scholarly journals Navigator-Free Submillimeter Diffusion Imaging Using Multishot-Encoded Simultaneous Multi-Slice (MUSIUM)

2020 ◽  
Author(s):  
Wei-Tang Chang ◽  
Khoi Huynh ◽  
Pew-Thian Yap ◽  
Weili Lin
Keyword(s):  
Signal To Noise Ratio ◽  
Diffusion Imaging ◽  
Brain Structures ◽  
Peak Amplitude ◽  
Acquisition Time ◽  
Rf Power ◽  
Isotropic Resolution ◽  
Low Snr ◽  
Scan Time

Abstract The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures. One of the major challenges in submillimeter dMRI is the inherently low signal-to-noise ratio (SNR). While approaches capable of mitigating the low SNR have been proposed, namely simultaneous multi-slab (SMSlab) and generalized slice dithered enhanced resolution with simultaneous multislice (gSlider-SMS), limitations are associated with these approaches. The SMSlab sequences suffer from the slab boundary artifacts and require additional navigators for phase estimation. On the other hand, gSlider sequences require relatively high RF power and peak amplitude, which increase the SAR and complicate the RF excitation. In this work, we developed a navigator-free multishot-encoded simultaneous multi-slice (MUSIUM) imaging approach, achieving enhanced SNR, low RF power and peak amplitude, and being free from slab boundary artifacts. The dMRI with ultrahigh resolution (0.86 mm isotropic), whole brain coverage and ~12.5 minute acquisition time were achieved, revealing detailed structures at cortical and white matter areas. The simulated and in vivo results also demonstrated that the MUSIUM imaging was minimally affected by the motion. Taken together, the MUSIUM imaging is a promising approach to achieve submillimeter diffusion imaging on 3T scanner within clinically feasible scan time.

scholarly journals 2½-minute 3D 7T 31P-MRSI of the human heart using concentric rings (CRT)

2021 ◽  
Author(s):  
William T Clarke ◽  
Lukas Hingerl ◽  
Bernhard Strasser ◽  
Wolfgang Bogner ◽  
Ladislav Valkovic ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Variable Number ◽  
Low Rank ◽  
Acquisition Time ◽  
Temporal Data ◽  
Scan Time ◽  
Spread Function ◽  
3D Acquisition ◽  
Spatio Temporal ◽  
31P Mrsi

A 3D density-weighted concentric ring trajectory (CRT) MRSI sequence is implemented for cardiac 31P-MRS at 7T. The point-by-point k-space sampling of traditional phase-encoded CSI sequences severely restricts the minimum scan time at higher spatial resolutions. Our proposed CRT sequence implements a stack of concentric rings trajectory, with a variable number of rings and planes spaced to optimise the density of k-space weighting. This creates flexibility in acquisition time, allowing acquisitions substantially faster than traditional phase-encoded CSI sequences, while retaining high SNR. We first characterise the signal-to-noise ratio and point spread function of the CRT sequence in phantoms. We then evaluate it at five different acquisition times and spatial resolutions in the hearts of five healthy participants at 7T. These different sequence durations are compared with existing published 3D acquisition-weighted CSI sequences with matched acquisition times and spatial resolutions. To minimise the effect of noise on the short acquisitions, low-rank denoising of the spatio-temporal data was also performed after acquisition. The proposed sequence measures 3D localised PCr/ATP ratios of the human myocardium in 2.5 minutes, 2.6 times faster than the minimum scan time for the acquisition-weighted phase-encoded CSI. Alternatively, in the same scan time a 1.7-times smaller nominal voxel volume can be achieved. Low-rank denoising reduced the variance of measured PCr/ATP ratios by 11% across all protocols. The faster acquisitions permitted by 7T CRT 31P-MRSI could make cardiac stress protocols or creatine kinase rate measurements (which involve repeated scans) more tolerable for patients without sacrificing spatial resolution.

scholarly journals Whole-Brain High-Resolution Metabolite Mapping with 3D Compressed-Sensing-SENSE-LowRank 1H FID-MRSI

