pinecone/core-2020-05-10-deduplication huggingface dataset:
A ranking of diffusion MRI compartment models with in vivo human brain data

PURPOSE: Diffusion magnetic resonance imaging (MRI) microstructure imaging provides a unique noninvasive probe into tissue microstructure. The technique relies on biophysically motivated mathematical models, relating microscopic tissue features to the magnetic resonance (MR) signal. This work aims to determine which compartment models of diffusion MRI are best at describing measurements from in vivo human brain white matter. METHODS: Recent work shows that three compartment models, designed to capture intra-axonal, extracellular, and isotropically restricted diffusion, best explain multi-b-value data sets from fixed rat corpus callosum. We extend this investigation to in vivo by using a live human subject on a clinical scanner. The analysis compares models of one, two, and three compartments and ranks their ability to explain the measured data. We enhance the original methodology to further evaluate the stability of the ranking. RESULTS: As with fixed tissue, three compartment models explain the data best. However, a clearer hierarchical structure and simpler models emerge. We also find that splitting the scanning into shorter sessions has little effect on the ranking of models, and that the results are broadly reproducible across sessions. CONCLUSION: Three compartments are required to explain diffusion MR measurements from in vivo corpus callosum, which informs the choice of model for microstructure imaging applications in the brain
Approximate Fourier Domain Expression for Bloch-Siegert Shift

Cataloged from PDF version of article.PurposeIn this study, a new simple Fourier domain-based analytical expression for the Bloch-Siegert (BS) shift-based B-1 mapping method is proposed to obtain vertical bar b(1)(+)vertical bar more accurately while using short BS pulse durations and small off-resonance frequencies. 

Theory and MethodsA new simple analytical expression for the BS shift is derived by simplifying the Bloch equations. In this expression, the phase is calculated in terms of the Fourier transform of the radiofrequency pulse envelope, and thus making the off- and on-resonance effects more easily understandable. To verify the accuracy of the proposed expression, Bloch simulations and MR experiments are performed for the hard, Fermi, and Shinner-Le Roux pulse shapes. 

ResultsAnalyses of the BS phase shift-based B-1 mapping method in terms of radiofrequency pulse shape, pulse duration, and off-resonance frequency show that vertical bar b(1)(+)vertical bar can be obtained more accurately with the aid of this new expression. 

ConclusionsIn this study, a new simple frequency domain analytical expression is proposed for the BS shift. Using this expression, vertical bar b(1)(+)vertical bar values can be predicted from the phase data using the frequency spectrum of the radiofrequency pulse. This method works well even for short pulse durations and small offset frequencies. Magn Reson Med 73:117-125, 2015. (c) 2014 Wiley Periodicals, Inc
A general linear relaxometry model of R1 using imaging data.

PURPOSE: The longitudinal relaxation rate (R1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort.
METHODS: Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps.
RESULTS: The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort.
CONCLUSION: A single set of global coefficients can be used to relate R1 , MT, and R2 * across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309-1314, 2015. © 2014 Wiley Periodicals, Inc
High-resolution diffusion-weighted brain MRI under motion

Magnetic resonance imaging is one of the fastest developing medical imaging techniques. It provides excellent soft tissue contrast and has been a leading tool for neuroradiology and neuroscience research over the last decades. One of the possible MR imaging contrasts is the ability to visualize diffusion processes. The method, referred to as diffusion-weighted imaging, is one of the most common clinical contrasts but is prone to artifacts and is challenging to acquire at high resolutions.



This thesis aimed to improve the resolution of diffusion weighted imaging, both in a clinical and in a research context. While diffusion-weighted imaging traditionally has been considered a 2D technique the manuscripts and methods presented here explore 3D diffusion acquisitions with isotropic resolution. Acquiring multiple small 3D volumes, or slabs, which are combined into one full volume has been the method of choice in this work.



The first paper presented explores a parallel imaging driven multi-echo EPI readout to enable high resolution with reduced geometric distortions. The work performed on diffusion phase correction lead to an understanding that was used for the subsequent multi-slab papers.



The second and third papers introduce the diffusion-weighted 3D multi-slab echo-planar imaging technique and explore its advantages and performance. As the method requires a slightly increased acquisition time the need for prospective motion correction became apparent.



The forth paper suggests a new motion navigator using the subcutaneous fat surrounding the skull for rigid body head motion estimation, dubbed FatNav. The spatially sparse representation of the fat signal allowed for high parallel imaging acceleration factors, short acquisition times, and reduced geometric distortions of the navigator.



The fifth manuscript presents a combination of the high-resolution 3D multi-slab technique and a modified FatNav module. Unlike our first FatNav implementation, using a single sagittal slab, this modified navigator acquired orthogonal projections of the head using the fat signal alone.



The combined use of both presented methods provides a promising start for a fully motion corrected high-resolution diffusion acquisition in a clinical setting
Self-navigated isotropic three-dimensional cardiac T2 mapping.

