Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data.Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T1-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions.Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes.Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.</p

Ultra-high field MR spectroscopic imaging in neurodegenerative disorders

Magnetresonanzspektroskopie Bildgebung (1H MRSI) ist eine nichtinvasive Methode, die es ermöglicht, die räumliche Verteilung von mehreren Metaboliten im Gehirn in vivo abzubilden, die mit pathologischen Veränderungen wie Axonalverlust, neuronaler Schädigung, Entzündung, Demyelinisierung, Glia-Aktivierung, oxidativem Stress oder Exzitotoxizität verbunden sind. Diesen Prozessen liegen verschiedene neurodegenerative oder demyelinisierende Erkrankungen zugrunde, für die derzeit keine Biomarker für eine frühere und/oder differenzierte Diagnose, Prognose oder Therapiebewertung zur Verfügung stehen. Das Ziel dieser Dissertation war es, das klinische Potenzial von hochauflösendem MRSI mit direkter FID-Akquisition (FID-MRSI) bei 7T zu untersuchen. Verschiedene Aspekte im Zusammenhang mit der Erfassung und Quantifizierung der MRSI Daten wurden berücksichtigt. Die Verbesserungen der spektralen Qualität, der Quantifizierungsgenauigkeit und der Effizienz von Messbeschleunigung durch ein ultrahohes Magnetfeld wurden nachgewiesen. Die Menge der zuverlässig abgebildeten Neurometaboliten bei gesunden Probanden wurde durch Myo-Inositol, Taurin, Glutathion, Glutamin oder N-Acetylaspartylglutamat bei 7T im Vergleich zu 3T erweitert. Zusätzlich wurden pathologisch relevante Metaboliten wie Glycin oder Lipide in Hirntumoren detektiert. Die verbesserte Messgeschwindigkeit bei 7T ergab klinisch realisierbare Messzeiten von 6 min, ohne die Quantifizierungsgenauigkeit zu reduzieren. Die erhöhte räumliche Auflösung des FID-MRSI (22 mm2 in der Ebene) ermöglichte es, veränderte neurochemische Profile von kleinen Multiple-Sklerose-Läsionen zu beurteilen, die mit herkömmlichen Auflösungen des MRSI nicht richtig erkannt werden konnten. Die scheinbaren Läsionen auf Stoffwechselkarten mit der erreichten ultrahohen Auflösung glichen eher den makroskopischen Gewebeschäden, die auf der konventionellen MRT sichtbar waren. Die genaue Quantifizierung von FID-MRSI erfordert Informationen über die zugrunde liegenden Beiträge von Makromolekülen mit hohem Molekulargewicht. Ein einzelnes in vivo gemessenes makromolekulares Spektrum, das im Vorwissen des Anpassungsalgorithmus enthalten ist, lieferte eine äußerst zuverlässige Quantifizierung für häufige Neurometaboliten bei gesunden Probanden. Die Parametrisierung des makromolekularen Spektrums ist die bessere Option, wenn erwartet wird, dass das makromolekulare Profil pathologisch verändert ist, als Kompromiss zwischen Quantifizierungsgenauigkeit und Reproduzierbarkeit. Bewegung und Magnetfeldverzerrungen stellen für MRSI eine weitere Herausforderung dar, insbesondere in PatientInnen und bei bewegungsempfindlichen Methoden. Das Ausmaß und die Muster der Kopfbewegung wurden während des MRSI-Scans bei Patienten mit neurodegenerativen Erkrankungen (Morbus Parkinson, leichte kognitive Beeinträchtigung) sowie bei jungen und älteren Menschen untersucht. Volumetrische Navigatoren, die auf die Reduzierung von zeitlichen Bewegungs- und Magnetfeldinstabilitäten zugeschnitten sind, konnten die spektrale Qualität auch bei Patienten mit übermäßiger Kopfbewegung wiederherstellen. Die vorgestellten Ergebnisse zeigen eine zuverlässige und klinisch machbare Darstellung von pathologisch relevanten Neurometaboliten mit hochauflösendem FID-MRSI bei 7T mit Aussicht auf klinische Anwendungen bei neurodegenerativen Erkrankungen.Proton magnetic resonance spectroscopic imaging (1H MRSI) is a non-invasive method that enables in vivo mapping of brain metabolites associated with pathological changes such as axonal loss, neuronal damage, inflammation, demyelination, glial activation, oxidative stress, or excitotoxicity. These processes underlie various neurodegenerative or demyelinating diseases, which currently lack biomarkers for earlier and/or differential diagnosis, prognosis, or treatment assessment. The purpose of this thesis was to investigate the clinical potential of high-resolution MRSI based on direct free induction decay acquisition (FID-MRSI) at 7T. Different aspects related to acquisition and quantification of the spectroscopic imaging data were considered. The improvements in spectral quality, quantification precision and parallel imaging efficiency arising from ultra-high magnetic field were demonstrated in this thesis. The amount of reliably mapped neurometabolites in healthy volunteers was extended by myo-inositol, taurine, glutathione, glutamine, and N-acetylaspartylglutamate at 7T in comparison to 3T. Additional pathologically relevant metabolites such as glycine or lipids were detected in brain tumors. The improved parallel imaging efficiency at 7T yielded clinically feasible measurement times of 6 min without any relevant loss in quantification precision. Increased spatial resolution of FID-MRSI (22 mm2 in-plane) allowed to assess altered neurochemical profiles of small multiple sclerosis lesions, which could not be properly detected with conventional resolutions of MRSI. The apparent lesions on metabolic maps with such ultra-high resolution resembled more closely the macroscopic tissue damage visible on conventional MRI. Accurate quantification of FID-MRSI requires information about underlying contributions from high-molecular-weight macromolecules. An inclusion of a single in vivo measured macromolecular spectrum into prior knowledge of the fitting algorithm provided highly reliable quantification for common brain metabolites in healthy volunteers. Parameterization of the macromolecular spectrum may be preferred when the macromolecular profile is expected to be pathologically changed, as a compromise between quantification accuracy and reproducibility. Motion and magnetic field distortions pose another challenge for MRSI, particularly in patients and for motion-sensitive methods. The extent and patterns of head motion were assessed during the MRSI scans in patients with neurodegenerative diseases (Parkinson's disease, mild cognitive impairment) and in young and elderly healthy controls. Volumetric navigators tailored for mitigation of temporal motion and magnetic field instabilities were able to restore spectral quality also in patients with excessive head motion. The presented results show reliable and clinically feasible mapping of pathologically relevant neurometabolites via high-resolution FID-MRSI at 7T with the prospect to clinical applications in neurodegenerative diseases.Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersArbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprüftMedizinische Universität Wien, Diss., 2019(VLID)458248

