50 research outputs found
MR Spectra from rat hippocampus with LCModel quantification and the corresponding basis set
No full text<p>This folder contains the LCModel quantifications of spectra acquired in hippocampus from 7 rats. The spectra were quntified using six different DKNTMN (spline stiffness) values (0.1, 0.25, 0.4, 0.5, 1, 5). In the folder Control_files_Basis_set you can find all the control files used in this quantification along with the corresponding basis set (metabolites/simulated using NMRScopeB from jMRUI and <em>in vivo </em>parameters + full MM spectrum).</p>
<p>Please cite the following manuscript if you are using the data</p>
<p><a href="https://pubmed.ncbi.nlm.nih.gov/34268821/">In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times - PubMed (nih.gov)</a><br> </p>
Processing of MM signals acquired in vivo at 9.4T using 1H SVS
No full text<p>Processing of MM signals acquired in vivo at 9.4T using 1H SVS @ <a href="https://www.epfl.ch/labs/mrs4brain/">MRS4Brain research group</a>. </p>
<p>The video was recording during a presentation done by Dunja Simicic for the Virtual jMRUI Training Course @ <a href="https://inspire-med.eu/events">INSPiRE-MED EU project </a>H2020-MSCA-ITN-2018, no 813120. </p>
<p>Please use the VLC media player to view this video.</p>
<p>Please cite the following article if you are using the protocol described herein: <a href="https://pubmed.ncbi.nlm.nih.gov/34268821/">In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times - PubMed (nih.gov)</a></p>
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<div>Magn Reson Med</div>
. 2021 Nov;86(5):2384-2401.</div>
doi: 10.1002/mrm.28910. Epub 2021 Jul 15.</div>
<h1>In vivo macromolecule signals in rat brain <sup>1</sup> H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T<sub>2</sub> relaxation times</h1>
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<div><a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Simicic+D&cauthor_id=34268821">Dunja Simicic</a><sup> <a title="CIBM Center for Biomedical Imaging, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-1">1</a> <a title="Animal Imaging and Technology, EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-2">2</a> <a title="Laboratory for functional and metabolic imaging (LIFMET), EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-3">3</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Rackayova+V&cauthor_id=34268821">Veronika Rackayova</a><sup> <a title="CIBM Center for Biomedical Imaging, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-1">1</a> <a title="Animal Imaging and Technology, EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-2">2</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Xin+L&cauthor_id=34268821">Lijing Xin</a><sup> <a title="CIBM Center for Biomedical Imaging, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-1">1</a> <a title="Animal Imaging and Technology, EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-2">2</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Tk%C3%A1%C4%8D+I&cauthor_id=34268821">Ivan Tkáč</a><sup> <a title="Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-4">4</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Borbath+T&cauthor_id=34268821">Tamas Borbath</a><sup> <a title="High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-5">5</a> <a title="Faculty of Science, University of Tübingen, Tübingen, Germany." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-6">6</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Starcuk+Z+Jr&cauthor_id=34268821">Zenon Starcuk Jr</a><sup> <a title="Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-7">7</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Starcukova+J&cauthor_id=34268821">Jana Starcukova</a><sup> <a title="Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-7">7</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Lanz+B&cauthor_id=34268821">Bernard Lanz</a><sup> <a title="Laboratory for functional and metabolic imaging (LIFMET), EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-3">3</a></sup>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=pubdate&term=Cudalbu+C&cauthor_id=34268821">Cristina Cudalbu</a><sup> <a title="CIBM Center for Biomedical Imaging, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-1">1</a> <a title="Animal Imaging and Technology, EPFL, Lausanne, Switzerland." href="https://pubmed.ncbi.nlm.nih.gov/34268821/#full-view-affiliation-2">2</a></sup></div>
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Advanced metabolite mapping at ultra-high field using 1H-MRS, 1H-MRSI and macromolecules: applications in a rat model of type C hepatic encephalopathy
No full textMagnetic Resonance Spectroscopy (MRS) is the only technique capable of measuring a large number of metabolites simultaneously in vivo. Ultra-high magnetic fields (UHF) combined with ultra-short echo time (TE) sequences allow the detection of high-quality 1H MR spectra and the quantification of 20 different metabolites in the brain (markers of energy metabolism, osmoregulation etc.).