PURPOSE: To implement and characterize an isotropic three-dimensional cardiac T2 mapping technique.
METHODS: A self-navigated three-dimensional radial segmented balanced steady-state free precession pulse sequence with an isotropic 1.7-mm spatial resolution was implemented at 3T with a variable T2 preparation module. Bloch equation and Monte Carlo simulations were performed to determine the influence of the heart rate, B1 inhomogeneity and noise on the T2 fitting accuracy. In a phantom study, the accuracy of the pulse sequence was studied through comparison with a gold-standard spin-echo T2 mapping method. The robustness and homogeneity of the technique were ascertained in a study of 10 healthy adult human volunteers, while first results obtained in patients are reported.
RESULTS: The numerical simulations demonstrated that the heart rate and B1 inhomogeneity cause only minor deviations in the T2 fitting, whereas the phantom study showed good agreement of the technique with the gold standard. The volunteer study demonstrated an average myocardial T2 of 40.5 ± 3.3 ms and a &lt;15% T2 gradient in the base-apex and anterior-inferior direction. In three patients, elevated T2 values were measured in regions with expected edema.
CONCLUSION: This respiratory self-navigated isotropic three-dimensional technique allows for accurate and robust in vitro and in vivo T2 quantification. Magn Reson Med 73:1549-1554, 2015. © 2014 Wiley Periodicals, Inc
Single acquisition electrical property mapping based on relative coil sensitivities: A proof-of-concept demonstration.

PURPOSE: All methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases.
THEORY AND METHODS: To demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes.
RESULTS: The method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood.
CONCLUSION: The proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc
Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering

Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion Purpose To investigate whether nonlinear dimensionality reduction improves unsupervised classification of 1H MRS brain tumor data compared with a linear method. Methods In vivo single-voxel 1H magnetic resonance spectroscopy (55 patients) and 1H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. Results An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With 1H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. Conclusion The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of 1H MRSI data after cluster analysis
POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): A general algorithm for reducing motion-related artifacts.

PURPOSE: A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion-weighted imaging. THEORY: Images with reduced artifacts are reconstructed with an iterative projection onto convex sets (POCS) procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. METHODS: The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved diffusion-weighted imaging data corresponding to different k-space trajectories and matrix condition numbers. RESULTS: Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. CONCLUSION: POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods
Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruc- tion of Breath-Hold Cardiac Cine MRI

Purpose: Compressed sensing methods with motion estimation and compensation techniques
have been proposed for the reconstruction of accelerated dynamic MRI. However, artifacts that
naturally arise in compressed sensing reconstruction procedures hinder the estimation of motion
from reconstructed images, especially at high acceleration factors. This work introduces a robust
groupwise non-rigid motion estimation technique applied to the compressed sensing reconstruction
of dynamic cardiac cine MRI sequences.
Theory and Methods: A spatio-temporal regularized, groupwise, non-rigid registration method
based on a B-splines deformation model and a least squares metric is used to estimate and to
compensate the movement of the heart in breath-hold cine acquisitions and to obtain a quasi-static
sequence with highly sparse representation in temporally transformed domains.
Results: Short axis in vivo datasets are used for validation, both original multi-coil as well as
DICOM data. Fully sampled data were retrospectively undersampled with various acceleration
factors and reconstructions were compared with the two well-known methods k-t FOCUSS and
MASTeR. The proposed method achieves higher signal to error ratio and structure similarity index
for medium to high acceleration factors.
Conclusions: Reconstruction methods based on groupwise registration show higher quality recon-
structions for cardiac cine images than the pairwise counterparts tested
Multi-institutional validation of a novel textural analysis tool for preoperative stratification of suspected thyroid tumors on diffusion weighted MRI

PURPOSE: Ultrasound-guided fine needle aspirate cytology fails to diagnose many malignant thyroid nodules; consequently, patients may undergo diagnostic lobectomy. This study assessed whether textural analysis (TA) could noninvasively stratify thyroid nodules accurately using diffusion-weighted MRI (DW-MRI).
METHODS: This multi-institutional study examined 3T DW-MRI images obtained with spin echo echo planar imaging sequences. The training data set included 26 patients from Cambridge, United Kingdom, and the test data set included 18 thyroid cancer patients from Memorial Sloan Kettering Cancer Center (New York, New York, USA). Apparent diffusion coefficients (ADCs) were compared over regions of interest (ROIs) defined on thyroid nodules. TA, linear discriminant analysis (LDA), and feature reduction were performed using the 21 MaZda-generated texture parameters that best distinguished benign and malignant ROIs.
RESULTS: Training data set mean ADC values were significantly different for benign and malignant nodules (P = 0.02) with a sensitivity and specificity of 70% and 63%, respectively, and a receiver operator characteristic (ROC) area under the curve (AUC) of 0.73. The LDA model of the top 21 textural features correctly classified 89/94 DW-MRI ROIs with 92% sensitivity, 96% specificity, and an AUC of 0.97. This algorithm correctly classified 16/18 (89%) patients in the independently obtained test set of thyroid DW-MRI scans.
CONCLUSION: TA classifies thyroid nodules with high sensitivity and specificity on multi-institutional DW-MRI data sets. This method requires further validation in a larger prospective study.Grant sponsor: Cancer Research UK Cambridge Institute; Grant number:
C14303/A17197; Grant sponsor: Addenbrooke’s Charitable Trust; Grant
sponsor: University of Cambridge; Grant sponsor: Cambridge Experimental
Cancer Medicine Centre; Grant sponsor: National Institute for Health
Research Cambridge Biomedical Research Centre; Grant sponsor: National
Cancer Institute/National Institutes of Health; Grant numbers:
1R21CA176660-01A1 and P50 CA172012-01A1.This is the final version. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/mrm.25743/abstract;jsessionid=0FB537018C6841C60A3A7244C3702BC2.f03t02
Development of Timd2 as a Reporter Gene for MRI

Purpose: To assess the potential of an MRI gene reporter
based on the ferritin receptor Timd2 (T-cell immunoglobulin
and mucin domain containing protein 2), using T1- and T2-
weighted imaging.
Methods: Pellets of cells that had been modified to express
the Timd2 transgene, and incubated with either iron-loaded or
manganese-loaded ferritin, were imaged using T1- and T2-
weighted MRI. Mice were also implanted subcutaneously with
Timd2-expressing cells and the resulting xenograft tissue
imaged following intravenous injection of ferritin using T2-
weighted imaging.
Results: Timd2-expressing cells, but not control cells, showed
a large increase in both R2 and R1 in vitro following incubation
with iron-loaded and manganese-loaded ferritin, respectively.
Expression of Timd2 had no effect on cell viability or proliferation;
however, manganese-loaded ferritin, but not iron-loaded
ferritin, was toxic to Timd2-expressing cells. Timd2-expressing
xenografts in vivo showed much smaller changes in R2 following
injection of iron-loaded ferritin than the same cells incubated
in vitro with iron-loaded ferritin.
Conclusion: Timd2 has demonstrated potential as an MRI
reporter gene, producing large increases in R2 and R1 with ferritin
and manganese-loaded ferritin respectively in vitro, although
more modest changes in R2 in vivo. Manganese-loaded apoferritin
was not used in vivo due to the toxicity observed in
vitro.This work was supported
by the Medical Research Council and Cancer Research UK (CRUK) doctoral training grants (to P.S.P.) and a
CRUK Program Grant to K.M.B. T.B.R. was in receipt of
Intra-European Marie Curie and Long-Term European
Molecular Biology Organization fellowships.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1002/mrm.25750/abstract
Motion-insensitive determination of B1+ amplitudes based on the bloch-siegert shift in single voxels of moving organs including the human heart.

PURPOSE\ud
\ud
To reliably determine the amplitude of the transmit radiofrequency ( B1+) field in moving organs like the liver and heart, where most current techniques are usually not feasible.\ud
\ud
METHODS\ud
\ud
B1+ field measurement based on the Bloch-Siegert shift induced by a pair of Fermi pulses in a double-triggered modified Point RESolved Spectroscopy (PRESS) sequence with motion-compensated crusher gradients has been developed. Performance of the sequence was tested in moving phantoms and in muscle, liver, and heart of six healthy volunteers each, using different arrangements of transmit/receive coils.\ud
\ud
RESULTS\ud
\ud
B1+ determination in a moving phantom was almost independent of type and amplitude of the motion and agreed well with theory. In vivo, repeated measurements led to very small coefficients of variance (CV) if the amplitude of the Fermi pulse was chosen above an appropriate level (CV in muscle 0.6%, liver 1.6%, heart 2.3% with moderate amplitude of the Fermi pulses and 1.2% with stronger Fermi pulses).\ud
\ud
CONCLUSION\ud
\ud
The proposed sequence shows a very robust determination of B1+ in a single voxel even under challenging conditions (transmission with a surface coil or measurements in the heart without breath-hold). Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc
Diffusion MRI with concurrent magnetic field monitoring

PURPOSE: Diffusion MRI is compromised by unknown field perturbation during image encoding. The purpose of this study was to address this problem using the recently described approach of concurrent magnetic field monitoring.\ud
METHODS: Magnetic field dynamics were monitored during the echo planar imaging readout of a common diffusion-weighted MRI sequence using an integrated magnetic field camera setup. The image encoding including encoding changes over the duration of entire scans were quantified and analyzed. Field perturbations were corrected by accounting for them in generalized image reconstruction. The impact on image quality along with geometrical congruence among different diffusion-weighted images was assessed both qualitatively and quantitatively.\ud
RESULTS: The most significant field perturbations were found to be related to higher-order eddy currents from diffusion-weighting gradients and B0 field drift as well as gradual changes of short-term eddy current behavior and mechanical oscillations during the scan. All artifacts relating to dynamic field perturbations were eliminated by incorporating the measured encoding in image reconstruction.\ud
CONCLUSION: Concurrent field monitoring combined with generalized reconstruction enhances depiction fidelity in diffusion imaging. In addition to artifact reduction, it improves geometric congruence and thus facilitates image combination for quantitative diffusion analysis