Magnetic Resonance in Medicine / Densityweighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T

Purpose Fullslice magnetic resonance spectroscopic imaging at urn:x-wiley:07403194:media:mrm26987:mrm26987-math-0001 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and kspace filtering, but this prolongs scan times and reduces the signaltonoise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNRefficiency further. In this study, we propose an SNRefficient spatialspectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hammingweighted kspace, thus termed densityweightedCONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR. Theory and Methods Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (singleslice, fieldofview 220 220 mm2, matrix 64 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. DensityweightedCONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed eCONCEPT), (b) elliptical phaseencoding, and (c) 5fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phaseencoding. Results By intrinsically sampling a Hammingweighted kspace, densityweightedCONCEPT removed Gibbsringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than eCONCEPT, elliptical phaseencoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phaseencoding (all P < 0.05), respectively, which lead to improved metabolic maps. Conclusion DensityweightedCONCEPT provides clinically attractive fullslice highresolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:28742885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.(VLID)483936

The influence of spatial resolution on the spectral quality and quantification accuracy of whole-brain MRSI at 1.5T, 3T, 7T, and 9.4T

PURPOSE: Inhomogeneities in the static magnetic field (B0 ) deteriorate MRSI data quality by lowering the spectral resolution and SNR. MRSI with low spatial resolution is also prone to lipid bleeding. These problems are increasingly problematic at ultra-high fields. An approach to tackling these challenges independent of B0 -shim hardware is to increase the spatial resolution. Therefore, we investigated the effect of improved spatial resolution on spectral quality and quantification at 4 field strengths. METHODS: Whole-brain MRSI data was simulated for 3 spatial resolutions and 4 B0 s based on experimentally acquired MRI data and simulated free induction decay signals of metabolites and lipids. To compare the spectral quality and quantification, we derived SNR normalized to the voxel size (nSNR), linewidth and metabolite concentration ratios, their Cramer-Rao-lower-bounds (CRLBs), and the absolute percentage error (APE) of estimated concentrations compared to the gold standard for the whole-brain and 8 brain regions. RESULTS: At 7T, we found up to a 3.4-fold improved nSNR (in the frontal lobe) and a 2.8-fold reduced linewidth (in the temporal lobe) for 1 cm3 versus 0.25 cm3 resolution. This effect was much more pronounced at higher and less homogenous B0 (1.6-fold improved nSNR and 1.8-fold improved linewidth in the parietal lobe at 3T). This had direct implications for quantification: the volume of reliably quantified spectra increased with resolution by 1.2-fold and 1.5-fold (when thresholded by CRLBs or APE, respectively). CONCLUSION: MRSI data quality benefits from increased spatial resolution particularly at higher B0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field

Frequency drift in MR spectroscopy at 3T.

PurposeHeating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.MethodA standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).ResultsOf the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p &lt; 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.DiscussionThis study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B-0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed

Frequency drift in MR spectroscopy at 3T

Purpose: Heating of gradient coils and passive shim components is a common cause of instability in the B 0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. Method: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). Results: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. Discussion: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed