2009c is the most recent version of the MNI-ICBM152 brain average, providing a higher level of anatomical details. Cerebra is based on an accurate non-linear registration of cortical and subcortical labelling from Mindboggle 101 to the symmetric MNI-ICBM2009c atlas, followed by manual editing.

Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for quantitative volume, thickness, and shape measurements, as well as an important intermediate step in many preprocessing pipelines. This work introduces a new highly accurate and versatile method based on 3D convolutional neural networks for the automatic segmentation of neuroanatomy in T1-weighted MRI. In combination with a deep 3D fully convolutional architecture, efficient linear registration-derived spatial priors are used to incorporate additional spatial context into the network. An aggressive data augmentation scheme using random elastic deformations is also used to regularize the networks, allowing for excellent performance even in cases where only limited labeled training data are available. Applied to hippocampus segmentation in an elderly population (mean Dice coefficient = 92.1%) and subcortical segmentation in a healthy adult population (mean Dice coefficient = 89.5%), we demonstrate new state-of-the-art accuracies and a high robustness to outliers. Further validation on a multistructure segmentation task in a scan-rescan dataset demonstrates accuracy (mean Dice coefficient = 86.6%) similar to the scan-rescan reliability of expert manual segmentations (mean Dice coefficient = 86.9%), and improved reliability compared to both expert manual segmentations and automated segmentations using FIRST. Furthermore, our method maintains a highly competitive runtime performance (e.g., requiring only 10 s for left/right hippocampal segmentation in 1 × 1 × 1 mm 3 MNI stereotaxic space), orders of magnitude faster than conventional multiatlas segmentation methods., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Beginning in the early stages of Alzheimer's disease (AD), the hippocampus reduces its functional connections to other cortical regions due to synaptic depletion. However, little is known regarding connectivity abnormalities within the hippocampus. Here, we describe rostral-caudal hippocampal convergence (rcHC), a metric of the overlap between the rostral and caudal hippocampal functional networks, across the clinical spectrum of AD. We predicted a decline in rostral-caudal hippocampal convergence in the early stages of the disease. Using fMRI, we generated resting-state hippocampal functional networks across 56 controls, 48 early MCI (EMCI), 35 late MCI (LMCI), and 31 AD patients from the Alzheimer's Disease Neuroimaging Initiative cohort. For each diagnostic group, we performed a conjunction analysis and compared the rostral and caudal hippocampal network changes using a mixed effects linear model to estimate the convergence and differences between these networks, respectively. The conjunction analysis showed a reduction of rostral-caudal hippocampal convergence strength from early MCI to AD, independent of hippocampal atrophy. Our results demonstrate a parallel between the functional convergence within the hippocampus and disease stage, which is independent of brain atrophy. These findings support the concept that network convergence might contribute as a biomarker for connectivity dysfunction in early stages of AD.

Few studies have investigated the link between putative biomarkers of attention-deficit/hyperactivity disorder (ADHD) symptomatology and genetic risk for ADHD. To address this, we investigate the degree to which ADHD symptomatology is associated with white matter microstructure and cerebral cortical thickness in a large population-based sample of adolescents. Critically, we then test the extent to which multimodal correlates of ADHD symptomatology are related to ADHD polygenic risk score (PRS). Neuroimaging, genetic, and behavioral data were obtained from the IMAGEN study. A dimensional ADHD composite score was derived from multi-informant ratings of ADHD symptomatology. Using tract-based spatial statistics, whole brain voxel-wise regressions between fractional anisotropy (FA) and ADHD composite score were calculated. Local cortical thickness was regressed on ADHD composite score. ADHD PRS was based on a very recent genome-wide association study, and calculated using PRSice. ADHD composite score was negatively associated with FA in several white matter pathways, including bilateral superior and inferior longitudinal fasciculi (p < 0.05, corrected). ADHD composite score was negatively associated with orbitofrontal cortical thickness (p < 0.05, corrected). The ADHD composite score was correlated with ADHD PRS (p < 0.001). FA correlates of ADHD symptomatology were significantly associated with ADHD PRS, whereas cortical thickness correlates of ADHD symptomatology were unrelated to ADHD PRS. Variation in hyperactive/inattentive symptomatology was associated with white matter microstructure, which, in turn, was related to ADHD PRS. Results suggest that genetic risk for ADHD symptomatology may be tied to biological processes affecting white matter microstructure.

Objective: To determine the frequency of cortical lesions (CLs) in patients with pediatric-onset multiple sclerosis (POMS) using multi-contrast magnetic resonance imaging (MRI), and the relationship between frontal CL load and upper limb dexterity assessed with the Nine-Hole Peg Test (9-HPT)., Methods: Participants completed the 9-HPT and were imaged on a 3T MRI scanner to collect T1-weighted three-dimensional (3D) magnetization prepared rapid gradient echo (MPRAGE), proton density-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) images. CLs were manually segmented using all MRI contrasts., Results: We enrolled 24 participants with POMS (mean (standard deviation) age at first symptom: 13.3 (±2.7) years; mean age at scan: 18.8 (±3) years; mean disease duration of 5 (±3.2) years). A total of 391 CLs (mean, 16.3 ± 27.2; median, 7) were identified in 19 of 24 POMS patients (79%). The total number of CLs was positively associated with white matter lesion volume ( p = 0.04) but not with thalamic volume, age at the time of the scan, or disease duration. The number of frontal CLs was associated with slower performance on the 9-HPT ( p = 0.05)., Conclusion: Multi-contrast 3T MRI led to a high rate of CL detection, demonstrating that cortical pathology occurs even in pediatric-onset disease. Frontal lobe CL count was associated with reduced manual dexterity, indicating that these CLs are clinically relevant.

