Longitudinal Relationship Between Brain Atrophy Patterns, Cognitive Decline, and Cerebrospinal Fluid Biomarkers in Alzheimer's Disease Explored by Orthonormal Projective Non-Negative Matrix Factorization.

Background: Longitudinal magnetic resonance imaging (MRI) has been proposed for tracking the progression of Alzheimer's disease (AD) through the assessment of brain atrophy. Objective: Detection of brain atrophy patterns in patients with AD as the longitudinal disease tracker. Methods: We used a refined version of orthonormal projective non-negative matrix factorization (OPNMF) to identify six distinct spatial components of voxel-wise volume loss in the brains of 83 subjects with AD from the ADNI3 cohort relative to healthy young controls from the ABIDE study. We extracted non-negative coefficients representing subject-specific quantitative measures of regional atrophy. Coefficients of brain atrophy were compared to subjects with mild cognitive impairment and controls, to investigate the cross-sectional and longitudinal associations between AD biomarkers and regional atrophy severity in different groups. We further validated our results in an independent dataset from ADNI2. Results: The six non-overlapping atrophy components represent symmetric gray matter volume loss primarily in frontal, temporal, parietal and cerebellar regions. Atrophy in these regions was highly correlated with cognition both cross-sectionally and longitudinally, with medial temporal atrophy showing the strongest correlations. Subjects with elevated CSF levels of TAU and PTAU and lower baseline CSF Aß42 values, demonstrated a tendency toward a more rapid increase of atrophy. Conclusions: The present study has applied a transferable method to characterize the imaging changes associated with AD through six spatially distinct atrophy components and correlated these atrophy patterns with cognitive changes and CSF biomarkers cross-sectionally and longitudinally, which may help us better understand the underlying pathology of AD.

Subject-specific material properties of the heel pad: An inverse finite element analysis.

Individuals with diabetes are at a higher risk of developing foot ulcers. To better understand internal soft tissue loading and potential treatment options, subject-specific finite element (FE) foot models have been used. However, existing models typically lack subject-specific soft tissue material properties and only utilize subject-specific anatomy. Therefore, this study determined subject-specific hindfoot soft tissue material properties from one non-diabetic and one diabetic subject using inverse FE analysis. Each subject underwent cyclic MRI experiments to simulate physiological gait and to obtain compressive force and three-dimensional soft tissue imaging data at 16 phases along the loading-unloading cycles. The FE models consisted of rigid bones and nearly-incompressible first-order Ogden hyperelastic skin, fat, and muscle (resulting in six independent material parameters). Then, calcaneus and loading platen kinematics were computed from imaging data and prescribed to the FE model. Two analyses were performed for each subject. First, the skin, fat, and muscle layers were lumped into a single generic soft tissue material and optimized to the platen force. Second, the skin, fat, and muscle material properties were individually determined by simultaneously optimizing for platen force, muscle vertical displacement, and skin mediolateral bulging. Our results indicated that compared to the individual without diabetes, the individual with diabetes had stiffer generic soft tissue behavior at high strain and that the only substantially stiffer multi-material layer was fat tissue. Thus, we suggest that this protocol serves as a guideline for exploring differences in non-diabetic and diabetic soft tissue material properties in a larger population.

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

Learning Cortical Parcellations Using Graph Neural Networks.

Deep learning has been applied to magnetic resonance imaging (MRI) for a variety of purposes, ranging from the acceleration of image acquisition and image denoising to tissue segmentation and disease diagnosis. Convolutional neural networks have been particularly useful for analyzing MRI data due to the regularly sampled spatial and temporal nature of the data. However, advances in the field of brain imaging have led to network- and surface-based analyses that are often better represented in the graph domain. In this analysis, we propose a general purpose cortical segmentation method that, given resting-state connectivity features readily computed during conventional MRI pre-processing and a set of corresponding training labels, can generate cortical parcellations for new MRI data. We applied recent advances in the field of graph neural networks to the problem of cortical surface segmentation, using resting-state connectivity to learn discrete maps of the human neocortex. We found that graph neural networks accurately learn low-dimensional representations of functional brain connectivity that can be naturally extended to map the cortices of new datasets. After optimizing over algorithm type, network architecture, and training features, our approach yielded mean classification accuracies of 79.91% relative to a previously published parcellation. We describe how some hyperparameter choices including training and testing data duration, network architecture, and algorithm choice affect model performance.

