The Role of CT and MR Imaging in Stereotactic Body Radiotherapy of the Spine: From Patient Selection and Treatment Planning to Post-Treatment Monitoring.

Spine metastases (SMs) are common, arising in 70% of the cases of the most prevalent malignancies in males (prostate cancer) and females (breast cancer). Stereotactic body radiotherapy, or SBRT, has been incorporated into clinical treatment algorithms over the past decade. SBRT has shown promising rates of local control for oligometastatic spinal lesions with low radiation dose to adjacent critical tissues, particularly the spinal cord.

Integrated multimodal cell atlas of Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies.

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

Unlabelled: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convolutional neural network.

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.

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.

Generalizability of Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs Using an Adaptation of the Modified-2 Algorithm-Based Qualitative Criteria.

Rationale And Objectives: Spinal osteoporotic compression fractures (OCFs) can be an early biomarker for osteoporosis but are often subtle, incidental, and underreported. To ensure early diagnosis and treatment of osteoporosis, we aimed to build a deep learning vertebral body classifier for OCFs as a critical component of our future automated opportunistic screening tool.

Materials And Methods: We retrospectively assembled a local dataset, including 1790 subjects and 15,050 vertebral bodies (thoracic and lumbar).

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.

Integrated multimodal cell atlas of Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types.

Osteoporosis identification among previously undiagnosed individuals with vertebral fractures.

Unlabelled: Because osteoporosis is under-recognized in patients with vertebral fractures, we evaluated characteristics associated with osteoporosis identification. Most patients with vertebral fractures did not receive evaluation or treatment for osteoporosis. Black, younger, and male participants were particularly unlikely to have had recognized osteoporosis, which could increase their risk of negative outcomes.

Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

Rationale And Objectives: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic compression fractures (OCFs), an osteoporosis biomarker, are often incidental and under-reported. Accurate automated opportunistic OCF screening can increase the diagnosis rate and ensure adequate treatment.

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.

DicomAnnotator: a Configurable Open-Source Software Program for Efficient DICOM Image Annotation.

Modern, supervised machine learning approaches to medical image classification, image segmentation, and object detection usually require many annotated images. As manual annotation is usually labor-intensive and time-consuming, a well-designed software program can aid and expedite the annotation process. Ideally, this program should be configurable for various annotation tasks, enable efficient placement of several types of annotations on an image or a region of an image, attribute annotations to individual annotators, and be able to display Digital Imaging and Communications in Medicine (DICOM)-formatted images.

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.

Practical Considerations for Radiologists in Implementing a Patient-friendly MRI Experience.

For many patients, numerous unpleasant features of the magnetic resonance imaging (MRI) experience such as scan duration, auditory noise, spatial confinement, and motion restrictions can lead to premature termination or low diagnostic quality of imaging studies. This article discusses practical, patient-oriented considerations that are helpful for radiologists contemplating ways to improve the MRI experience for patients. Patient friendly scanner properties are discussed, with an emphasis on literature findings of effectiveness in mitigating patient claustrophobia, other anxiety, or motion and on reducing scan incompletion rates or need for sedation.

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.

Lumbar Spinal Stenosis Severity by CT or MRI Does Not Predict Response to Epidural Corticosteroid versus Lidocaine Injections.

Background And Purpose: Epidural steroid injections may offer little-to-no short-term benefit in the overall population of patients with symptomatic spinal stenosis compared with lidocaine alone. We investigated whether imaging could identify subgroups of patients who might benefit most.

Materials And Methods: A secondary analysis of the Lumbar Epidural Steroid Injections for Spinal Stenosis prospective, double-blind trial was performed, and patients were randomized to receive an epidural injection of lidocaine with or without corticosteroids.

Ambient temperature and solar insolation are associated with decreased prevalence of SSRI-treated psychiatric disorders.

Serotonergic function is known to fluctuate in association with light and temperature. Serotonin-related behaviors and disorders similarly vary with climatic exposure, but the associations are complex. This complexity may reflect the importance of dose and timing of exposure, as well as acclimation.

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.

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.

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.

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.

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]).