74 results found
Lally P, Matthews P, Bangerter N, 2021, Unbalanced SSFP for super-resolution in MRI, Magnetic Resonance in Medicine, Vol: 85, Pages: 2477-2489, ISSN: 0740-3194
Purpose: To achieve rapid, low SAR super-resolution imaging by exploiting the characteristic magnetization off-resonance profile in SSFP.Theory and Methods: In the presented technique, low flip angle unbalanced SSFP imaging is used to acquire a series of images at a low nominal resolution which are then combined in a super-resolution strategy analogous to non-linear structured illumination microscopy. This is demonstrated in principle via Bloch simulations and synthetic phantoms, and the performance is quantified in terms of point-spread function (PSF) and signal-to-noise ratio (SNR) for gray and white matter from field strengths of 0.35T to 9.4T. A k-space reconstruction approach is proposed to account for B0 effects. This was applied to reconstruct super-resolution images from a test object at 9.4T.Results: Artifact-free super-resolution images were produced after incorporating sufficient preparation time for the magnetization to approach the steady state. High-resolution images of a test object were obtained at 9.4T, in the presence of considerable B0 inhomogeneity. For gray matter, the highest achievable resolution ranges from 3% of the acquired voxel dimension at 0.35T, to 9% at 9.4T. For white matter, this corresponds to 3% and 10% respectively. Compared to an equivalent segmented gradient echo acquisition at the optimal flip angle, with a fixed TR of 8ms, gray matter has up to 34% of the SNR at 9.4T while using a x10 smaller flip angle. For white matter, this corresponds to 29% with a x11 smaller flip angle.Conclusion: This approach achieves high degrees of super-resolution enhancement with minimal RF power requirements.
Fernquest S, Palmer A, Gammer B, et al., 2019, Compositional MRI of the Hip: Reproducibility, Effect of Joint Unloading, and Comparison of T2 Relaxometry with Delayed Gadolinium-Enhanced Magnetic Resonance Imaging of Cartilage, CARTILAGE, Pages: 194760351984167-194760351984167, ISSN: 1947-6035
Taylor CJ, Tarbox GJ, Bolster BD, et al., 2019, Magnetic resonance imaging-based measurement of internal deformation of vibrating vocal fold models, Journal of the Acoustical Society of America, Vol: 145, Pages: 989-997, ISSN: 0001-4966
A method is presented for tracking the internal deformation of self-oscillating vocal fold models using magnetic resonance imaging (MRI). Silicone models scaled to four times life-size to lower the flow-induced vibration frequency were embedded with fiducial markers in a coronal plane. Candidate marker materials were tested using static specimens, and two materials, cupric sulfate and glass, were chosen for testing in the vibrating vocal fold models. The vibrating models were imaged using a gated MRI protocol wherein MRI acquisition was triggered using the subglottal pressure signal. Two-dimensional image slices at different phases during self-oscillation were captured, and in each phase the fiducial markers were clearly visible. The process was also demonstrated using a three-dimensional scan at two phases. The benefit of averaging to increase signal-to-noise ratio was explored. The results demonstrate the ability to use MRI to acquire quantitative deformation data that could be used, for example, to validate computational models of flow-induced vocal fold vibration and quantify deformation fields encountered by cells in bioreactor studies.
McKibben N, Mendoza M, DiBella E, et al., 2019, Deep Learning Super-FOV for accelerated bSSFP banding reduction, 27th Annual ISMRM conference, May 2019
McKibben N, Tarbox G, Mendoza M, et al., 2019, Analysis of Coil Combination for bSSFP Elliptical Signal Model, 27th Annual ISMRM conference, May 2019
Mendoza M, McKibben N, Tarbox G, et al., 2019, Synthetic Banding for bSSFP Data Augmentation Using Machine Learning, 27th Annual ISMRM conference, May 2019
Schmid AB, Campbell J, Hurley SA, et al., 2018, Feasibility of diffusion tensor and morphologic imaging of peripheral nerves at ultra-high field strength, Investigative Radiology, Vol: 53, Pages: 705-713, ISSN: 0020-9996
Objectives The aim of this study was to describe the development of morphologic and diffusion tensor imaging sequences of peripheral nerves at 7 T, using carpal tunnel syndrome (CTS) as a model system of focal nerve injury.Materials and Methods Morphologic images were acquired at 7 T using a balanced steady-state free precession sequence. Diffusion tensor imaging was performed using single-shot echo-planar imaging and readout-segmented echo-planar imaging sequences. Different acquisition and postprocessing methods were compared to describe the optimal analysis pipeline. Magnetic resonance imaging parameters including cross-sectional areas, signal intensity, fractional anisotropy (FA), as well as mean, axial, and radial diffusivity were compared between patients with CTS (n = 8) and healthy controls (n = 6) using analyses of covariance corrected for age (significance set at P < 0.05). Pearson correlations with Bonferroni correction were used to determine association of magnetic resonance imaging parameters with clinical measures (significance set at P < 0.01).Results The 7 T acquisitions with high in-plane resolution (0.2 × 0.2mm) afforded detailed morphologic resolution of peripheral nerve fascicles. For diffusion tensor imaging, single-shot echo-planar imaging was more efficient than readout-segmented echo-planar imaging in terms of signal-to-noise ratio per unit scan time. Distortion artifacts were pronounced, but could be corrected during postprocessing. Registration of FA maps to the morphologic images was successful. The developed imaging and analysis pipeline identified lower median nerve FA (pisiform bone, 0.37 [SD 0.10]) and higher radial diffusivity (1.08 [0.20]) in patients with CTS compared with healthy controls (0.53 [0.06] and 0.78 [0.11], respectively, P < 0.047). Fractional anisotropy and radial diffusivity strongly correlated with patients' symptoms (r = −0.866 and 0.866, respectively, P = 0.005).Conclusions Our data demonstrate
McKibben N, Mendoza M, Tian Y, et al., 2018, Deep Convolutional Neural Networks for Estimation of Pre-Reconstruction Data Reorderings, ISMRM Machine Learning, October 2018
Mendoza M, McKibben N, Hales L, et al., 2018, Banding Artifact Reduction in Musculoskeletal bSSFO using Deep Learning, ISMRM Machine Learning, October 2018
Martay JLB, Palmer AJR, Bangerter NK, et al., 2018, A preliminary modeling investigation into the safe correction zone for high tibial osteotomy, The Knee, Vol: 25, Pages: 286-295, ISSN: 0968-0160
Tarbox G, Smith C, Bolster BD, et al., 2018, Pressure-Triggered Gated MRI Acquisition of a Vibrating Scaled Vocal Fold Model, Joint Annual Meeting of ISMRM - ESMRMB
Thorneloe L, Bangerter N, Violette V, et al., 2018, Muscle Activation using 3D Cones Sodium, T2-Weighted Imaging, and T2 Mapping: Comparison of Techniques, ISMRM - ESMRMB Joint Annual Meeting
Tarbox G, Nazaran A, Bangerter N, et al., 2018, Iron Deposition in Alzheimer's Dementia Hippocampus is Associated with Increased R2* Values, Joint Annual Meeting of ISMRM - ESMRMB
Alfaro-Almagro F, Jenkinson M, Bangerter NK, et al., 2017, Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank., NeuroImage, Vol: 166, Pages: 400-424, ISSN: 1053-8119
UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.
Palmer A, Fernquest S, Rombach I, et al., 2017, Diagnostic and prognostic value of delayed Gadolinium Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC) in early osteoarthritis of the hip, Osteoarthritis and Cartilage, Vol: 25, Pages: 1468-1477, ISSN: 1063-4584
Kaggie JD, Sapkota N, Thapa B, et al., 2017, Synchronous radial 1 H and 23 Na dual-nuclear MRI on a clinical MRI system, equipped with a broadband transmit channel, Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering, Vol: 46B, Pages: e21347-e21347, ISSN: 1552-5031
Mendoza MA, Valentine J, Bangerter N, 2017, In-Vivo Fat Water Separation with Multiple-Acquisition bSSFP, ISMRM 25th Annual Meeting
Taylor M, Valentine J, Whitaker S, et al., 2017, Field Mapping using bSSFP Elliptical Signal Model, ISMRM 25th Annual Meeting
Nazaran A, Tarbox G, Hartley R, et al., 2017, Difference Image Ultra-Short Echo Time T2* Mapping Using a 3D Cones Trajectory, ISMRM 25th Annual Meeting
Tarbox G, Valentine J, Taylor M, et al., 2017, bSSFP Elliptical Signal Model with GRAPPA Parallel Imaging for Musculoskeletal Applications, ISMRM 25th Annual Meeting
Bangerter NK, Taylor MD, Tarbox GJ, et al., 2016, Quantitative techniques for musculoskeletal MRI at 7 Tesla, Quantitative Imaging in Medicine and Surgery, Vol: 6, Pages: 715-730, ISSN: 2223-4292
Bangerter NK, Tarbox GJ, Taylor MD, et al., 2016, Quantitative sodium magnetic resonance imaging of cartilage, muscle, and tendon, Quantitative Imaging in Medicine and Surgery, Vol: 6, Pages: 699-714, ISSN: 2223-4292
Miller KL, Alfaro-Almagro F, Bangerter NK, et al., 2016, Multimodal population brain imaging in the UK Biobank prospective epidemiological study, Nature Neuroscience, Vol: 19, Pages: 1523-1536, ISSN: 1097-6256
Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.
Wang H, Adluru G, Chen L, et al., 2016, Radial simultaneous multi-slice CAIPI for ungated myocardial perfusion, Magnetic Resonance Imaging, Vol: 34, Pages: 1329-1336, ISSN: 0730-725X
Nazaran A, Wisco JJ, Hageman N, et al., 2016, Methodology for computing white matter nerve fiber orientation in human histological slices, Journal of Neuroscience Methods, Vol: 261, Pages: 75-84, ISSN: 0165-0270
Miller KL, Bangerter N, Almagro FA, et al., 2016, UK Biobank: Brain imaging protocols and first data release, ISMRM 24th Annual Meeting
Whitaker ST, Taylor M, Wang H, et al., 2016, SNR and Banding Artifact Reduction Analysis of Phase-Cycled Elliptical Signal Model bSSFP, ISMRM 24th Annual Meeting of the ISMRM
Howell F, Wang H, Park DJ, et al., 2016, Simultaneous Extraction of ADC and T2, ISMRM 24th Annual Meeting
Park DJ, Bangerter N, Palmer AJR, et al., 2016, Toward a 7T MRI protocol for the evaluation of early osteoarthritis in knee cartilage, ISMRM 24th Annual Meeting
Taylor M, Wang H, Palmer AJR, et al., 2016, Rapid High Resolution Morphological Imaging of Cartilage at 7T: Contrast Optimization and Comparison of DESS, Phase-Cycled bSSFP, and 3D SPACE, ISMRM 24th Annual Meeting
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