Applying Artificial Intelligence to Mitigate Effects of Patient Motion or Other Complicating Factors on Image Quality.

Artificial intelligence, particularly deep learning, offers several possibilities to improve the quality or speed of image acquisition in magnetic resonance imaging (MRI). In this article, we briefly review basic machine learning concepts and discuss commonly used neural network architectures for image-to-image translation. Recent examples in the literature describing application of machine learning techniques to clinical MR image acquisition or postprocessing are discussed. Machine learning can contribute to better image quality by improving spatial resolution, reducing image noise, and removing undesired motion or other artifacts. As patients occasionally are unable to tolerate lengthy acquisition times or gadolinium agents, machine learning can potentially assist MRI workflow and patient comfort by facilitating faster acquisitions or reducing exogenous contrast dosage. Although artificial intelligence approaches often have limitations, such as problems with generalizability or explainability, there is potential for these techniques to improve diagnostic utility, throughput, and patient experience in clinical MRI practice.

Making Magnets More Attractive: Physics and Engineering Contributions to Patient Comfort in MRI.

Patient comfort is an important factor of a successful magnetic resonance (MR) examination, and improvements in the patient's MR scanning experience can contribute to improved image quality, diagnostic accuracy, and efficiency in the radiology department, and therefore reduced cost. Magnet designs that are more open and accessible, reduced auditory noise of MR examinations, light and flexible radiofrequency (RF) coils, and faster motion-insensitive imaging techniques can all significantly improve the patient experience in MR imaging. In this work, we review the design, development, and implementation of these physics and engineering approaches to improve patient comfort.

Model-based tracking of the bones of the foot: A biplane fluoroscopy validation study.

Measuring foot kinematics using optical motion capture is technically challenging due to the depth of the talus, small bone size, and soft tissue artifact. We present a validation of our biplane X-ray system, demonstrating its accuracy in tracking the foot bones directly. Using an experimental linear/rotary stage we imaged pairs of tali, calcanei, and first metatarsals, with embedded beads, through 30 poses. Model- and bead-based algorithms were employed for semi-automatic tracking. Translational and rotational poses were compared to the experimental stage (a reference standard) to determine registration performance. For each bone, 10 frames per pose were analyzed. Model-based: The resulting overall translational bias of the six bones was 0.058 mm with a precision of ± 0.049 mm. The overall rotational bias of the six bones was 0.42° with a precision of ± 0.41°. Bead-based: the overall translational bias was 0.037 mm with a precision of ± 0.032 mm and for rotation was 0.29° with a precision of ± 0.26°. We validated the accuracy of our system to determine the spatial position and orientation of isolated foot bones, including the talus, calcaneus, and first metatarsal over a range of quasi-static poses. Although the accuracy of dynamic motion was not assessed, use of an experimental stage establishes a reference standard.

A preliminary study of patient-specific mechanical properties of diabetic and healthy plantar soft tissue from gated magnetic resonance imaging.

Foot loading rate, load magnitude, and the presence of diseases such as diabetes can all affect the mechanical properties of the plantar soft tissues of the human foot. The hydraulic plantar soft tissue reducer instrument was designed to gain insight into which variables are the most significant in determining these properties. It was used with gated magnetic resonance imaging to capture three-dimensional images of feet under dynamic loading conditions. Custom electronics controlled by LabVIEW software simultaneously recorded system pressure, which was then translated to applied force values based on calibration curves. Data were collected for two subjects, one without diabetes (Subject A) and one with diabetes (Subject B). For a 0.2-Hz loading rate, and strains 0.16, 0.18, 0.20, and 0.22, Subject A's average tangential heel pad stiffness was 10 N/mm and Subject B's was 24 N/mm. Maximum test loads were approximately 200 N. Loading rate and load magnitude limitations (both were lower than physiologic values) will continue to be addressed in the next version of the instrument. However, the current hydraulic plantar soft tissue reducer did produce a data set for healthy versus diabetic tissue stiffness that agrees with previous trends. These data are also being used to improve finite element analysis models of the foot as part of a related project.