2020 ◽  
Author(s):  
Antoine Klauser ◽  
Paul Klauser ◽  
Frédéric Grouiller ◽  
Sebastien Courvoisier ◽  
Francois Lazeyras
Keyword(s):  
High Resolution ◽  
Brain Regions ◽  
Low Rank ◽  
Acquisition Time ◽  
Resonance Spectroscopy ◽  
Brain Anatomy ◽  
Reconstruction Technique ◽  
Whole Brain ◽  
Isotropic Resolution

There is a growing interest of the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopy imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time which severely limits its applications for clinical or research purposes. We developed a novel acquisition-reconstruction technique combining fast 1H-FID-MRSI sequence accelerated by random k-space undersampling and a low-rank and total-generalized variation (TGV) constrained model. This framework was applied to the brain of four healthy volunteers. Following 20 min acquisition, reconstruction and quantification, the resulting metabolic maps with a 5 mm isotropic resolution reflected the detailed neurochemical composition of all brain regions and revealed part of the underlying brain anatomy. Contrasts and features from the 3D metabolite distributions were in agreement with the literature and consistent across the four subjects. The successful combination of the 3D 1H-FID-MRSI with a constrained reconstruction enables the detailed mapping of metabolite concentrations at high-resolution in the whole brain and with an acquisition time that is compatible with clinical or research settings.

scholarly journals Phased-array combination of 2D MRS for lipid composition quantification in patients with breast cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Vasiliki Mallikourti ◽  
Sai Man Cheung ◽  
Tanja Gagliardi ◽  
Nicholas Senn ◽  
Yazan Masannat ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lipid Composition ◽  
Optimal Algorithm ◽  
Signal To Noise Ratio ◽  
Breast Tumour ◽  
Correlation Spectroscopy ◽  
Acquisition Time ◽  
Double Quantum ◽  
Internal Reference

AbstractLipid composition in breast cancer, a central marker of disease progression, can be non-invasively quantified using 2D MRS method of double quantum filtered correlation spectroscopy (DQF-COSY). The low signal to noise ratio (SNR), arising from signal retention of only 25% and depleted lipids within tumour, demands improvement approaches beyond signal averaging for clinically viable applications. We therefore adapted and examined combination algorithms, designed for 1D MRS, for 2D MRS with both internal and external references. Lipid composition spectra were acquired from 17 breast tumour specimens, 15 healthy female volunteers and 25 patients with breast cancer on a clinical 3 T MRI scanner. Whitened singular value decomposition (WSVD) with internal reference yielded maximal SNR with an improvement of 53.3% (40.3–106.9%) in specimens, 84.4 ± 40.6% in volunteers, 96.9 ± 54.2% in peritumoural adipose tissue and 52.4% (25.1–108.0%) in tumours in vivo. Non-uniformity, as variance of improvement across peaks, was low at 21.1% (13.7–28.1%) in specimens, 5.5% (4.2–7.2%) in volunteers, 6.1% (5.0–9.0%) in peritumoural tissue, and 20.7% (17.4–31.7%) in tumours in vivo. The bias (slope) in improvement ranged from − 1.08 to 0.21%/ppm along the diagonal directions. WSVD is therefore the optimal algorithm for lipid composition spectra with highest SNR uniformly across peaks, reducing acquisition time by up to 70% in patients, enabling clinical applications.

scholarly journals Capabilities of multi-pinhole SPECT with two stationary detectors for in vivo rat imaging

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jan P. Janssen ◽  
Jan V. Hoffmann ◽  
Takayuki Kanno ◽  
Naoko Nose ◽  
Jan-Peter Grunz ◽  
...  
Keyword(s):  
Image Quality ◽  
Point Source ◽  
Single Photon ◽  
Photon Emission ◽  
Small Animal ◽  
Acquisition Time ◽  
Emission Computed Tomography ◽  
Scan Time ◽  
Spect System

