An Evaluation of Distinct Volumetric and Functional MRI Contributions Toward Understanding Age and Task Performance: A Study in the Basal Ganglia

Prior work by our group and others has implicated the basal ganglia as important in age-related differences in tasks involving motor response control. The present study used structural and functional MRI approaches to analyze this region of interest (ROI) toward better understanding the contributions of structural and functional MRI measures to understanding age-related and task performance-related cognitive differences. Eleven healthy elders were compared with 11 healthy younger adults while they completed the “go” portion of a complex Go/No-go task. Separate ROI\u27s in the bilateral caudate (C) and putamen/globus pallidus (PGp) were studied based upon previous findings of age-related functional MRI differences in basal ganglia for this portion of the task. Structural volumes and functional activation (in percent area under the curve during correct responses) were independently extracted for these ROI\u27s. Results showed that age correlated with ROI volume in bilateral PGp and C, while multiple task performance measures correlated with functional activation in the left PGp. The Go/No-go task measures were also significantly correlated with traditional attention and executive functioning measures. Importantly, fMRI activation and volumes from each ROI were not significantly inter-correlated. These findings suggest that structural and functional MRI make unique contributions to the study of performance changes in aging

Alzheimer's Disease Prediction Using Longitudinal and Heterogeneous Magnetic Resonance Imaging

Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer's disease (AD) prediction and diagnosis. While traditional MRI-based diagnosis uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main difficulties arise in longitudinal MRI-based diagnosis: (1) the inconsistent longitudinal scans among subjects (i.e., different scanning time and different total number of scans); (2) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a novel feature selection and estimation method which can be applied to extract features from the heterogeneous longitudinal MRI. A key ingredient of our method is the combination of smoothing splines and the $l_1$-penalty. We perform experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results corroborate the advantages of the proposed method for AD prediction in longitudinal studies

MRI of the axial skeleton in spondyloarthritis : the many faces of new bone formation

Spondyloarthritis has two hallmark features: active inflammation and structural lesions with new bone formation. MRI is well suited to assess active inflammation, but there is increasing interest in the role of structural lesions at MRI. Recent MRI studies have examined the established features of new bone formation and demonstrated some novel features which show diagnostic value and might even have potential as possible markers of disease progression. Although MRI is not the first imaging modality that comes into mind for assessment of bony changes, these features of new bone formation can be detected on MRI-if one knows how to recognize them. This review illustrates the MRI features of new bone formation and addresses possible pitfalls

Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

First published online: 04 December 2019Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61-82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM-but not HC volume alone-predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults

Multi-Contrast MRI Reconstruction with Structure-Guided Total Variation

Magnetic resonance imaging (MRI) is a versatile imaging technique that allows different contrasts depending on the acquisition parameters. Many clinical imaging studies acquire MRI data for more than one of these contrasts---such as for instance T1 and T2 weighted images---which makes the overall scanning procedure very time consuming. As all of these images show the same underlying anatomy one can try to omit unnecessary measurements by taking the similarity into account during reconstruction. We will discuss two modifications of total variation---based on i) location and ii) direction---that take structural a priori knowledge into account and reduce to total variation in the degenerate case when no structural knowledge is available. We solve the resulting convex minimization problem with the alternating direction method of multipliers that separates the forward operator from the prior. For both priors the corresponding proximal operator can be implemented as an extension of the fast gradient projection method on the dual problem for total variation. We tested the priors on six data sets that are based on phantoms and real MRI images. In all test cases exploiting the structural information from the other contrast yields better results than separate reconstruction with total variation in terms of standard metrics like peak signal-to-noise ratio and structural similarity index. Furthermore, we found that exploiting the two dimensional directional information results in images with well defined edges, superior to those reconstructed solely using a priori information about the edge location.Comment: 18 pages, 16 figure

Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks

Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive microstructure assessment technique. Scalar measures, such as FA (fractional anisotropy) and MD (mean diffusivity), quantifying micro-structural tissue properties can be obtained using diffusion models and data processing pipelines. However, it is costly and time consuming to collect high quality diffusion data. Here, we therefore demonstrate how Generative Adversarial Networks (GANs) can be used to generate synthetic diffusion scalar measures from structural T1-weighted images in a single optimized step. Specifically, we train the popular CycleGAN model to learn to map a T1 image to FA or MD, and vice versa. As an application, we show that synthetic FA images can be used as a target for non-linear registration, to correct for geometric distortions common in diffusion MRI

Diagnostic value of MRI of the sacroiliac joints in juvenile spondyloarthritis

Early diagnosis of spondyloarthritis (SpA) is becoming more important as new medical treatment options have become available to treat inflammation and delay progression of the disease. Increasingly, magnetic resonance imaging (MRI) of the sacroiliac joints is obtained for early detection of inflammatory changes, as it shows active inflammatory and structural lesions of sacroiliitis long before radiographic changes become evident. MRI of the sacroiliac joints in children is a useful tool for suspected juvenile spondyloarthritis (JSpA), even though it is not yet included in the current pediatric classification systems. Recognizing MRI features of pediatric sacroiliitis is a challenge. As most radiologists are not familiar with the normal MRI appearance of the pediatric sacroiliac joint, clear definitions are mandatory. Actually, the adult Assessment of Spondyloarthritis International Society (ASAS) definition for sacroiliitis needs some adaptations for children. A proposal for a possible pediatric-specific definition for active sacroiliitis on MRI is presented in this review. Furthermore, MRI without contrast administration is sufficient to identify bone marrow edema (BME), capsulitis, and retroarticular enthesitis as features of active sacroiliitis in JSpA. In selected cases, when high short tau inversion recovery (STIR) signal in the joint is the only finding, gadolinium-enhanced images may help to confirm the presence of synovitis. Lastly, we found a high correlation between pelvic enthesitis and sacroiliitis on MRI of the sacroiliac joints in children. As pelvic enthesitis indicates active inflammation, it may play a role in assessment of the inflammatory status. Therefore, it should be carefully sought and noted when examining MRI of the sacroiliac joints in children

Microtesla MRI of the human brain combined with MEG

One of the challenges in functional brain imaging is integration of complementary imaging modalities, such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). MEG, which uses highly sensitive superconducting quantum interference devices (SQUIDs) to directly measure magnetic fields of neuronal currents, cannot be combined with conventional high-field MRI in a single instrument. Indirect matching of MEG and MRI data leads to significant co-registration errors. A recently proposed imaging method - SQUID-based microtesla MRI - can be naturally combined with MEG in the same system to directly provide structural maps for MEG-localized sources. It enables easy and accurate integration of MEG and MRI/fMRI, because microtesla MR images can be precisely matched to structural images provided by high-field MRI and other techniques. Here we report the first images of the human brain by microtesla MRI, together with auditory MEG (functional) data, recorded using the same seven-channel SQUID system during the same imaging session. The images were acquired at 46 microtesla measurement field with pre-polarization at 30 mT. We also estimated transverse relaxation times for different tissues at microtesla fields. Our results demonstrate feasibility and potential of human brain imaging by microtesla MRI. They also show that two new types of imaging equipment - low-cost systems for anatomical MRI of the human brain at microtesla fields, and more advanced instruments for combined functional (MEG) and structural (microtesla MRI) brain imaging - are practical.Comment: 8 pages, 5 figures - accepted by JM