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  • 1
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    A comparison of optimization algorithms for localized in vivo B 0 shimming
    Wiley ; 2018
    In:  Magnetic Resonance in Medicine Vol. 79, No. 2 ( 2018-02), p. 1145-1156
    Details
    In: Magnetic Resonance in Medicine, Wiley, Vol. 79, No. 2 ( 2018-02), p. 1145-1156
    Abstract: To compare several different optimization algorithms currently used for localized in vivo B 0 shimming, and to introduce a novel, fast, and robust constrained regularized algorithm ( ConsTru ) for this purpose. Methods Ten different optimization algorithms (including samples from both generic and dedicated least‐squares solvers, and a novel constrained regularized inversion method) were implemented and compared for shimming in five different shimming volumes on 66 in vivo data sets from both 7 T and 9.4 T. The best algorithm was chosen to perform single‐voxel spectroscopy at 9.4 T in the frontal cortex of the brain on 10 volunteers. Results The results of the performance tests proved that the shimming algorithm is prone to unstable solutions if it depends on the value of a starting point, and is not regularized to handle ill‐conditioned problems. The ConsTru algorithm proved to be the most robust, fast, and efficient algorithm among all of the chosen algorithms. It enabled acquisition of spectra of reproducible high quality in the frontal cortex at 9.4 T. Conclusions For localized in vivo B 0 shimming, the use of a dedicated linear least‐squares solver instead of a generic nonlinear one is highly recommended. Among all of the linear solvers, the constrained regularized method ( ConsTru ) was found to be both fast and most robust. Magn Reson Med 79:1145–1156, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    URL: Article
    DOI: 10.1002/mrm.v79.2
    DOI: 10.1002/mrm.26758
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1493786-4
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  • 2
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    Modeling real shim fields for very high degree (and order) B 0 shimming of the human brain at 9.4 T
    Wiley ; 2018
    In:  Magnetic Resonance in Medicine Vol. 79, No. 1 ( 2018-01), p. 529-540
    Details
    In: Magnetic Resonance in Medicine, Wiley, Vol. 79, No. 1 ( 2018-01), p. 529-540
    Abstract: To describe the process of calibrating a B 0 shim system using high‐degree (or high order) spherical harmonic models of the measured shim fields, to provide a method that considers amplitude dependency of these models, and to show the advantage of very high‐degree B 0 shimming for whole‐brain and single‐slice applications at 9.4 Tesla (T). Methods An insert shim with up to fourth and partial fifth/sixth degree (order) spherical harmonics was used with a Siemens 9.4T scanner. Each shim field was measured and modeled as input for the shimming algorithm. Optimal shim currents can therefore be calculated in a single iteration. A range of shim currents was used in the modeling to account for possible amplitude nonlinearities. The modeled shim fields were used to compare different degrees of whole‐brain B 0 shimming on healthy subjects. Results The ideal shim fields did not correctly shim the subject brains. However, using the modeled shim fields improved the B 0 homogeneity from 55.1 (second degree) to 44.68 Hz (partial fifth/sixth degree) on the whole brains of 9 healthy volunteers, with a total applied current of 0.77 and 6.8 A, respectively. Conclusions The necessity of calibrating the shim system was shown. Better B 0 homogeneity drastically reduces signal dropout and distortions for echo‐planar imaging, and significantly improves the linewidths of MR spectroscopy imaging. Magn Reson Med 79:529–540, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    URL: Article
    DOI: 10.1002/mrm.v79.1
    DOI: 10.1002/mrm.26658
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1493786-4
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  • 3
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    High and ultra-high resolution metabolite mapping of the human brain using 1 H FID MRSI at 9.4T
    Elsevier BV ; 2018
    In:  NeuroImage Vol. 168 ( 2018-03), p. 211-221
    Details
    In: NeuroImage, Elsevier BV, Vol. 168 ( 2018-03), p. 211-221
    Type of Medium: Online Resource
    ISSN: 1053-8119
    URL: Article
    DOI: 10.1016/j.neuroimage.2016.12.065
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 1471418-8
    SSG: 5,2
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  • 4
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    MultiNet PyGRAPPA: Multiple neural networks for reconstructing variable density GRAPPA (a 1H FID MRSI study)
    Elsevier BV ; 2018
    In:  NeuroImage Vol. 183 ( 2018-12), p. 336-345
    Details
    In: NeuroImage, Elsevier BV, Vol. 183 ( 2018-12), p. 336-345
    Type of Medium: Online Resource
    ISSN: 1053-8119
    URL: Article
    DOI: 10.1016/j.neuroimage.2018.08.032
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 1471418-8
    SSG: 5,2
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  • 5
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    Non‐water‐suppressed 1 H FID‐MRSI at 3T and 9.4T
    Wiley ; 2018