Abstract We aimed to investigate the image quality of the U-SPECT5/CT E-Class a micro single-photon emission computed tomography (SPECT) system with two large stationary detectors for visualization of rat hearts and bones using clinically available 99mTc-labelled tracers. Sensitivity, spatial resolution, uniformity and contrast-to-noise ratio (CNR) of the small-animal SPECT scanner were investigated in phantom studies using an ultra-high-resolution rat and mouse multi-pinhole collimator (UHR-RM). Point source, hot-rod, and uniform phantoms with 99mTc-solution were scanned for high-count performance assessment and count levels equal to animal scans, respectively. Reconstruction was performed using the similarity-regulated ordered-subsets expectation maximization (SROSEM) algorithm with Gaussian smoothing. Rats were injected with ~ 100 MBq [99mTc]Tc-MIBI or ~ 150 MBq [99mTc]Tc-HMDP and received multi-frame micro-SPECT imaging after tracer distribution. Animal scans were reconstructed for three different acquisition times and post-processed with different sized Gaussian filters. Following reconstruction, CNR was calculated and image quality evaluated by three independent readers on a five-point scale from 1 = “very poor” to 5 = “very good”. Point source sensitivity was 567 cps/MBq and radioactive rods as small as 1.2 mm were resolved with the UHR-RM collimator. Collimator-dependent uniformity was 55.5%. Phantom CNR improved with increasing rod size, filter size and activity concentration. Left ventricle and bone structures were successfully visualized in rat experiments. Image quality was strongly affected by the extent of post-filtering, whereas scan time did not have substantial influence on visual assessment. Good image quality was achieved for resolution range greater than 1.8 mm in bone and 2.8 mm in heart. The recently introduced small animal SPECT system with two stationary detectors and UHR-RM collimator is capable to provide excellent image quality in heart and bone scans in a rat using standardized reconstruction parameters and appropriate post-filtering. However, there are still challenges in achieving maximum system resolution in the sub-millimeter range with in vivo settings under limited injection dose and acquisition time.

MRI: How to perform a pediatric scan

2013 ◽  
Vol 54 (9) ◽  
pp. 991-997 ◽  
Author(s):  
Øystein E Olsen
Keyword(s):  
Signal To Noise Ratio ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Acquisition Time ◽  
Artifact Reduction ◽  
Resonance Imaging ◽  
Basic Principles ◽  
Low Snr ◽  
Patient Preparation ◽  
Magnetic Resonance Imaging Mri

Magnetic resonance imaging (MRI) is rich in diagnostic information but requires optimization for use in children. The main problems are motion artifacts and poor signal-to-noise ratio (SNR). SNR is proportional to voxel volume, which must therefore not be too small, however, usually needs to be reduced compared to adult imaging to account for the finer anatomy of the child. The use of multi-channel coils with element sizes appropriate for the anatomy of interest ensures optimal baseline SNR. Longer acquisition time increases SNR (with a square-root factor), but the flip-side is that this allows more motion artifacts. Attention to patient preparation and to techniques for motion artifact reduction is therefore crucial, and the most important principles are discussed. Low SNR may in part be compensated by optimizing the image contrast by weighting (tissue and lesions T1 and T2 may differ from adults) and by using contrast agents. It is also powerful to combine different image contrasts during postprocessing. The basic principles are discussed, followed by an example scan protocol.

scholarly journals The SIGMA rat brain templates and atlases for multimodal MRI data analysis and visualization

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
D. A. Barrière ◽  
R. Magalhães ◽  
A. Novais ◽  
P. Marques ◽  
E. Selingue ◽  
...  
Keyword(s):  
Rat Brain ◽  
Ex Vivo ◽  
Brain Mri ◽  
Brain Structures ◽  
Isotropic Resolution ◽  
Complete Set ◽  
Multimodal Mri ◽  
Preclinical Mri ◽  
Neuroimaging Software

