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  • 1
    In: NMR in Biomedicine, Wiley, Vol. 34, No. 12 ( 2021-12)
    Abstract: Recently, a 3D‐concentric ring trajectory (CRT)‐based free induction decay (FID)‐MRSI sequence was introduced for fast high‐resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. Methods We acquired whole‐brain 3D‐CRT‐FID‐MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter‐subject coefficients of variation (CVs) were compared for all ROIs. Results Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo‐inositol, and N ‐acetylaspartate in 44 regions were estimated within quality thresholds. Inter‐subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo‐inositol, and 9%/6%/19% for N ‐acetylaspartate. Discussion We defined the performance of 3D‐CRT‐based FID‐MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter‐subject CVs expected. However, the basal brain regions and lesser‐signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B 0 / B 1 ‐field inhomogeneities will be necessary to achieve reliable whole‐brain coverage.
    Type of Medium: Online Resource
    ISSN: 0952-3480 , 1099-1492
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
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    detail.hit.zdb_id: 1000976-0
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  • 2
    In: Magnetic Resonance in Medicine, Wiley, Vol. 79, No. 3 ( 2018-03), p. 1231-1240
    Abstract: 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. Methods The measured in vivo MM spectrum was parameterized using advanced method for accurate, robust, and efficient spectral fitting (AMARES) and Hankel‐Lanczos singular value decomposition algorithms from which six different MM models were derived. Soft constraints were applied to avoid over‐parameterization. All MM models were combined with simulated metabolite spectra to form complete basis sets. FID‐MRSI data from 14 healthy volunteers were quantified via LCModel, and the results were compared between all basis sets. Results The MM model using nine individual AMARES‐parameterized MM components with additional soft constraints achieved the most reliable results. Nine MMs and seven metabolites were mapped simultaneously over the whole slice. Conclusion The proposed MM model may facilitate studies that involve patients with pathologically altered MMs. Magn Reson Med 79:1231–1240, 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.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1493786-4
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  • 3
    In: Magnetic Resonance in Medicine, Wiley, Vol. 82, No. 2 ( 2019-08), p. 551-565
    Abstract: Inhomogeneities in the static magnetic field ( B 0 ) 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 B 0 ‐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 B 0 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 cm 3 versus 0.25 cm 3 resolution. This effect was much more pronounced at higher and less homogenous B 0 (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 B 0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B 0 shimming hardware, this will enable robust whole‐brain MRSI at ultra‐high field.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1493786-4
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  • 4
    In: Magnetic Resonance in Medicine, Wiley, Vol. 82, No. 5 ( 2019-11), p. 1587-1603
    Abstract: Proton MR spectroscopic imaging (MRSI) benefits from B 0 ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already‐fast sampling via concentric rings, we implemented additional, non‐Cartesian, hybrid through‐time/through‐k‐space (tt/tk)‐generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities. Methods Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single‐slice free induction decay (FID)‐MRSI. Through‐time/through‐k‐space‐GRAPPA with constant/variable‐density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole‐brain FID‐MRSI. Results Using iMUSICAL for coil combination yielded the highest signal‐to‐noise ratio (SNR) (+9%) and lowest Cramer‐Rao lower bounds (CRLBs) (‐6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g‐factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two‐fold, variable‐density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data. Conclusion Through‐time/through‐k‐space‐GRAPPA can accelerate already time‐efficient non‐Cartesian spatial‐spectral 2D/3D‐MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 1493786-4
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  • 5
    In: NeuroImage, Elsevier BV, Vol. 168 ( 2018-03), p. 477-489
    Type of Medium: Online Resource
    ISSN: 1053-8119
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 1471418-8
    SSG: 5,2
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  • 6
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2022-2-28)
    Abstract: To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 7
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-3-3)
    Abstract: Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 8
    In: Investigative Radiology, Ovid Technologies (Wolters Kluwer Health), Vol. 52, No. 10 ( 2017-10), p. 631-639
    Type of Medium: Online Resource
    ISSN: 1536-0210 , 0020-9996
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2017
    detail.hit.zdb_id: 2041543-6
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  • 9
    In: NeuroImage, Elsevier BV, Vol. 121 ( 2015-11), p. 126-135
    Type of Medium: Online Resource
    ISSN: 1053-8119
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 1471418-8
    SSG: 5,2
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  • 10
    In: Neuro-Oncology Advances, Oxford University Press (OUP), Vol. 3, No. Supplement_1 ( 2021-03-25), p. i1-i1
    Abstract: Neurosurgical resection in gliomas depends on the precise preoperative definition of the tumor and its margins to realize a safe maximum resection that translates into a better patient outcome. New metabolic imaging techniques could improve this delineation as well as designate targets for biopsies. We validated the performance of our fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in high-grade gliomas (HGGs) as first step to this regard. METHODS We measured 23 patients with HGGs at 7T with MRSI covering the whole cerebrum with 3.4mm isotropic resolution in 15 min. Quantification used a basis-set of 17 neurochemical components. They were evaluated for their reliability/quality and compared to neuroradiologically segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast-enhanced+edema, peritumoral) and histopathology (e.g., grade, IDH-status). RESULTS We found 18/23 measurements to be usable and ten neurochemicals quantified with acceptable quality. The most common denominators were increases of glutamine, glycine, and total choline as well as decreases of N-acetyl-aspartate and total creatine over most tumor regions. Other metabolites like taurine and serine showed mixed behavior. We further found that heterogeneity in the metabolic images often continued into the peritumoral region. While 2-hydroxy-glutarate could not be satisfyingly quantified, we found a tendency for a decrease of glutamate in IDH1-mutant HGGs. DISCUSSION Our findings corresponded well to clinical tumor segmentation but were more heterogeneous and often extended into the peritumoral region. Our results corresponded to previous knowledge, but with previously not feasible resolution. Apart from glycine/glutamine and their role in glioma progression, more research on the connection of glutamate and others to specific mutations is necessary. The addition of low-grade gliomas and statistical ROI analysis in a larger cohort will be the next important steps to define the benefits of our 7T MRSI approach for the definition of spatial metabolic tumor profiles.
    Type of Medium: Online Resource
    ISSN: 2632-2498
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 3009682-0
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