In structural neuroimaging studies, reduced cerebral cortical thickness in orbital and ventromedial prefrontal regions is frequently interpreted as reflecting an impaired ability to downregulate neuronal activity in the amygdalae. Unfortunately, little research has been conducted in order to test this conjecture. We examine the extent to which amygdalar reactivity is associated with cortical thickness in a population-based sample of adolescents. Data were obtained from the IMAGEN study, which includes 2,223 adolescents. While undergoing functional neuroimaging, participants passively viewed video clips of a face that started from a neutral expression and progressively turned angry, or, instead, turned to a second neutral expression. Left and right amygdala ROIs were used to extract mean BOLD signal change for the angry minus neutral face contrast for all subjects. T1-weighted images were processed through the CIVET pipeline (version 2.1.0). In variable-centered analyses, local cortical thickness was regressed against amygdalar reactivity using first and second-order linear models. In a follow-up person-centered analysis, we defined a "high reactive" group of participants based on mean amygdalar BOLD signal change for the angry minus neutral face contrast. Between-group differences in cortical thickness were examined ("high reactive" versus all other participants). A significant association was revealed between the continuous measure of amygdalar reactivity and bilateral ventromedial prefrontal cortical thickness in a second-order linear model (p < 0.05, corrected). The "high reactive" group, in comparison to all other participants, possessed reduced cortical thickness in bilateral orbital and ventromedial prefrontal cortices, bilateral anterior temporal cortices, left caudal middle temporal gyrus, and the left inferior and middle frontal gyri (p < 0.05, corrected). Results are consistent with non-human primate studies, and provide empirical support for an association between reduced prefrontal cortical thickness and amygdalar reactivity. Future research will likely benefit from investigating the degree to which psychopathology qualifies relations between prefrontal cortical structure and amygdalar reactivity., Competing Interests: Dr. Banaschewski has served as an advisor or consultant to Bristol-Myers Squibb, Desitin Arzneimittel, Eli Lilly, Medice, Novartis, Pfizer, Shire, UCB, and Vifor Pharma; he has received conference attendance support, conference support, or speaking fees from Eli Lilly, Janssen McNeil, Medice, Novartis, Shire, and UCB; and he is involved in clinical trials conducted by Eli Lilly, Novartis, and Shire; the present work is unrelated to these relationships. The other authors report no biomedical financial interests or potential conflicts of interest. The information, above, does not alter our adherence to PLOS ONE policies on sharing data and materials.

The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) integration was used to generate the streamlines. Finally, the local EA-CSF is computed by integrating the CSF probability along the generated streamlines. The proposed local EA-CSF extraction tool was used to study the early postnatal brain development in typically developing infants. The results show that the proposed localized EA-CSF extraction pipeline can produce statistically significant regions that are not observed in previous global approach.

Background: We previously reported that infants who developed autism spectrum disorder (ASD) had increased cerebrospinal fluid (CSF) in the subarachnoid space (i.e., extra-axial CSF) from 6 to 24 months of age. We attempted to confirm and extend this finding in a larger independent sample., Methods: A longitudinal magnetic resonance imaging study of infants at risk for ASD was carried out on 343 infants, who underwent neuroimaging at 6, 12, and 24 months. Of these infants, 221 were at high risk for ASD because of an older sibling with ASD, and 122 were at low risk with no family history of ASD. A total of 47 infants were diagnosed with ASD at 24 months and were compared with 174 high-risk and 122 low-risk infants without ASD., Results: Infants who developed ASD had significantly greater extra-axial CSF volume at 6 months compared with both comparison groups without ASD (18% greater than high-risk infants without ASD; Cohen's d = 0.54). Extra-axial CSF volume remained elevated through 24 months (d = 0.46). Infants with more severe autism symptoms had an even greater volume of extra-axial CSF from 6 to 24 months (24% greater at 6 months, d = 0.70; 15% greater at 24 months, d = 0.70). Extra-axial CSF volume at 6 months predicted which high-risk infants would be diagnosed with ASD at 24 months with an overall accuracy of 69% and corresponding 66% sensitivity and 68% specificity, which was fully cross-validated in a separate sample., Conclusions: This study confirms and extends previous findings that increased extra-axial CSF is detectable at 6 months in high-risk infants who develop ASD. Future studies will address whether this anomaly is a contributing factor to the etiology of ASD or an early risk marker for ASD., (Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The hippocampus is one of the first brain structures affected by Alzheimer's disease (AD). While many automatic methods for hippocampal segmentation exist, few studies have compared them on the same data. In this study, we compare four fully automated hippocampal segmentation methods in terms of their conformity with manual segmentation and their ability to be used as an AD biomarker in clinical settings. We also apply error correction to the four automatic segmentation methods, and complete a comprehensive validation to investigate differences between the methods. The effect size and classification performance is measured for AD versus normal control (NC) groups and for stable mild cognitive impairment (sMCI) versus progressive mild cognitive impairment (pMCI) groups. Our study shows that the nonlinear patch-based segmentation method with error correction is the most accurate automatic segmentation method and yields the most conformity with manual segmentation (κ=0.894). The largest effect size between AD versus NC and sMCI versus pMCI is produced by FreeSurfer with error correction. We further show that, using only hippocampal volume, age, and sex as features, the area under the receiver operating characteristic curve reaches up to 0.8813 for AD versus NC and 0.6451 for sMCI versus pMCI. However, the automatic segmentation methods are not significantly different in their performance., (Copyright © 2017. Published by Elsevier Inc.)

