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MR Imaging the spinal cord of non-human primates (NHP), such as squirrel monkey, is important since the injuries in NHP resemble those that afflict human spinal cords. Our previous studies have reported a multi-parametric MRI protocol, including functional MRI, diffusion tensor imaging, quantitative magnetization transfer and chemical exchange saturation transfer, which allows non-invasive detection and monitoring of injury-associated structural, functional and molecular changes over time. High signal-to-noise ratio (SNR) is critical for obtaining high-resolution images and robust estimates of MRI parameters. In this work, we describe our construction and use of a single channel coil designed to maximize the SNR for imaging the squirrel monkey cervical spinal cord in a 21 cm bore magnet at 9.4 T. We first numerically optimized the coil dimension of a single loop coil and then evaluated the benefits of a quadrature design. We then built an optimized coil based on the simulation results and compared its SNR performance with a non-optimized single coil in both phantoms and in vivo.
Copyright © 2020 Elsevier Inc. All rights reserved.
PURPOSE - Chemical exchange saturation transfer (CEST) is an MRI technique sensitive to the presence of low-concentration solute protons exchanging with water. However, magnetization transfer (MT) effects also arise when large semisolid molecules interact with water, which biases CEST parameter estimates if quantitative models do not account for macromolecular effects. This study establishes under what conditions this bias is significant and demonstrates how using an appropriate model provides more accurate quantitative CEST measurements.
METHODS - CEST and MT data were acquired in phantoms containing bovine serum albumin and agarose. Several quantitative CEST and MT models were used with the phantom data to demonstrate how underfitting can influence estimates of the CEST effect. CEST and MT data were acquired in healthy volunteers, and a two-pool model was fit in vivo and in vitro, whereas removing increasing amounts of CEST data to show biases in the CEST analysis also corrupts MT parameter estimates.
RESULTS - When all significant CEST/MT effects were included, the derived parameter estimates for each CEST/MT pool significantly correlated (P < .05) with bovine serum albumin/agarose concentration; minimal or negative correlations were found with underfitted data. Additionally, a bootstrap analysis demonstrated that significant biases occur in MT parameter estimates (P < .001) when unmodeled CEST data are included in the analysis.
CONCLUSIONS - These results indicate that current practices of simultaneously fitting both CEST and MT effects in model-based analyses can lead to significant bias in all parameter estimates unless a sufficiently detailed model is utilized. Therefore, care must be taken when quantifying CEST and MT effects in vivo by properly modeling data to minimize these biases.
© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
PURPOSE - Transcranial focused ultrasound (FUS) is increasingly being explored to modulate neuronal activity. To target neuromodulation, researchers often localize the FUS beam onto the brain region(s) of interest using spatially tracked tools overlaid on pre-acquired images. Here, we quantify the accuracy of optically tracked image-guided FUS with magnetic resonance imaging (MRI) thermometry, evaluate sources of error and demonstrate feasibility of these procedures to target the macaque somatosensory region.
METHODS - We developed an optically tracked FUS system capable of projecting the transducer focus onto a pre-acquired MRI volume. To measure the target registration error (TRE), we aimed the transducer focus at a desired target in a phantom under image guidance, heated the target while imaging with MR thermometry and then calculated the TRE as the difference between the targeted and heated locations. Multiple targets were measured using either an unbiased or bias-corrected calibration. We then targeted the macaque S1 brain region, where displacement induced by the acoustic radiation force was measured using MR acoustic radiation force imaging (MR-ARFI).
RESULTS - All calibration methods enabled registration with TRE on the order of 3 mm. Unbiased calibration resulted in an average TRE of 3.26 mm (min-max: 2.80-4.53 mm), which was not significantly changed by prospective bias correction (TRE of 3.05 mm; 2.06-3.81 mm, p = 0.55). Restricting motion between the transducer and target and increasing the distance between tracked markers reduced the TRE to 2.43 mm (min-max: 0.79-3.88 mm). MR-ARFI images showed qualitatively similar shape and extent as projected beam profiles in a living non-human primate.
CONCLUSIONS - Our study describes methods for image guidance of FUS neuromodulation and quantifies errors associated with this method in a large animal. The workflow is efficient enough for in vivo use, and we demonstrate transcranial MR-ARFI in vivo in macaques for the first time.