Association of Collateral Blood Vessels Detected by Arterial Spin Labeling Magnetic Resonance Imaging With Neurological Outcome After Ischemic Stroke.

Importance: Robust collateral blood vessels have been associated with better neurologic outcome following acute ischemic stroke (AIS). The most commonly used methods for identifying collaterals are contrast-based angiographic imaging techniques, which are not possible in all patients after AIS. Objective: To assess the association between the presence of collateral vessels identified using arterial spin labeling (ASL) magnetic resonance imaging, a technique that does not require exogenous administration of contrast, and neurologic outcome in patients after AIS. Design, Setting, and Participants: This retrospective cohort study examined 38 patients after AIS admitted to a tertiary academic medical center between 2012 and 2014 who underwent MRI with ASL. Main Outcomes and Measures: According to a prespecified hypothesis, ASL images were graded for the presence of collaterals by 2 neuroradiologists. Modified Rankin Scale (mRS) scores at discharge and other composite data were abstracted from the medical record by a neurologist blinded to radiologic data. Results: Of the 38 patients, 19 (50.0%) were male, and the mean (SD) age was 61 (20) years. In 25 of 38 patients (65.8%), collaterals were detected using ASL, which were significantly associated with both a good outcome (mRS score of 0-2 at discharge; P = .02) and a 1-point decrease in mRS score at discharge (odds ratio, 6.4; 95% CI, 1.7-23.4; P = .005). In a multivariable ordinal logistic regression model, controlling for admission National Institutes of Health Stroke Scale score, history of atrial fibrillation, premorbid mRS score, and stroke parent artery status, there was a strong association between the presence of ASL collaterals and a 1-point decrease in the mRS score at discharge (odds ratio, 5.1; 95% CI, 1.2-22.1; P = .03). Conclusions and Relevance: Following AIS, the presence of ASL collaterals is strongly associated with better neurological outcome at hospital discharge. This novel association between ASL collaterals and improved neurologic outcome may help guide prognosis and management, particularly in patients who are unable to undergo contrast-based radiological studies.

A comprehensive transcriptional map of primate brain development.

The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.

Perimesencephalic Hemorrhage: Yield of Single versus Multiple DSA Examinations-A Single-Center Study and Meta-Analysis.

Purpose To quantify the rate of detection of aneurysms at follow-up digital subtraction angiography (DSA) after initial DSA with results negative for aneurysms in subjects with perimesencephalic (PM) nonaneurysmal subarachnoid hemorrhage. Materials and Methods This single-center retrospective study and meta-analysis was approved by the institutional review board. At a single institution from 2000 to 2013, 252 consecutive patients with subarachnoid hemorrhage at computed tomography (CT) and two DSA examinations negative for aneurysm within 10 days were evaluated for inclusion in the study, and 131 met CT criteria for PM nonaneurysmal subarachnoid hemorrhage (53 women; mean age, 53 years [range, 33-88 years]). DS angiographic reports were reviewed for causative abnormalities. Three reviewers searched MEDLINE and electronic databases for studies that reported detection of aneurysm in subjects with PM hemorrhage who had undergone multiple DSA examinations. Main inclusion criteria were PM hemorrhage at CT per van Gijn classification, head CT performed within 72 hours of symptom onset, initial DS angiographic results negative for aneurysm, and two DSA examinations within 10 days. Studies with fewer than 25 subjects were excluded. Methodology was assessed by using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The summary rate of aneurysm detection for subsequent DSA was calculated by using a fixed-effects model. Results Six studies with 298 subjects and a single-institution study with 131 subjects were included. No aneurysms were seen at follow-up DSA in the single-center study (0.0%). Three aneurysms were detected at follow-up DSA in three of six studies from the literature (one of 29 [3.4%], one of 65 [1.5%], and one of 34 [2.9%] patients). Two occurred in cases that likely preceded the use of the current DSA technique. The summary aneurysm detection rate at subsequent DSA was 1.6% (95% confidence interval: 0.7%, 3.8%; range of individual study detection rate: 0.0%-3.4%). Conclusion In patients with PM nonaneurysmal subarachnoid hemorrhage and initial DSA negative for aneurysms, the yield of follow-up DSA for detection of causative aneurysms is very low. © RSNA, 2016 Online supplemental material is available for this article.