Parkinson׳s disease (PD) is a neurodegenerative disease that primarily affects the motor functions of the patients. Research and surgical treatment of PD (e.g., deep brain stimulation) often require human brain atlases for structural identification or as references for anatomical normalization. However, two pitfalls exist for many current atlases used for PD. First, most atlases do not represent the disease-specific anatomy as they are based on healthy young subjects. Second, subcortical structures, such as the subthalamic nucleus (STN) used in deep brain stimulation procedures, are often not well visualized. The dataset described in this Data in Brief is a population-averaged atlas that was made with 3 T MRI scans of 25 PD patients, and contains 5 image contrasts: T1w (FLASH & MPRAGE), T2*w, T1-T2* fusion, phase, and an R2* map. While the T1w, T2*w, and T1-T2* fusion templates provide excellent anatomical details for both cortical and sub-cortical structures, the phase and R2* map contain bio-chemical features. Probabilistic tissue maps of whiter matter, grey matter, and cerebrospinal fluid are provided for the atlas. We also manually segmented eight subcortical structures: caudate nucleus, putamen, globus pallidus internus and externus (GPi & GPe), thalamus, STN, substantia nigra (SN), and the red nucleus (RN). Lastly, a co-registered histology-derived digitized atlas containing 123 anatomical structures is included. The dataset is made freely available at the MNI data repository accessible through the link http://nist.mni.mcgill.ca/?p=1209.

The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-based multi-atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-of-the-art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes)., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Acquired demyelinating syndromes (ADS) have the potential to negatively impact cerebellar growth, given the proclivity for infratentorial lesions in pediatric-onset multiple sclerosis (MS) and ADS., Objective: To investigate cerebellar growth longitudinally in pediatric ADS., Methods: Cerebellar volumes from 472 magnetic resonance imaging (MRI) scans of 98 patients with monophasic ADS (monoADS), monophasic acute disseminated encephalomyelitis (ADEM), and MS (49 girls; mean age: 11.4 years at first scan, mean follow-up: 3.1 years) imaged serially from onset and 897 MRI scans of 418 healthy children (223 girls, mean age: 11.3 years, mean follow-up: 2.9 years) were segmented automatically, analyzed with mixed-effect models, and compared with cerebral volume., Results: Cerebellar developmental trajectories followed a U-shaped curve, showing larger volumes in boys (p < 0.001). Cerebellar volumes in all three patient groups failed to reach age-expected trajectories, leading to significantly smaller volumes, notably in the posterior lobes. Cerebellar volume reductions were of a similar magnitude to cerebral volume reductions. Cerebellar white matter volume declined in MS and ADEM patients over time, while in monoADS patients it remained similar to controls. Cerebellar volumes did not correlate either with lesion volumes at onset or with physical disability., Conclusion: MonoADS, ADEM, and MS in childhood lead to impaired age-expected growth of the cerebellum., (© The Author(s), 2015.)

Background: Posterior fossa lesions are common in pediatric-onset multiple sclerosis (MS), which is of concern, given the known role of the cerebellum in cognition., Objectives: To investigate the relationship between cerebellar pathology and cognitive function in youth with pediatric-onset MS., Methods: Twenty-eight pediatric-onset relapsing-remitting MS patients (21 girls; mean age 16.2 years; mean disease duration 4.3 years, median Expanded Disability Status Scale 1.25) were compared to 33 age- and sex-matched healthy controls. Participants underwent structural magnetic resonance imaging (MRI) and neuropsychological evaluation to assess intelligence, attention, processing speed, language, visuo-motor integration, and fine-motor dexterity. Associations between cognitive outcomes and cerebellar volume independent of cerebral volume were examined., Results: Cognitive and motor performance of the MS group was reduced relative to controls (all p<0.003). While cerebellar volumes did not differ between groups, cerebellar posterior lobe volume and infratentorial lesion volume accounted for extra variance on measures of information processing (R(2)=0.43; p=0.02) and vocabulary (R(2)=0.56; p=0.04) in patients (controlling for cerebral volume and sex), but not in controls., Conclusion: Smaller cerebellar posterior lobe volume, a known region for cognitive processing, and increased lesion burden in the posterior fossa adversely impact cognitive function, an important functional consequence of MS onset during childhood., (© The Author(s), 2015.)

We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation.

