Bernhard Strasser
Medical University of Vienna
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Featured researches published by Bernhard Strasser.
NeuroImage | 2014
Wolfgang Bogner; Borjan Gagoski; Aaron T. Hess; Himanshu Bhat; M. Dylan Tisdall; Andre van der Kouwe; Bernhard Strasser; Małgorzata Marjańska; Siegfried Trattnig; P. Ellen Grant; Bruce R. Rosen; Ovidiu C. Andronesi
Gamma-aminobutyric acid (GABA) and glutamate (Glu) are the major neurotransmitters in the brain. They are crucial for the functioning of healthy brain and their alteration is a major mechanism in the pathophysiology of many neuro-psychiatric disorders. Magnetic resonance spectroscopy (MRS) is the only way to measure GABA and Glu non-invasively in vivo. GABA detection is particularly challenging and requires special MRS techniques. The most popular is MEscher-GArwood (MEGA) difference editing with single-voxel Point RESolved Spectroscopy (PRESS) localization. This technique has three major limitations: a) MEGA editing is a subtraction technique, hence is very sensitive to scanner instabilities and motion artifacts. b) PRESS is prone to localization errors at high fields (≥3T) that compromise accurate quantification. c) Single-voxel spectroscopy can (similar to a biopsy) only probe steady GABA and Glu levels in a single location at a time. To mitigate these problems, we implemented a 3D MEGA-editing MRS imaging sequence with the following three features: a) Real-time motion correction, dynamic shim updates, and selective reacquisition to eliminate subtraction artifacts due to scanner instabilities and subject motion. b) Localization by Adiabatic SElective Refocusing (LASER) to improve the localization accuracy and signal-to-noise ratio. c) K-space encoding via a weighted stack of spirals provides 3D metabolic mapping with flexible scan times. Simulations, phantom and in vivo experiments prove that our MEGA-LASER sequence enables 3D mapping of GABA+ and Glx (Glutamate+Gluatmine), by providing 1.66 times larger signal for the 3.02ppm multiplet of GABA+ compared to MEGA-PRESS, leading to clinically feasible scan times for 3D brain imaging. Hence, our sequence allows accurate and robust 3D-mapping of brain GABA+ and Glx levels to be performed at clinical 3T MR scanners for use in neuroscience and clinical applications.
NeuroImage | 2015
Michal Považan; Gilbert Hangel; Bernhard Strasser; Stephan Gruber; Marek Chmelik; Siegfried Trattnig; Wolfgang Bogner
Long echo time (TE) MR spectroscopy (MRS) sequences are sensitive only to metabolites of low molecular weight. At shorter TE, significantly more metabolite signals are detectable, including broad signals of high-molecular-weight macromolecules (MMs). Although the presence of MM resonances can bias metabolite quantification at short TE, proper quantification of MMs is important since MMs themselves may serve as potentially valuable biomarkers for many pathologies. We have therefore developed an FID-based 2D-MR Spectroscopic Imaging (2D-MRSI) sequence to map MMs in healthy brain tissue at 7 T within a scan time of ~17 min and a repetition time of 879 ms. This 2D-MRSI technique provides MM maps over a whole slice (i.e., including cortical gray matter) at an ultra-short acquisition delay of 1.3 ms, using double inversion for efficient nulling of low-molecular-weight metabolites. The optimal sequence parameters were estimated using Bloch simulations, phantom testing, and in vivo validation. The acquired in vivo MM spectra (n=6) included nine distinct MM peaks in the range of ~0.9-3.7 ppm. The measured average MM spectrum was incorporated into the LCModel basis set and utilized for further quantification of MRSI data sets without metabolite nulling, which were acquired in five additional volunteers. The quantification results for two basis sets, one including the MMs and one without MM spectrum, were compared. Due to the high spectral resolution and full signal detection provided by the FID-MRSI sequence, we could successfully map five important brain metabolites. Most quantified metabolite signal amplitudes were significantly lower since the inclusion of MMs into the basis set corrected the overestimation of metabolite signals. The precision of fit (i.e., Cramér Rao lower bounds) remained unchanged. Our MM maps show that the overall MM contribution was higher in gray matter than in white matter. In conclusion, the acquired MM spectrum improved the accuracy of metabolite quantification and allowed the acquisition of high spatial resolution maps of five major brain metabolites and also MMs.