Canonical genetic signatures of the adult human brain.

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.

The design and validation of a magnetic resonance imaging-compatible device for obtaining mechanical properties of plantar soft tissue via gated acquisition.

Changes in the mechanical properties of the plantar soft tissue in people with diabetes may contribute to the formation of plantar ulcers. Such ulcers have been shown to be in the causal pathway for lower extremity amputation. The hydraulic plantar soft tissue reducer (HyPSTER) was designed to measure in vivo, rate-dependent plantar soft tissue compressive force and three-dimensional deformations to help understand, predict, and prevent ulcer formation. These patient-specific values can then be used in an inverse finite element analysis to determine tissue moduli, and subsequently used in a foot model to show regions of high stress under a wide variety of loading conditions. The HyPSTER uses an actuator to drive a magnetic resonance imaging-compatible hydraulic loading platform. Pressure and actuator position were synchronized with gated magnetic resonance imaging acquisition. Achievable loading rates were slower than those found in normal walking because of a water-hammer effect (pressure wave ringing) in the hydraulic system when the actuator direction was changed rapidly. The subsequent verification tests were, therefore, performed at 0.2 Hz. The unloaded displacement accuracy of the system was within 0.31%. Compliance, presumably in the system's plastic components, caused a displacement loss of 5.7 mm during a 20-mm actuator test at 1354 N. This was accounted for with a target to actual calibration curve. The positional accuracy of the HyPSTER during loaded displacement verification tests from 3 to 9 mm against a silicone backstop was 95.9% with a precision of 98.7%. The HyPSTER generated minimal artifact in the magnetic resonance imaging scanner. Careful analysis of the synchronization of the HyPSTER and the magnetic resonance imaging scanner was performed. With some limitations, the HyPSTER provided key functionality in measuring dynamic, patient-specific plantar soft tissue mechanical properties.

Anatomically informed metrics for connectivity-based cortical parcellation from diffusion MRI.

Connectivity information derived from diffusion MRI can be used to parcellate the cerebral cortex into anatomically and functionally meaningful subdivisions. Acquisition and processing parameters can significantly affect parcellation results, and there is no consensus on best practice protocols. We propose a novel approach for evaluating parcellation based on measuring the degree to which parcellation conforms to known principles of brain organization, specifically cortical field homogeneity and interhemispheric homology. The proposed metrics are well behaved on morphologically generated whole-brain parcels, where they correctly identify contralateral homologies and give higher scores to anatomically versus arbitrarily generated parcellations. The measures show that individual cortical fields have characteristic connectivity profiles that are compact and separable, and that the topological arrangement of such fields is strongly conserved between hemispheres and individuals. The proposed metrics can be used to evaluate the quality of parcellations at the subject and group levels and to improve acquisition and data processing for connectivity-based cortical parcellation.

Transcranial magnetic stimulation in the treatment of chronic widespread pain: a randomized controlled study.

OBJECTIVE: Our objective was to assess transcranial magnetic stimulation (TMS) in the treatment of chronic widespread pain. METHODS: Nineteen participants were randomized into 2 groups: one group receiving active TMS (n = 7) and another group receiving sham stimulation (n = 11) applied to the left dorsolateral prefrontal cortex. During sham stimulation, subjects heard a sound similar to the sound heard by those receiving the active treatment and received an active electrical stimulus to the scalp. The stimulation protocol consisted of 15 sessions completed within a 4-week period. Blind assessments were done at baseline and after each 5 sessions followed by blind assessments at 1 week, 1 month, and 3 months after the last TMS sessions. The primary outcome variable was a pain measure, the Gracely Box Intensity Scale (BIRS). RESULTS: The percentage of subjects who guessed that they were receiving TMS was similar in the 2 groups. Both the TMS group and the sham group showed a statistically significant reduction in the BIRS scores from baseline during the acute phase of treatment and the follow-up phase. However, the TMS and sham groups did not differ in the change in the BIRS scores. DISCUSSION: Although some previous clinical studies and basic science studies of TMS in treating pain are promising, this study found no difference in the analgesic effect of TMS and sham stimulation. Future studies should use a sham condition that attempts to simulate the sound and sensation of the TMS stimulation. Stimulus location and other stimulus parameters should be explored in future studies.

Robust registration of longitudinal spine CT.

Accurate and reliable registration of longitudinal spine images is essential for assessment of disease progression and surgical outcome. Implementing a fully automatic and robust registration for clinical use, however, is challenging since standard registration techniques often fail due to poor initial alignment. The main causes of registration failure are the small overlap between scans which focus on different parts of the spine and/or substantial change in shape (e.g. after correction of abnormal curvature) and appearance (e.g. due to surgical implants). To overcome these issues we propose a registration approach which incorporates estimates of vertebrae locations obtained from a learning-based classification method. These location priors are used to initialize the registration and to provide semantic information within the optimization process. Quantitative evaluation on a database of 93 patients with a total of 276 registrations on longitudinal spine CT demonstrate that our registration method significantly reduces the number of failure cases.

No change in neuropsychological functioning after receiving repetitive transcranial magnetic stimulation treatment for major depression.

Early studies of transcranial magnetic stimulation (TMS) have shown no adverse effects on neuropsychological function. However, further research using higher TMS intensities as well as a greater number of TMS pulses and with larger sample sizes is needed. We studied 68 patients with major depressive disorder who were randomized to receive either 15 sessions of sham or real TMS at 110% of the estimated prefrontal cortex threshold to the left dorsolateral prefrontal cortex. Each session consisted of 32 5-second trains of 10-Hz repetitive TMS at 110% adjusted motor threshold. A total of 24,000 pulses were given. Neuropsychological function was assessed before and immediately after TMS treatment with a battery of 8 tests. Using a higher TMS intensity as well as a greater number of pulses and having a larger sample size compared with most previous studies, this study found no negative neuropsychological effects of TMS. Changes in neuropsychological function were unrelated to changes in depression.

Angiographic perfusion imaging: real-time assessment of endovascular treatment for cerebral vasospasm.

BACKGROUND AND PURPOSE: Cerebral perfusion analysis is useful in the diagnosis and treatment of cerebral vasospasm. A new modality of real-time cerebral perfusion imaging and analysis has been developed using standard 2-dimensional angiography. We report our initial experience with this technique to assess response to therapy during endovascular vasospasm procedures. METHODS: Colorized angiographic perfusion maps were obtained immediately before and after endovascular vasospasm treatment. Semiquantitative perfusion parameters (cerebral blood flow, cerebral blood volume, mean transit time, and time to peak) were calculated from time-density curves obtained from intraarterial contrast injection. The effects of intraarterial vasospasm therapy were assessed. RESULTS: Eight vascular territories in 4 patients with vasospasm underwent interventional angiography and angiographic perfusion analysis. Pretreatment perfusion maps demonstrated variable perfusion deficits in specific vascular territories. After endovascular treatment in 6 vessels, improvement was seen to varying degrees in both angiographic appearance and perfusion parameters. Clinical improvement and reduction in transcranial Doppler velocity was also observed. CONCLUSIONS: Real-time angiographic perfusion imaging is feasible during endovascular procedures for vasospasm. Perfusion analysis may aid in assessment of efficacy of the intervention. Comparison with traditional perfusion imaging is needed to validate this technique.

Marker-based validation of a biplane fluoroscopy system for quantifying foot kinematics.

INTRODUCTION: Radiostereometric analysis has demonstrated its capacity to track precise motion of the bones within a subject during motion. Existing devices for imaging the body in two planes are often custom built systems; we present here the design and marker-based validation of a system that has been optimized to image the foot during gait. METHODS: Mechanical modifications were made to paired BV Pulsera C-arms (Philips Medical Systems) to allow unfettered gait through the imaging area. Image quality improvements were obtained with high speed cameras and the correction of image distorting artifacts. To assess the system's accuracy, we placed beads at known locations throughout the imaging field, and used post processing software to calculate their apparent locations. RESULTS: Distortion correction reduced overall RMS error from 6.56 mm to 0.17 mm. When tracking beads in static images a translational accuracy of 0.094 ± 0.081 mm and rotational accuracy of 0.083 ± 0.068° was determined. In dynamic trials simulating speeds seen during walking, accuracy was 0.126 ± 0.122 mm. DISCUSSION: The accuracies and precisions found are within the reported ranges from other such systems. With the completion of marker-based validation, we look to model-based validation of the foot during gait.