Most of the studies conducted on the development of the corpus callosum (CC) have been limited to a relatively simple assessment of callosal area, providing an estimation of the size of the CC in two dimensions rather than its actual measurement. The goal of this study was to revisit callosal development in childhood and adolescence by using a three-dimensional (3D) magnetic resonance imaging template of the CC that considers the horizontal width of the CC and compares this with the two-dimensional (2D) callosal area. We mapped callosal growth in a large sample of youths followed longitudinally (N = 370 at T1; N = 304 at T2; and N = 246 at T3). Both techniques were based on a five-section subdivision of the CC. The results obtained with the 3D method revealed that the rate of CC growth over a 4-year period in the rostrum, the genu, the anterior body and the splenium was significantly higher in the youngest age group (< 7 years) than in older groups, indicating an intense period of development in early childhood for the anterior and posterior parts of the CC. Similar results were obtained when 2D callosal area was used for the anterior and posterior parts of the CC. However, divergent results were found in the mid-body and the caudal body of the CC. As shown by differences between 2D estimations and actual 3D measurements of callosal growth, our study highlights the importance of considering the horizontal width in measuring developmental changes in the CC., (© 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Purpose: Parkinson's disease (PD) is the second leading neurodegenerative disease after Alzheimer's disease. In PD research and its surgical treatment, such as deep brain stimulation (DBS), anatomical structural identification and references for spatial normalization are essential, and human brain atlases/templates are proven highly instrumental. However, two shortcomings affect current templates used for PD. First, many templates are derived from a single healthy subject that is not sufficiently representative of the PD-population anatomy. This may result in suboptimal surgical plans for DBS surgery and biased analysis for morphological studies. Second, commonly used mono-contrast templates lack sufficient image contrast for some subcortical structures (i.e., subthalamic nucleus) and biochemical information (i.e., iron content), a valuable feature in current PD research., Methods: We employed a novel T1-T2* fusion MRI that visualizes both cortical and subcortical structures to drive groupwise registration to create co-registered multi-contrast (T1w, T2*w, T1-T2* fusion, phase, and an R2* map) unbiased templates from 15 PD patients, and a high-resolution histology-derived 3D atlas is co-registered. For validation, these templates are compared against the Colin27 template for landmark registration and midbrain nuclei segmentation., Results: While the T1w, T2*w, and T1-T2* fusion templates provide excellent anatomical details for both cortical and subcortical structures, the phase and R2* map contain the biochemical features. By one-way ANOVA tests, our templates significantly ([Formula: see text]) outperform the Colin27 template in the registration-based tasks., Conclusion: The proposed unbiased templates are more representative of the population of interest and can benefit both the surgical planning and research of PD.

The quantification of local surface complexity in the human cortex has shown to be of interest in investigating population differences as well as developmental changes in neurodegenerative or neurodevelopment diseases. We propose a novel assessment method that represents local complexity as the difference between the observed distributions of local surface topology to its best-fit basic topology model within a given local neighborhood. This distribution difference is estimated via Earth Move Distance (EMD) over the histogram within the local neighborhood of the surface topology quantified via the Shape Index (SI) measure. The EMD scores have a range from simple complexity (0.0), which indicates a consistent local surface topology, up to high complexity (1.0), which indicates a highly variable local surface topology. The basic topology models are categorized as 9 geometric situation modeling situations such as crowns, ridges and fundi of cortical gyro and sulci. We apply a geodesic kernel to calculate the local SI histrogram distribution within a given region. In our experiments, we obtained the results of local complexity that shows generally higher complexity in the gyral/sulcal wall regions and lower complexity in some gyral ridges and lowest complexity in sulcal fundus areas. In addition, we show expected, preliminary results of increased surface complexity across most of the cortical surface within the first years of postnatal life, hypothesized to be due to the changes such as development of sulcal pits.

Objective: The frequent lack of correspondence between performance and observational measures of executive functioning, including working memory, has raised questions about the validity of the observational measures. This study was conducted to investigate sources of this discrepancy through correlation of volumetric and cortical thickness (CT) neuroimaging values with performance and questionnaire measures of working memory (WM)., Methods: Using longitudinal data from the NIH MRI Study of Normal Brain Development (Volumes, N= 347, 54.3% female; CT, N= 350, 54.6% female; age range: 6 to 16.9 years), scores on the Behavioral Rating Inventory of Executive Function (BRIEF) WM, Emotional Control (EC) and Inhibition (INH) scales; Wechsler Scale of Intelligence for Children-III Digit Span; and Cambridge Neuropsychological Test Battery Spatial Working Memory (CANTAB SWM) were correlated with each other and with morphometric measurements using mixed effects linear regression models., Results: BRIEF WM was correlated with CANTAB SWM (p < .001). With whole brain correction, BRIEF WM and EC were both correlated with CT of the posterior parahippocampal gyrus (PHG), EC on the right side only. Performance measures of WM were unrelated to lobar volumes or CT, but were associated with volumes of hippocampus and amygdala., Conclusions: The known role of PHG in contextual learning suggests that the BRIEF WM assesses contextualized learning/memory, potentially explaining its loose correspondence to the decontextualized performance measures. Observational measures can be useful and valid functional metrics, complementing performance measures. Labels used to characterize scales should be interpreted with caution, however., (PsycINFO Database Record (c) 2015 APA, all rights reserved.)

Objective: To determine the impact of pediatric-onset multiple sclerosis (MS) on age-expected brain growth., Methods: Whole brain and regional volumes of 36 patients with relapsing-remitting MS onset prior to 18 years of age were segmented in 185 longitudinal MRI scans (2-11 scans per participant, 3-month to 2-year scan intervals). MRI scans of 25 age- and sex-matched healthy normal controls (NC) were also acquired at baseline and 2 years later on the same scanner as the MS group. A total of 874 scans from 339 participants from the NIH-funded MRI study of normal brain development acquired at 2-year intervals were used as an age-expected healthy growth reference. All data were analyzed with an automatic image processing pipeline to estimate the volume of brain and brain substructures. Mixed-effect models were built using age, sex, and group as fixed effects., Results: Significant group and age interactions were found with the adjusted models fitting brain volumes and normalized thalamus volumes (p < 10(-4)). These findings indicate a failure of age-normative brain growth for the MS group, and an even greater failure of thalamic growth. In patients with MS, T2 lesion volume correlated with a greater reduction in age-expected thalamic volume. To exclude any scanner-related influence on our data, we confirmed no significant interaction of group in the adjusted models between the NC and NIH MRI Study of Normal Brain Development groups., Conclusions: Our results provide evidence that the onset of MS during childhood and adolescence limits age-expected primary brain growth and leads to subsequent brain atrophy, implicating an early onset of the neurodegenerative aspect of MS., (© 2014 American Academy of Neurology.)