NMR in Biomedicine | 2015
Gilbert Hangel; Bernhard Strasser; Michal Považan; Stephan Gruber; Marek Chmelik; Martin Gajdošík; Siegfried Trattnig; Wolfgang Bogner
This work presents a new approach for high‐resolution MRSI of the brain at 7 T in clinically feasible measurement times. Two major problems of MRSI are the long scan times for large matrix sizes and the possible spectral contamination by the transcranial lipid signal. We propose a combination of free induction decay (FID)‐MRSI with a short acquisition delay and acceleration via in‐plane two‐dimensional generalised autocalibrating partially parallel acquisition (2D‐GRAPPA) with adiabatic double inversion recovery (IR)‐based lipid suppression to allow robust high‐resolution MRSI. We performed Bloch simulations to evaluate the magnetisation pathways of lipids and metabolites, and compared the results with phantom measurements. Acceleration factors in the range 2–25 were tested in a phantom. Five volunteers were scanned to verify the value of our MRSI method in vivo. GRAPPA artefacts that cause fold‐in of transcranial lipids were suppressed via double IR, with a non‐selective symmetric frequency sweep. The use of long, low‐power inversion pulses (100 ms) reduced specific absorption rate requirements. The symmetric frequency sweep over both pulses provided good lipid suppression (>90%), in addition to a reduced loss in metabolite signal‐to‐noise ratio (SNR), compared with conventional IR suppression (52–70%). The metabolic mapping over the whole brain slice was not limited to a rectangular region of interest. 2D‐GRAPPA provided acceleration up to a factor of nine for in vivo FID‐MRSI without a substantial increase in g‐factors (<1.1). A 64 × 64 matrix can be acquired with a common repetition time of ~1.3 s in only 8 min without lipid artefacts caused by acceleration. Overall, we present a fast and robust MRSI method, using combined double IR fat suppression and 2D‐GRAPPA acceleration, which may be used in (pre)clinical studies of the brain at 7 T.
NMR in Biomedicine | 2013
Bernhard Strasser; Marek Chmelik; Simon Robinson; Gilbert Hangel; Staci A. Gruber; Siegfried Trattnig; Wolfgang Bogner
The goal of this study was to evaluate a new method of combining multi‐channel 1H MRSI data by direct use of a matching imaging scan as a reference, rather than computing sensitivity maps. Seven healthy volunteers were measured on a 7‐T MR scanner using a head coil with a 32‐channel array coil for receive‐only and a volume coil for receive/transmit. The accuracy of prediction of the phase of the 1H MRSI data with a fast imaging pre‐scan was investigated with the volume coil. The array coil 1H MRSI data were combined using matching imaging data as coil combination weights. The signal‐to‐noise ratio (SNR), spectral quality, metabolic map quality and Cramér–Rao lower bounds were then compared with the data obtained by two standard methods, i.e. using sensitivity maps and the first free induction decay (FID) data point. Additional noise decorrelation was performed to further optimize the SNR gain. The new combination method improved significantly the SNR (+29%), overall spectral quality and visual appearance of metabolic maps, and lowered the Cramér–Rao lower bounds (−34%), compared with the combination method based on the first FID data point. The results were similar to those obtained by the combination method using sensitivity maps, but the new method increased the SNR slightly (+1.7%), decreased the algorithm complexity, required no reference coil and pre‐phased all spectra correctly prior to spectral processing. Noise decorrelation further increased the SNR by 13%. The proposed method is a fast, robust and simple way to improve the coil combination in 1H MRSI of the human brain at 7 T, and could be extended to other 1H MRSI techniques.
Radiology | 2016
Olgica Zaric; Katja Pinker; Stefan Zbyn; Bernhard Strasser; Simon P. Robinson; Lenka Minarikova; Stephan Gruber; Alex Farr; Christian F. Singer; Thomas H. Helbich; Siegfried Trattnig; Wolfgang Bogner
Purpose To investigate the clinical feasibility of a quantitative sodium 23 ((23)Na) magnetic resonance (MR) imaging protocol developed for breast tumor assessment and to compare it with 7-T diffusion-weighted imaging (DWI). Materials and Methods Written informed consent in this institutional review board-approved study was obtained from eight healthy volunteers and 17 patients with 20 breast tumors (five benign, 15 malignant). To achieve the best image quality and reproducibility, the (23)Na sequence was optimized and tested on phantoms and healthy volunteers. For in vivo quantification of absolute tissue sodium concentration (TSC), an external phantom was used. Static magnetic field, or B0, and combined transmit and receive radiofrequency field, or B1, maps were acquired, and image quality, measurement reproducibility, and accuracy testing were performed. Bilateral (23)Na and DWI sequences were performed before contrast material-enhanced MR imaging in patients with breast tumors. TSC and apparent diffusion coefficient (ADC) were calculated and correlated for healthy glandular tissue and benign and malignant lesions. Results The (23)Na MR imaging protocol is feasible, with 1.5-mm in-plane resolution and 16-minute imaging time. Good image quality was achieved, with high reproducibility (mean TSC values ± standard deviation for the test, 36 mmol per kilogram of wet weight ± 2 [range, 34-37 mmol/kg]; for the retest, 37 mmol/kg ± 1 [range, 35-39 mmol/kg]; P = .610) and accuracy (r = 0.998, P < .001). TSC values in normal glandular and adipose breast tissue were 35 mmol/kg ± 3 and 18 mmol/kg ± 3, respectively. In malignant lesions (mean size, 31 mm ± 24; range, 6-92 mm), the TSC of 69 mmol/kg ± 10 was, on average, 49% higher than that in benign lesions (mean size, 14 mm ± 12; range, 6-35 mm), with a TSC of 47 mmol/kg ± 8 (P = .002). There were similar ADC differences between benign ([1.78 ± 0.23] × 10(-3) mm(2)/sec) and malignant ([1.03 ± 0.23] × 10(-3) mm(2)/sec) tumors (P = .002). ADC and TSC were inversely correlated (r = -0.881, P < .001). Conclusion Quantitative (23)Na MR imaging is clinically feasible, may provide good differentiation between malignant and benign breast lesions, and demonstrates an inverse correlation with ADC. (©) RSNA, 2016 Online supplemental material is available for this article.