In vivo brain localized 1H MR spectra at short TEs contain the contribution of mobile macromolecules (MM). Reliable detection and fitting of MM are crucial for accurate quantification. Higher spectral resolution at UHF led to increased interest in using a parametrized MM spectrum and flexible spline baselines to address unpredicted spectroscopic components.
In this thesis the MM spectra (from the rat brain at 9.4T) were characterized using an improved methodological approach for their post-processing, fitting and quantification. This method provided an efficient tool for parametrization of the MM spectrum into individual components and estimation of their T2app relaxation times. An extensive assessment on how the MM spectrum and spline baseline stiffness affect the metabolite and MM quantification is also reported
Type C hepatic encephalopathy (HE) is a complication of chronic liver disease (CLD). Children and adults respond differently to CLD and its related toxic accumulation of molecules (i.e. ammonium (NH4+), glutamine (Gln)). Children with CLD may grow up with significant neurocognitive deficits even after liver transplantation. Despite considerable advances in understanding the pathogenesis of type C HE, the exact metabolic mechanisms and their regional variations are not fully understood.
The advantages of UHF short TE 1H MRS were used herein to describe the regional distribution of metabolites in the developing and adult brain using the bile duct ligated model (BDL) of type C HE (adult and postnatal day 21 rats). Three brain regions were assessed (hippocampus, cerebellum and striatum) pointing towards cerebellum as a region with the heaviest burden of Gln and unique metabolic response. Changes in cell morphology were followed longitudinally and related to the metabolic alterations. Elevated oxidative stress is reported using electron paramagnetic resonance, together with the decreased antioxidants (1H MRS) emphasizing its important role in HE. The brain regional measurements confirmed the higher susceptibility of developing brain to the disease and the increased vulnerability of cerebellum. Finally, the beneficial effect of Cr supplementation on the neurometabolic profile is described using 1H MRS and 31P MRS in CLD pups (BDL at postnatal day 15) suggesting that an appropriate treatment may have significant public health impact.
MRSI is a powerful tool to non-invasively and spatially map the brain regional distribution of metabolites in vivo. While MRSI in human brain is increasingly used, preclinical MRSI is not widely applied mainly due to the small rodent brain, long acquisition times and low signal to noise ratio.
The implementation of a novel approach: free induction decay (FID) MRSI on the 14.1T preclinical scanner is described herein. This method offers a fast and robust data acquisition with high spatial resolution resulting in high quality spectroscopic maps. Finally, preliminary assessment of the effect of two noise reduction techniques (MP-PCA and TGV reconstruction) on the spectra from preclinical MRSI datasets is briefly presented.LIFME
Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling.
No full textNoise-reduction techniques for 1H-FID-MRSI at 14.1T: Monte-Carlo validation & in vivo application
No full textProton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool
that enables the multidimensional non-invasive mapping of the neurochemical
profile at high-resolution over the entire brain. The constant demand for
higher spatial resolution in 1H-MRSI led to increased interest in
post-processing-based denoising methods aimed at reducing noise variance. The
aim of the present study was to implement two noise-reduction techniques, the
Marchenko-Pastur principal component analysis (MP-PCA) based denoising and the
low-rank total generalized variation (LR-TGV) reconstruction, and to test their
potential and impact on preclinical 14.1T fast in vivo 1H-FID-MRSI datasets.
Since there is no known ground truth for in vivo metabolite maps, additional
evaluations of the performance of both noise-reduction strategies were
conducted using Monte-Carlo simulations. Results showed that both denoising
techniques increased the apparent signal-to-noise ratio SNR while preserving
noise properties in each spectrum for both in vivo and Monte-Carlo datasets.
Relative metabolite concentrations were not significantly altered by either
methods and brain regional differences were preserved in both synthetic and in
vivo datasets. Increased precision of metabolite estimates was observed for the
two methods, with inconsistencies noted on lower concentrated metabolites. Our
study provided a framework on how to evaluate the performance of MP-PCA and
LR-TGV methods for preclinical 1H-FID MRSI data at 14.1T. While gains in
apparent SNR and precision were observed, concentration estimations ought to be
treated with care especially for low-concentrated metabolites.Comment: Brayan Alves and Dunja Simicic are joint first authors. Currently in
revision for NMR in Biomedicin
Neurometabolic changes in a rat pup model of type C HE - 1H MRS dataset (hippocampus)
No full text1H MRS in hippocampus was used to study longitudinally the effect of chronic liver disease (bile duct ligated rat model) in the brain (type C hepatic encephalopathy) of animals having developed disease a post natal day 15 (p15) corresponding to ~4 months old human brain. The dataset contains MR spectra and LCModel Quanifications from 7 bile duct ligated and 8 control animals at week 2, 4 and 6 after surgery
MP-PCA denoising for diffusion MRS data: promises and pitfalls.
No full textDiffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4T in rat brain and at 3T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered
Fast high-resolution metabolite mapping in the rat brain using 1H-FID-MRSI at 14.1T
No full textMagnetic resonance spectroscopic imaging (MRSI) enables the simultaneous non-invasive acquisition of MR spectra from multiple spatial locations inside the brain. While 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical settings, mostly because of difficulties specifically related to very small nominal voxel size in the rodent brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio SNR.
In this context, we implemented a free induction decay 1H-MRSI sequence (1H-FID-MRSI) in the rat brain at 14.1T. We combined the advantages of 1H-FID-MRSI with the ultra-high magnetic field to achieve higher SNR, coverage and spatial resolution in the rodent brain, and developed a custom dedicated processing pipeline with a graphical user interface: MRS4Brain toolbox.
LCModel fit, using the simulated metabolite basis-set and in-vivo measured MM, provided reliable fits for the data at acquisition delays of 1.3 and 0.94 ms. The resulting Cramér-Rao lower bounds were sufficiently low (<30%) for eight metabolites of interest, leading to highly reproducible metabolic maps. Similar spectral quality and metabolic maps were obtained between 1 and 2 averages, with slightly better contrast and brain coverage due to increased SNR in the latter case. Furthermore, the obtained metabolic maps were accurate enough to confirm the previously known brain regional distribution of some metabolites. The acquisitions proved high reproducibility over time.
We demonstrated that the increased SNR and spectral resolution at 14.1T can be translated into high spatial resolution in 1H-FID-MRSI of the rat brain in 13 minutes, using the sequence and processing pipeline described herein. High-resolution 1H-FID-MRSI at 14.1T provided reproducible and high-quality metabolic mapping of brain metabolites with significantly reduced technical limitations.Dunja Simicic and Brayan Alves are joint first author
1H-FID-MRSI LIVE DEMO @14.1T
No full text<p>Live demos of 1H-FID-MRSI- acquisitions at 14.1T by <a href="https://www.epfl.ch/labs/mrs4brain/">MRS4Brain research group</a> @ CIBM MRI EPFL AIT. Two live demos recorded directly on our 14.1T scanner containing the protocol used to acquired FID-MRSI data sets, including the imaging performed before the FID-MRSI acquisitions. The protocol used to acquired in vivo macromolecules with FID-MRSI is also presented in the video from 22/02/2024. Please open the videos with VLC media player.</p>
<p>Please cite the following article if you are using the protocol and sequence described herein</p>
<p><em>“Fast high-resolution metabolite mapping in the rat brain using 1 H-FID-MRSI at 14.1T” </em></p>
<p><em>Dunja Simicic, Brayan Alves, Jessie Mosso, Guillaume Briand, Thanh Phong Lê, Ruud B. van Heeswijk, Jana Starčuková, Bernard Lanz, Antoine Klauser, Bernhard Strasser, Wolfgang Bogner, Cristina Cudalbu</em></p>
<p><em>under review in NMR in Biomed</em></p>
Neurometabolic profiles of bile duct ligated rats after the treatment with an urease inhibitor – 1H MRS dataset
No full text<p>1H MRS in the cerebellum was used to study the effect of 2-octynohydroxamic acid (2-octynoHA) treatment on the brain of bile duct ligated (BDL) rats (type C hepatic encephalopathy). The study included four groups of rats: negative control group (rats received a drug-free solution), suspension group (rats received a suspension of 2-octynoHA; 30 mg/kg, twice daily), solution group (rats received a solution of 2-octynoHA, 30 mg/kg, twice daily) and capsule group (rats received 2-octynoHA in enteric capsules; 10 mg once daily). 1H MRS measurements were performed on day 39 post-BDL surgery corresponding to the last day of treatment. The dataset contains RAW spectra (metabolites and water) prepared for LCModel quantification.</p>
<p>Funded by Carigest</p>