Reliable and fast segmentation of the human cerebellum with its complex architecture of lobes and lobules has been a challenge for the past decades. Emerging knowledge of the functional integration of the cerebellum in various sensori-motor and cognitive-behavioral circuits demands new automatic segmentation techniques, with accuracies similar to manual segmentations, but applicable to large subject numbers in a reasonable time frame. This article presents the development and application of a novel pipeline for rapid automatic segmentation of the human cerebellum and its lobules (RASCAL) combining patch-based label-fusion and a template library of manually labeled cerebella of 16 healthy controls from the International Consortium for Brain Mapping (ICBM) database. Leave-one-out experiments revealed a good agreement between manual and automatic segmentations (Dice kappa = 0.82). Intraclass correlation coefficients (ICC) were calculated to test reliability of segmented volumes and were highest (ICC > 0.9) for global measures (total and hemispherical grey and white matter) followed by larger lobules of the posterior lobe (ICC > 0.8). Further we applied the pipeline to all 152 young healthy controls of the ICBM database to look for hemispheric and gender differences. The results demonstrated larger native space volumes in men then women (mean (± SD) total cerebellar volume in women = 217 cm(3) (± 26), men = 259 cm(3) (± 29); P < 0.001). Significant gender-by-hemisphere interaction was only found in stereotaxic space volumes for white matter core (men > women) and anterior lobe volume (women > men). This new method shows great potential for the precise and efficient analysis of the cerebellum in large patient cohorts., (Copyright © 2014 Wiley Periodicals, Inc.)

Associations between brain cortical tissue volume and cognitive function in old age are frequently interpreted as suggesting that preservation of cortical tissue is the foundation of successful cognitive aging. However, this association could also, in part, reflect a lifelong association between cognitive ability and cortical tissue. We analyzed data on 588 subjects from the Lothian Birth Cohort 1936 who had intelligence quotient (IQ) scores from the same cognitive test available at both 11 and 70 years of age as well as high-resolution brain magnetic resonance imaging data obtained at approximately 73 years of age. Cortical thickness was estimated at 81 924 sampling points across the cortex for each subject using an automated pipeline. Multiple regression was used to assess associations between cortical thickness and the IQ measures at 11 and 70 years. Childhood IQ accounted for more than two-third of the association between IQ at 70 years and cortical thickness measured at age 73 years. This warns against ascribing a causal interpretation to the association between cognitive ability and cortical tissue in old age based on assumptions about, and exclusive reference to, the aging process and any associated disease. Without early-life measures of cognitive ability, it would have been tempting to conclude that preservation of cortical thickness in old age is a foundation for successful cognitive aging when, instead, it is a lifelong association. This being said, results should not be construed as meaning that all studies on aging require direct measures of childhood IQ, but as suggesting that proxy measures of prior cognitive function can be useful to take into consideration.

Executive dysfunction is frequently associated with episodic memory decline in amnestic mild cognitive impairment (aMCI) patients. Resting state executive control network (RS-ECN) represents a novel approach to interrogate the integrity of brain areas underlying executive dysfunction. The present study aims to investigate RS-ECN in aMCI and examine a possible link between changes in brain functional connectivity and declines in executive function. aMCI individuals (n = 13) and healthy subjects (n = 16) underwent cognitive assessment including executive function and high field functional magnetic resonance imaging. Individual RS-ECN maps were estimated using a seed-based cross-correlation method. Between groups RS-ECN functional connectivity comparison was assessed using voxel-wise statistic parametric mapping. aMCI individuals had reduced RS-ECN connectivity in the anterior cingulate cortex (ACC) and dorsal lateral prefrontal cortex (DLPFC), bilaterally. In contrast, aMCI showed increased connectivity in ventral lateral and anterior prefrontal cortex, bilaterally. Connectivity strength was associated with executive function in the ACC (r = 0.6213, p = 0.023) and right DLPFC (r = 0.6454, p = 0.017). Coexistence between connectivity declines and recruitment of brain regions outside the RS-ECN as reported here fits a brain reserve conceptual framework in which brain networks undergo remodeling in aMCI individuals.

The purpose of this project was to evaluate white matter degeneration and its impact on hippocampal structural connectivity in patients with amnestic mild cognitive impairment, non-amnestic mild cognitive impairment and Alzheimer's disease. We estimated white matter fractional anisotropy, mean diffusivity and hippocampal structural connectivity in two independent cohorts. The ADNI cohort included 108 subjects [25 cognitively normal, 21 amnestic mild cognitive impairment, 47 non-amnestic mild cognitive impairment and 15 Alzheimer's disease]. A second cohort included 34 subjects [15 cognitively normal and 19 amnestic mild cognitive impairment] recruited in Montreal. All subjects underwent clinical and neuropsychological assessment in addition to diffusion and T1 MRI. Individual fractional anisotropy and mean diffusivity maps were generated using FSL-DTIfit. In addition, hippocampal structural connectivity maps expressing the probability of connectivity between the hippocampus and cortex were generated using a pipeline based on FSL-probtrackX. Voxel-based group comparison statistics of fractional anisotropy, mean diffusivity and hippocampal structural connectivity were estimated using Tract-Based Spatial Statistics. The proportion of abnormal to total white matter volume was estimated using the total volume of the white matter skeleton. We found that in both cohorts, amnestic mild cognitive impairment patients had 27-29% white matter volume showing higher mean diffusivity but no significant fractional anisotropy abnormalities. No fractional anisotropy or mean diffusivity differences were observed between non-amnestic mild cognitive impairment patients and cognitively normal subjects. Alzheimer's disease patients had 66.3% of normalized white matter volume with increased mean diffusivity and 54.3% of the white matter had reduced fractional anisotropy. Reduced structural connectivity was found in the hippocampal connections to temporal, inferior parietal, posterior cingulate and frontal regions only in the Alzheimer's group. The severity of white matter degeneration appears to be higher in advanced clinical stages, supporting the construct that these abnormalities are part of the pathophysiological processes of Alzheimer's disease.

Typical adults show an inverse relation between callosal fiber length and degree of interhemispheric connectivity. This has been hypothesized to be a consequence of the influence of conduction delays and cellular costs during development on axonal pruning, both of which increase with fiber length. Autism spectrum disorder (ASD) provides a test of this hypothesis: Children with ASD are known to have enlarged brains; thus, adults with ASD should show reductions in interhemispheric connectivity proportional to their degree of brain overgrowth during development. This prediction was tested by assessing the relation between both the size and structure of the corpus callosum and callosal fiber length, adjusting for intracranial volume, which is thought to reflect maximum brain size achieved during development. Using tractography to estimate the length of callosal fibers emanating from all areas of cortex, and through which region of the corpus callosum they pass, we show that adults with ASD show an inverse relation between callosal fiber length, adjusted for intracranial volume, and callosum size, and a positive relation between adjusted callosal fiber length and radial diffusivity. The results provide support for the hypothesized impact of fiber length during development., (Copyright © 2012 Wiley Periodicals, Inc.)

Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects the corpus callosum (CC), which plays a key role in interhemispheric coupling in high-demand conditions. Using 3D callosal measurements and a letter-matching paradigm, this 2-part study investigated the neural substrate of interhemispheric coupling in individuals with AD or amnestic mild cognitive impairment (a-MCI) and age-matched healthy individuals (HC)., Method: Thirty-three right-handed participants were MRI scanned to measure the volume of the CC in 5 sections. In Study 1, AD, a-MCI, and HC individuals performed a low-demand perceptual letter shape-matching task (e.g., A-A); in Study 2, a-MCI and HC individuals performed a "case-sensitive" letter-matching task (Study 2A) and a "load-sensitive" letter-matching task (Study 2B)., Results: The results showed a positive correlation between Response Times and the midbody of the CC at the lowest cognitive demand level (Study 1) in participants with AD, and the total CC, midbody, caudal body, and isthmus of the CC at high cognitive demand levels (Study 2A) in normal aging. The volume of the anterior part of the CC was significantly negatively correlated with the interhemispheric behavioral indices for the a-MCI group (Study 1 and Study 2B)., Conclusion: This study provides evidence that interhemispheric coupling may constitute a flexible mechanism that can improve the brain's ability to meet processing demands for low cognitive demand in AD and for high cognitive demand in normal aging., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

Predicting Alzheimer's disease (AD) in individuals with some symptoms of cognitive decline may have great influence on treatment choice and disease progression. Structural magnetic resonance imaging (MRI) has the potential of revealing early signs of neurodegeneration in the human brain and may thus aid in predicting and diagnosing AD. Surface-based cortical thickness measurements from T1-weighted MRI have demonstrated high sensitivity to cortical gray matter changes. In this study we investigated the possibility for using patterns of cortical thickness measurements for predicting AD in subjects with mild cognitive impairment (MCI). We used a novel technique for identifying cortical regions potentially discriminative for separating individuals with MCI who progress to probable AD, from individuals with MCI who do not progress to probable AD. Specific patterns of atrophy were identified at four time periods before diagnosis of probable AD and features were selected as regions of interest within these patterns. The selected regions were used for cortical thickness measurements and applied in a classifier for testing the ability to predict AD at the four stages. In the validation, the test subjects were excluded from the feature selection to obtain unbiased results. The accuracy of the prediction improved as the time to conversion from MCI to AD decreased, from 70% at 3 years before the clinical criteria for AD was met, to 76% at 6 months before AD. By inclusion of test subjects in the feature selection process, the prediction accuracies were artificially inflated to a range of 73% to 81%. Two important results emerge from this study. First, prediction accuracies of conversion from MCI to AD can be improved by learning the atrophy patterns that are specific to the different stages of disease progression. This has the potential to guide the further development of imaging biomarkers in AD. Second, the results show that one needs to be careful when designing training, testing and validation schemes to ensure that datasets used to build the predictive models are not used in testing and validation., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Purpose: Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson's disease., Methods: T1-weighted and T2-weighted magnetic resonance (MR) image templates were created by averaging MR images of 57 patients with Parkinson's disease. Twenty-four deep brain structures were manually segmented on the templates. To validate the template-based segmentation, 14 of the 24 deep brain structures from the templates were manually segmented on 10 MR scans of Parkinson's patients as a gold standard. We compared the manual segmentations with three methods of automated segmentation: two registration-based approaches, automatic nonlinear image matching and anatomical labeling (ANIMAL) and symmetric image normalization (SyN), and one patch-label fusion technique. The automated labels were then compared with the manual labels using a Dice-kappa metric and center of gravity. A Friedman test was used to compare the Dice-kappa values and paired t tests for the center of gravity., Results: The Friedman test showed a significant difference between the three methods for both thalami (p < 0.05) and not for the subthalamic nuclei. Registration with ANIMAL was better than with SyN for the left thalamus and was better than the patch-based method for the right thalamus., Conclusion: Although template-based approaches are the most used techniques to segment basal ganglia by warping onto MR images, we found that the patch-based method provided similar results and was less time-consuming. Patch-based method may be preferable for the subthalamic nucleus segmentation in patients with Parkinson's disease.