    In:  Magnetic Resonance in Medicine Vol. 80, No. 2 ( 2018-08), p. 442-451
    Details
    In: Magnetic Resonance in Medicine, Wiley, Vol. 80, No. 2 ( 2018-08), p. 442-451
    Abstract: This study investigates metabolite concentrations using metabolite‐cycled 1 H free induction decay (FID) magnetic resonance spectroscopic imaging (MRSI) at ultra‐high fields. Methods A non‐lipid‐suppressed and slice‐selective ultra‐short echo time (TE) 1 H FID MRSI sequence was combined with a low‐specific absorption rate (SAR) asymmetric inversion adiabatic pulse to enable non‐water‐suppressed metabolite mapping using metabolite‐cycling at 9.4T. The results were compared to a water‐suppressed FID MRSI sequence, and the same study was performed at 3T for comparison. The scan times for performing single‐slice metabolite mapping with a nominal voxel size of 0.4 mL were 14 and 17.5 min on 3T and 9.4T, respectively. Results The low‐SAR asymmetric inversion adiabatic pulse enabled reliable non‐water‐suppressed metabolite mapping using metabolite cycling at both 3T and 9.4T. The spectra and maps showed good agreement with the water‐suppressed FID MRSI ones at both field strengths. A quantitative analysis of metabolite ratios with respect to N‐acetyl aspartate (NAA) was performed. The difference in Cre/NAA was statistically significant, ∼0.1 higher for the non‐water‐suppressed case than for water suppression (from 0.73 to 0.64 at 3T and from 0.69 to 0.59 at 9.4T). The difference is likely because of chemical exchange effects of the water suppression pulses. Small differences in mI/NAA were also statistically significant, however, are they are less reliable because the metabolite peaks are close to the water peak that may be affected by the water suppression pulses or metabolite‐cycling inversion pulse. Conclusion We showed the first implementation of non‐water‐suppressed metabolite‐cycled 1 H FID MRSI at ultra‐high fields. An increase in Cre/NAA was seen for the metabolite‐cycled case. The same methodology was further applied at 3T and similar results were observed. Magn Reson Med 80:442–451, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    URL: Article
    DOI: 10.1002/mrm.v80.2
    DOI: 10.1002/mrm.27049
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1493786-4
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  • 6
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    A System for Automated, Noninvasive, Morphology-Based Evaluation of Induced Pluripotent Stem Cell Cultures
    Elsevier BV ; 2014
    In:  SLAS Technology Vol. 19, No. 5 ( 2014-10), p. 454-460
    Details
    In: SLAS Technology, Elsevier BV, Vol. 19, No. 5 ( 2014-10), p. 454-460
    Type of Medium: Online Resource
    ISSN: 2472-6303
    URL: Article
    DOI: 10.1177/2211068214537258
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2014
    detail.hit.zdb_id: 2593238-X
    detail.hit.zdb_id: 2900310-6
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  • 7
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    Lipid‐suppressed and tissue‐fraction corrected metabolic distributions in human central brain structures using 2D 1 H magnetic resonance spectroscopic imaging at 7 T
    Wiley ; 2020
    In:  Brain and Behavior Vol. 10, No. 12 ( 2020-12)
    Details
    In: Brain and Behavior, Wiley, Vol. 10, No. 12 ( 2020-12)
    Abstract: Magnetic resonance spectroscopic imaging (MRSI) has the potential to add a layer of understanding of the neurobiological mechanisms underlying brain diseases, disease progression, and treatment efficacy. Limitations related to metabolite fitting of low signal‐to‐noise ratios data, signal variations due to partial‐volume effects, acquisition and extracranial lipid artifacts, along with clinically relevant aspects such as scan time constraints, are among the challenges associated with in vivo MRSI. Methods The aim of this work was to address some of these factors and to develop an acquisition, reconstruction, and postprocessing pipeline to derive lipid‐suppressed metabolite values of central brain structures based on free‐induction decay measurements made using a 7 T MR scanner. Anatomical images were used to perform high‐resolution (1 mm 3 ) partial‐volume correction to account for gray matter, white matter (WM), and cerebral‐spinal fluid signal contributions. Implementation of automatic quality control thresholds and normalization of metabolic maps from 23 subjects to the Montreal Neurological Institute (MNI) standard atlas facilitated the creation of high‐resolution average metabolite maps of several clinically relevant metabolites in central brain regions, while accounting for macromolecular distributions. Partial‐volume correction improved the delineation of deep brain nuclei. We report average metabolite values including glutamate + glutamine (Glx), glycerophosphocholine, choline and phosphocholine (tCho), (phospo)creatine, myo‐inositol and glycine (mI‐Gly), glutathione, N‐acetyl‐aspartyl glutamate(and glutamine), and N‐acetyl‐aspartate in the basal ganglia, central WM (thalamic radiation, corpus callosum) as well as insular cortex and intracalcarine sulcus. Conclusion MNI‐registered average metabolite maps facilitate group‐based analysis, thus offering the possibility to mitigate uncertainty in variable MRSI data.