PURPOSE - MR fingerprinting (MRF) sequences permit efficient T and T estimation in cranial and extracranial regions, but these areas may include substantial fat signals that bias T and T estimates. MRI fat signal fraction estimation is also a topic of active research in itself, but may be complicated by B heterogeneity and blurring during spiral k-space acquisitions, which are commonly used for MRF. An MRF method is proposed that separates fat and water signals, estimates water T and T, and accounts for B effects with spiral blurring correction, in a single sequence.
THEORY AND METHODS - A k-space-based fat-water separation method is further extended to unbalanced steady-state free precession MRF with swept echo time. Repeated application of this k-space fat-water separation to demodulated forms of the measured data allows a B map and correction to be approximated. The method is compared with MRF without fat separation across a broad range of fat signal fractions (FSFs), water Ts and Ts, and under heterogeneous static fields in simulations, phantoms, and in vivo.
RESULTS - The proposed method's FSF estimates had a concordance correlation coefficient of 0.990 with conventional measurements, and reduced biases in the T and T estimates due to fat signal relative to other MRF sequences by several hundred ms. The B correction improved the FSF, T, and T estimation compared to those estimates without correction.
CONCLUSION - The proposed method improves MRF water T and T estimation in the presence of fat and provides accurate FSF estimation with inline B correction.
Copyright © 2019 Elsevier Inc. All rights reserved.
BACKGROUND - Misidentifying parathyroid glands (PGs) during thyroidectomies or parathyroidectomies could significantly increase postoperative morbidity. Imaging systems based on near infrared autofluorescence (NIRAF) detection can localize PGs with high accuracy. These devices, however, depict NIRAF images on remote display monitors, where images lack spatial context and comparability with actual surgical field of view. In this study, we designed an overlay tissue imaging system (OTIS) that detects tissue NIRAF and back-projects the collected signal as a visible image directly onto the surgical field of view instead of a display monitor, and tested its ability for enhancing parathyroid visualization.
STUDY DESIGN - The OTIS was first calibrated with a fluorescent ink grid and initially tested with parathyroid, thyroid, and lymph node tissues ex vivo. For in vivo measurements, the surgeon's opinion on tissue of interest was first ascertained. After the surgeon looked away, the OTIS back-projected visible green light directly onto the tissue of interest, only if the device detected relatively high NIRAF as observed in PGs. System accuracy was determined by correlating NIRAF projection with surgeon's visual confirmation for in situ PGs or histopathology report for excised PGs.
RESULTS - The OTIS yielded 100% accuracy when tested ex vivo with parathyroid, thyroid, and lymph node specimens. Subsequently, the device was evaluated in 30 patients who underwent thyroidectomy and/or parathyroidectomy. Ninety-seven percent of exposed tissue of interest was visualized correctly as PGs by the OTIS, without requiring display monitors or contrast agents.
CONCLUSIONS - Although OTIS holds novel potential for enhancing label-free parathyroid visualization directly within the surgical field of view, additional device optimization is required for eventual clinical use.
Copyright © 2019 American College of Surgeons. Published by Elsevier Inc. All rights reserved.
PURPOSE - To improve multichannel compressed sensing (CS) reconstruction for MR proton resonance frequency (PRF) shift thermography, with application to MRI-induced RF heating evaluation and MR guided high intensity focused ultrasound (MRgFUS) temperature monitoring.
METHODS - A new compressed sensing reconstruction is proposed that enforces joint low rank and sparsity of complex difference domain PRF data between post heating and baseline images. Validations were performed on 4 retrospectively undersampled dynamic data sets in PRF applications, by comparing the proposed method to a previously described L and total variation- (TV-) based CS approach that also operates on complex difference domain data, and to a conventional low rank plus sparse (L+S) separation-based CS reconstruction applied to the original domain data.
RESULTS - In all 4 retrospective validations, the proposed reconstruction method outperformed the conventional L+S and L +TV CS reconstruction methods with a 3.6× acceleration ratio in terms of temperature accuracy with respect to fully sampled data. For RF heating evaluation, the proposed method achieved RMS error of 12%, compared to 19% for the L+S method and 17% for the L +TV method. For in vivo MRgFUS thalamotomy, the peak temperature reconstruction errors were 19%, 31%, and 35%, respectively.