Brain extraction is an important step in the analysis of brain images. The variability in brain morphology and the difference in intensity characteristics due to imaging sequences make the development of a general purpose brain extraction algorithm challenging. To address this issue, we propose a new robust method (BEaST) dedicated to produce consistent and accurate brain extraction. This method is based on nonlocal segmentation embedded in a multi-resolution framework. A library of 80 priors is semi-automatically constructed from the NIH-sponsored MRI study of normal brain development, the International Consortium for Brain Mapping, and the Alzheimer's Disease Neuroimaging Initiative databases. In testing, a mean Dice similarity coefficient of 0.9834±0.0053 was obtained when performing leave-one-out cross validation selecting only 20 priors from the library. Validation using the online Segmentation Validation Engine resulted in a top ranking position with a mean Dice coefficient of 0.9781±0.0047. Robustness of BEaST is demonstrated on all baseline ADNI data, resulting in a very low failure rate. The segmentation accuracy of the method is better than two widely used publicly available methods and recent state-of-the-art hybrid approaches. BEaST provides results comparable to a recent label fusion approach, while being 40 times faster and requiring a much smaller library of priors., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Objective: Whole brain and regional volume measurement methods were used to quantify white matter, gray matter, and deep gray matter structure volumes in a population of patients with pediatric-onset multiple sclerosis (MS)., Methods: Subjects included 38 patients (mean age 15.2 ± 2.4 years) and 33 age- and sex-matched healthy control (HC) participants. MRI measures included intracranial volume, normalized brain volume, normalized white and gray matter volume, and volumes of the thalamus, globus pallidus, putamen, and caudate. Because these volumes vary across age and sex in children, we normalized the volume measurements for MS and control groups by computing z scores using normative values obtained from healthy children enrolled in the MRI Study of Normal Brain Development., Results: The intracranial volume z score was significantly lower in the patients with MS (-0.45 ± 1.16; mean ± SD) compared with the HC participants (+0.25 ± 0.98; p = 0.01). Patients with MS also demonstrated significant decreases in normalized brain volume z scores (-1.09 ± 1.49 vs -0.05 ± 1.22; p = 0.002). After correction for global brain volume, thalamic volumes in the MS population remained lower than those of HCs (-0.68 ± 1.72 vs 0.15 ± 1.35; p = 0.02), indicating an even greater loss of thalamic tissue relative to more global brain measures. Moderate correlations were found between T2-weighted lesion load and normalized thalamic volumes (r = -0.44, p < 0.01) and normalized brain volume (r = -0.47, p < 0.01) and between disease duration and normalized thalamic volume (r = -0.58, p < 0.001) and normalized brain volume (r = -0.46, p < 0.01)., Conclusions: When compared with age- and sex-matched control subjects, the onset of MS during childhood is associated with a smaller overall head size, brain volume, and an even smaller thalamic volume.

Background: The hypothetical model of dynamic biomarkers for Alzheimer's disease (AD) describes high amyloid deposition and hypometabolism at the mild cognitive impairment (MCI) stage. However, it remains unknown whether brain amyloidosis and hypometabolism follow the same trajectories in MCI individuals. We used the concept of early MCI (EMCI) and late MCI (LMCI) as defined by the Alzheimer's disease Neuroimaging Initiative (ADNI)-Go in order to compare the biomarker profile between EMCI and LMCI., Objectives: To examine the global and voxel-based neocortical amyloid burden and metabolism among individuals who are cognitively normal (CN), as well as those with EMCI, LMCI and mild AD., Methods: In the present study, 354 participants, including CN (n = 109), EMCI (n = 157), LMCI (n = 39) and AD (n = 49), were enrolled between September 2009 and November 2011 through ADNI-GO and ADNI-2. Brain amyloid load and metabolism were estimated using [(18)F]AV45 and [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET, respectively. Uptake ratio images of [(18)F]AV45 and [(18)F]FDG were calculated by dividing the summed PET image by the median counts of the grey matter of the cerebellum and pons, respectively. Group differences of global [(18)F]AV45 and [(18)F]FDG were analyzed using ANOVA, while the voxel-based group differences were estimated using statistic parametric mapping (SPM)., Results: EMCI patients showed higher global [(18)F]AV45 retention compared to CN and lower uptake compared to LMCI. SPM detected higher [(18)F]AV45 uptake in EMCI compared to CN in the precuneus, posterior cingulate, medial and dorsal lateral prefrontal cortices, bilaterally. EMCI showed lower [(18)F]AV45 retention than LMCI in the superior temporal, inferior parietal, as well as dorsal lateral prefrontal cortices, bilaterally. Regarding to the global [(18)F]FDG, EMCI patients showed no significant difference from CN and a higher uptake ratio compared to LMCI. At the voxel level, EMCI showed higher metabolism in precuneus, hippocampus, entorhinal and inferior parietal cortices, as compared to LMCI., Conclusions: The present results indicate that brain metabolism remains normal despite the presence of significant amyloid accumulation in EMCI. These results suggest a role for anti-amyloid interventions in EMCI aiming to delay or halt the deposition of amyloid and related metabolism impairment.