NeuroImage | 2016
Gilbert Hangel; Bernhard Strasser; Michal Považan; Eva Heckova; Lukas Hingerl; Roland N. Boubela; Stephan Gruber; Siegfried Trattnig; Wolfgang Bogner
ABSTRACT MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B0/B1+‐homogeneity, specific absorption rate restrictions, long measurement times, and low spatial resolution. To overcome these limitations, we propose an ultra‐high resolution (UHR) MRSI sequence that provides a 128×128 matrix with a nominal voxel volume of 1.7×1.7×8 mm3 in a comparatively short measurement time. A clinically feasible scan time of 10–20 min is reached via a short TR of 200 ms due to an optimised free induction decay‐based acquisition with shortened water suppression as well as parallel imaging (PI) using Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA). This approach is not limited to a rectangular region of interest in the centre of the brain, but also covers cortical brain regions. Transversal pulse‐cascaded Hadamard encoding was able to further extend the coverage to 3D‐UHR‐MRSI of four slices (100×100×4 matrix size), with a measurement time of 17 min. Lipid contamination was removed during post‐processing using L2‐regularisation. Simulations, phantom and volunteer measurements were performed. The obtained single‐slice and 3D‐metabolite maps show the brain in unprecedented detail (e.g., hemispheres, ventricles, gyri, and the contrast between grey and white matter). This facilitates the use of UHR‐MRSI for clinical applications, such as measurements of the small structures and metabolic pathologic deviations found in small Multiple Sclerosis lesions. HIGHLIGHTSUltra‐high resolution MRSI (128×128 in‐plane matrix) at 7 T.Parallel imaging and short TR of 200 ms make UHR‐MRSI clinically feasible (10–20 min).Pulse‐cascaded Hadamard encoding provides 3D‐MRSI coverage.
Magnetic Resonance in Medicine | 2017
Bernhard Strasser; Michal Považan; Gilbert Hangel; Lukas Hingerl; Marek Chmelik; Staci A. Gruber; Siegfried Trattnig; Wolfgang Bogner
To compare a new parallel imaging (PI) method for multislice proton magnetic resonance spectroscopic imaging (1H‐MRSI), termed (2 + 1)D‐CAIPIRINHA, with two standard PI methods: 2D‐GRAPPA and 2D‐CAIPIRINHA at 7 Tesla (T).
NeuroImage | 2016
Siegfried Trattnig; Elisabeth Springer; Wolfgang Bogner; Gilbert Hangel; Bernhard Strasser; Barbara Dymerska; Pedro Lima Cardoso; Simon Robinson
The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7 T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7 T is to gain higher spatial resolution in the brain compared to 3 T. Of specific clinical interest for neuro applications is the cerebral cortex at 7 T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7 T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7 T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7 T.
Magnetic Resonance in Medicine | 2015
Lucia I. Navarro de Lara; Christian Windischberger; Andre Kuehne; Michael Woletz; Jürgen Sieg; Sven Bestmann; Nikolaus Weiskopf; Bernhard Strasser; Ewald Moser; Elmar Laistler
To overcome current limitations in combined transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) studies by employing a dedicated coil array design for 3 Tesla.
Magnetic Resonance in Medicine | 2018
Michal Považan; Bernhard Strasser; Gilbert Hangel; Eva Heckova; Stephan Gruber; Siegfried Trattnig; Wolfgang Bogner
Short‐echo‐time proton MR spectra at 7T feature nine to 10 distinct macromolecule (MM) resonances that overlap with the signals of metabolites. Typically, a metabolite‐nulled in vivo MM spectrum is included in the quantification`s prior knowledge to provide unbiased metabolite quantification. However, this MM model may fail if MMs are pathologically altered. In addition, information about the individual MM peaks is lost. In this study, we aimed to create an improved MM model by parameterization of the in vivo MM spectrum into individual components, and to use this new model to quantify free induction decay MR spectroscopic imaging (FID‐MRSI) data.