AbstractPreclinical imaging studies offer a unique access to the rat brain, allowing investigations that go beyond what is possible in human studies. Unfortunately, these techniques still suffer from a lack of dedicated and standardized neuroimaging tools, namely brain templates and descriptive atlases. Here, we present two rat brain MRI templates and their associated gray matter, white matter and cerebrospinal fluid probability maps, generated from ex vivo $${\mathrm{T}}_2^ \ast$$T2*-weighted images (90 µm isotropic resolution) and in vivo T2-weighted images (150 µm isotropic resolution). In association with these templates, we also provide both anatomical and functional 3D brain atlases, respectively derived from the merging of the Waxholm and Tohoku atlases, and analysis of resting-state functional MRI data. Finally, we propose a complete set of preclinical MRI reference resources, compatible with common neuroimaging software, for the investigation of rat brain structures and functions.

scholarly journals Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps

2021 ◽  
Author(s):  
Fang F Yu ◽  
Susie Yi Huang ◽  
Ashwin Kumar ◽  
Thomas Witzel ◽  
Congyu Liao ◽  
...  
Keyword(s):  
Acquisition Time ◽  
Proton Density ◽  
Head Orientation ◽  
Sampled Data ◽  
Clinical Implementation ◽  
Isotropic Resolution ◽  
Tissue Volume ◽  
Scan Time ◽  
Time Required ◽  
Parametric Maps

Purpose A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast parametric maps. We sought to reduce the acquisition time for quantitative susceptibility mapping (QSM) and macromolecular tissue volume (MTV) by acquiring both contrasts simultaneously by leveraging their redundancies. The Joint Virtual Coil concept with generalized autocalibrating partially parallel acquisitions (JVC-GRAPPA) was applied to reduce acquisition time further. Methods Three adult volunteers were imaged on a 3T scanner using a multi-echo 3D GRE sequence acquired at three head orientations. MTV, QSM, R2*, T1, and proton density maps were reconstructed. The same sequence (GRAPPA R=4) was performed in subject #1 with a single head orientation for comparison. Fully sampled data was acquired in subject #2, from which retrospective undersampling was performed (R=6 GRAPPA and R=9 JVC-GRAPPA). Prospective undersampling was performed in subject #3 (R=6 GRAPPA and R=9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes. Results Subject #1s multi-orientation and single-orientation MTV maps were not significantly different based on RMSE. For subject #2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject #3. Using QSM, R2*, and MTV, the contributions of myelin and iron content to susceptibility was estimated. Conclusion We have developed a novel strategy to simultaneously acquire data for the reconstruction of five intrinsically co-registered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 minutes using JVC-GRAPPA.

scholarly journals In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fuyixue Wang ◽  
Zijing Dong ◽  
Qiyuan Tian ◽  
Congyu Liao ◽  
Qiuyun Fan ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Parallel Imaging ◽  
Brain Structures ◽  
Test Bed ◽  
Whole Brain ◽  
Isotropic Resolution ◽  
Imaging Reconstruction ◽  
Further Development ◽  
Array Coil

AbstractWe present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing

2020 ◽  
Vol 85 (3) ◽  
pp. 1397-1413
Author(s):  
Maarten Naeyaert ◽  
Jan Aelterman ◽  
Johan Van Audekerke ◽  
Vladimir Golkov ◽  
Daniel Cremers ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Angular Resolution ◽  
Spin Echo ◽  
Diffusion Imaging ◽  
Fast Spin Echo ◽  
High Angular Resolution ◽  
Isotropic Resolution ◽  
Fast Spin

scholarly journals In vivo human whole-brain Connectom diffusion MRI dataset at 760 μm isotropic resolution

2020 ◽  
Author(s):  
Fuyixue Wang ◽  
Zijing Dong ◽  
Qiyuan Tian ◽  
Congyu Liao ◽  
Qiuyun Fan ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Parallel Imaging ◽  
Brain Structures ◽  
Test Bed ◽  
Whole Brain ◽  
Isotropic Resolution ◽  
Imaging Reconstruction ◽  
Further Development ◽  
Array Coil

AbstractWe present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy subject. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity. This comprehensive dataset can also be used as a test bed for new modeling, sub-sampling strategies, denoising and processing algorithms, potentially providing a common testing platform for further development of in vivo high resolution dMRI techniques. Whole brain anatomical T1-weighted and T2-weighted images at submillimeter scale along with field maps are also made available.

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