Purpose: We present a new technique for registering magnetic resonance (MR) and ultrasound images in the context of neurosurgery. It involves generating a pseudo-ultrasound (pseudo-US) from a segmented MR image and uses cross-correlation as the cost function to register the pseudo-US to the real ultrasound data. The algorithm's performance is compared with that of a state-of-the-art technique that uses a median-filtered MR image to register to a Gaussian-blurred ultrasound using a normalized mutual information (NMI) objective function., Methods: The two methods were tested on data from 15 patients with brain tumor, including low-and high-grade gliomas, in both first operations and reoperations. Two metrics were used to evaluate registration accuracy: (1) the mean distance between corresponding points, identified on both MR and ultrasound images by two experts, and (2) ratings based on visual comparison by one neurosurgeon., Results: The mean residual distance of the pseudo-US technique, 2.97 mm, is significantly more accurate (p = .0011) than that of the NMI approach, 4.86 mm. The visual assessment shows that only 4 of the 15 cases had a satisfactory initial alignment based on homologous skin-point registration. There is a significant correlation between the quantitative distance measures and the qualitative ratings (rho = 0.785)., Conclusion: The results show that the pseudo-US rigid registration technique robustly improves the MRI-ultrasound alignment when compared with the initial alignment, even when applied to highly distorted brains and a large range of tumor sizes and appearances.

We used cross-sectional tensor-based morphometry to visualize reduced volume in the whole brains of pediatric patients with multiple sclerosis, relative to healthy controls. As a marker of local volume difference, we used the Jacobian determinant of the deformation field that maps each subject to a standard space. To properly assess abnormal differences in volume in this age group, it is necessary to account for the normal, age-related differences in brain volume. This was accomplished by computing normalized z-score Jacobian determinant values at each voxel to represent the local volume difference (in standard deviations) between an individual subject and an age- and sex-matched healthy normal population. Compared with healthy controls, pediatric patients with multiple sclerosis exhibited significantly reduced volumes within the thalamus and the splenium of the corpus callosum and significant expansions in the ventricles. While T2-weighted lesion volume was correlated with reduced splenium volume, no correlation was found between T2-weighted lesion volume and reduced thalamic volume. Reduced volumes of the optic pathways, including that of the optic tracts and optic radiations, correlated with disease duration. Our results suggest that focal inflammatory lesions may play an important role in tract degeneration, including transsynaptic degeneration., (Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.)

Quantitative magnetic resonance analysis often requires accurate, robust, and reliable automatic extraction of anatomical structures. Recently, template-warping methods incorporating a label fusion strategy have demonstrated high accuracy in segmenting cerebral structures. In this study, we propose a novel patch-based method using expert manual segmentations as priors to achieve this task. Inspired by recent work in image denoising, the proposed nonlocal patch-based label fusion produces accurate and robust segmentation. Validation with two different datasets is presented. In our experiments, the hippocampi of 80 healthy subjects and the lateral ventricles of 80 patients with Alzheimer's disease were segmented. The influence on segmentation accuracy of different parameters such as patch size and number of training subjects was also studied. A comparison with an appearance-based method and a template-based method was also carried out. The highest median kappa index values obtained with the proposed method were 0.884 for hippocampus segmentation and 0.959 for lateral ventricle segmentation., (Crown Copyright © 2010. Published by Elsevier Inc. All rights reserved.)

Spatial normalization, registration, and segmentation techniques for Magnetic Resonance Imaging (MRI) often use a target or template volume to facilitate processing, take advantage of prior information, and define a common coordinate system for analysis. In the neuroimaging literature, the MNI305 Talairach-like coordinate system is often used as a standard template. However, when studying pediatric populations, variation from the adult brain makes the MNI305 suboptimal for processing brain images of children. Morphological changes occurring during development render the use of age-appropriate templates desirable to reduce potential errors and minimize bias during processing of pediatric data. This paper presents the methods used to create unbiased, age-appropriate MRI atlas templates for pediatric studies that represent the average anatomy for the age range of 4.5-18.5 years, while maintaining a high level of anatomical detail and contrast. The creation of anatomical T1-weighted, T2-weighted, and proton density-weighted templates for specific developmentally important age-ranges, used data derived from the largest epidemiological, representative (healthy and normal) sample of the U.S. population, where each subject was carefully screened for medical and psychiatric factors and characterized using established neuropsychological and behavioral assessments. Use of these age-specific templates was evaluated by computing average tissue maps for gray matter, white matter, and cerebrospinal fluid for each specific age range, and by conducting an exemplar voxel-wise deformation-based morphometry study using 66 young (4.5-6.9 years) participants to demonstrate the benefits of using the age-appropriate templates. The public availability of these atlases/templates will facilitate analysis of pediatric MRI data and enable comparison of results between studies in a common standardized space specific to pediatric research., (Copyright © 2010 Elsevier Inc. All rights reserved.)