CONCLUSION - The complex difference-based low rank and sparse model enhances compressibility for dynamic PRF temperature imaging applications. The proposed multichannel CS reconstruction method enables high acceleration factors for PRF applications including RF heating evaluation and MRgFUS sonication.
© 2019 International Society for Magnetic Resonance in Medicine.
LEVEL OF EVIDENCE - 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.
© 2019 International Society for Magnetic Resonance in Medicine.
Diffusion weighted MRI (DWMRI) and the myriad of analysis approaches (from tensors to spherical harmonics and brain tractography to body multi-compartment models) depend on accurate quantification of the apparent diffusion coefficient (ADC). Signal drift during imaging (e.g., due to b0 drift associated with heating) can cause systematic non-linearities that manifest as ADC changes if not corrected. Herein, we present a case study on two phantoms on one scanner. Different scan protocols exhibit different degrees of drift during similar scans and may be sensitive to the order of scans within an exam. Vos et al. recently reviewed the effects of signal drift in DWMRI acquisitions and proposed a temporal model for correction. We propose a novel spatial-temporal model to correct for higher order aspects of the signal drift and derive a statistically robust variant. We evaluate the Vos model and propose a method using two phantoms that mimic the ADC of the relevant brain tissue (0.36-2.2 × 10-3 mm/s) on a single 3 T scanner. The phantoms are (1) a spherical isotropic sphere consisting of a single concentration of polyvinylpyrrolidone (PVP) and (2) an ice-water phantom with 13 vials of varying PVP concentrations. To characterize the impact of interspersed minimally weighted volumes ("b0's"), image volumes with b-value equal to 0.1 s/mm are interspersed every 8, 16, 32, 48, and 96 diffusion weighted volumes in different trials. Signal drift is found to have spatially varying effects that are not accounted for with temporal-only models. The novel model captures drift more accurately (i.e., reduces the overall change per-voxel over the course of a scan) and results in more consistent ADC metrics.
Copyright © 2018 Elsevier Inc. All rights reserved.
A fiber optic probe-based Raman spectroscopy system using a single laser module with two excitation wavelengths, at 680 and 785 nm, has been developed for measuring the fingerprint and high wavenumber regions using a single detector. This system is simpler and less expensive than previously reported configurations of combined fingerprint and high wavenumber Raman systems, and its probe-based implementation facilitates numerous in vivo applications. The high wavenumber region of the Raman spectrum ranges from 2800-3800 cm-1 and contains valuable information corresponding to the molecular vibrations of proteins, lipids, and water, which is complimentary to the biochemical signatures found in the fingerprint region (800-1800 cm-1), which probes DNA, lipids, and proteins. The efficacy of the system is demonstrated by tracking changes in water content in tissue-mimicking phantoms, where Voigtian decomposition of the high wavenumber water peak revealed a correlation between the water content and type of water-tissue interactions in the samples. This dual wavelength system was then used for in vivo assessment of cervical remodeling during mouse pregnancy, a physiologic process with known changes in tissue hydration. The system shows that Raman spectroscopy is sensitive to changes in collagen content in the fingerprint region and hydration state in the high wavenumber region, which was verified using an ex vivo comparison of wet and dry weight. Simultaneous fingerprint and high wavenumber Raman spectroscopy will allow precise in vivo quantification of tissue water content in the high wavenumber region, paired with the high biochemical specificity of the fingerprint region.
PURPOSE - The non-uniform fast Fourier transform (NUFFT) involves interpolation of non-uniformly sampled Fourier data onto a Cartesian grid, an interpolation that is slowed by complex, non-local data access patterns. A faster NUFFT would increase the clinical relevance of the plethora of advanced non-Cartesian acquisition methods.
METHODS - Here we customize the NUFFT procedure for a radial trajectory and GPU architecture to eliminate the bottlenecks encountered when allowing for arbitrary trajectories and hardware. We call the result TRON, for TRajectory Optimized NUFFT. We benchmark the speed and accuracy TRON on a Shepp-Logan phantom and on whole-body continuous golden-angle radial MRI.
RESULTS - TRON was 6-30× faster than the closest competitor, depending on test data set, and was the most accurate code tested.
CONCLUSIONS - Specialization of the NUFFT algorithm for a particular trajectory yielded significant speed gains. TRON can be easily extended to other trajectories, such as spiral and PROPELLER. TRON can be downloaded at http://github.com/davidssmith/TRON.
© 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.