    Type of Medium: Online Resource
    ISSN: 2162-3279 , 2162-3279
    URL: Issue
    URL: Article
    DOI: 10.1002/brb3.v10.12
    DOI: 10.1002/brb3.1852
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2623587-0
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  • 8
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    Over‐discretized SENSE reconstruction and B 0 correction for accelerated non‐lipid‐suppressed 1 H FID MRSI of the human brain at 9.4 T
    Wiley ; 2018
    In:  NMR in Biomedicine Vol. 31, No. 12 ( 2018-12)
    Details
    In: NMR in Biomedicine, Wiley, Vol. 31, No. 12 ( 2018-12)
    Abstract: The aim of this work was to use post‐processing methods to improve the data quality of metabolite maps acquired on the human brain at 9.4 T with accelerated acquisition schemes. This was accomplished by combining an improved sensitivity encoding (SENSE) reconstruction with a B 0 correction of spatially over‐discretized magnetic resonance spectroscopic imaging (MRSI) data. Since MRSI scans suffer from long scan duration, investigating different acceleration techniques has recently been the focus of several studies. Due to strong B 0 inhomogeneity and strict specific absorption rate (SAR) limitations at ultra‐high fields, the use of a low‐SAR sequence combined with an acceleration technique that is compatible with dynamic B 0 shim updating is preferable. Hence, in this study, a non‐lipid‐suppressed ultra‐short T E and T R 1 H free induction decay MRSI sequence is combined with an in‐plane SENSE acceleration technique to obtain high‐resolution metabolite maps in a clinically feasible scan time. One of the major issues in applying parallel imaging techniques to non‐lipid‐suppressed MRSI is the presence of strong lipid aliasing artifacts, which if not thoroughly resolved will hinder the accurate quantification of the metabolites of interest. To achieve a more robust reconstruction, an over‐discretized SENSE reconstruction (with direct control over the shape of the spatial response function) was combined with an over‐discretized B 0 correction. This method is compared with conventional SENSE reconstruction for seven acceleration schemes on four healthy volunteers. The over‐discretized method consistently outperformed conventional SENSE, resulting in an average of 23 ± 1.2% higher signal‐to‐noise ratio and 8 ± 2.9% less error in the fitting of the N‐acetylaspartate signal over a whole brain slice. The highest achievable acceleration factor with the proposed technique was determined to be 4. Finally, using the over‐discretized method, high‐resolution (97 μL nominal voxel size) metabolite maps can be acquired in 3.75 min at 9.4 T. This enables the acquisition of high‐resolution metabolite maps with more spatial coverage at ultra‐high fields.
    Type of Medium: Online Resource
    ISSN: 0952-3480 , 1099-1492
    URL: Issue
    URL: Article
    DOI: 10.1002/nbm.v31.12
    DOI: 10.1002/nbm.4014
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2002003-X
    detail.hit.zdb_id: 1000976-0
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  • 9
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    Constrained optimization for position calibration of an NMR field camera
    Wiley ; 2018
    In:  Magnetic Resonance in Medicine Vol. 80, No. 1 ( 2018-07), p. 380-390
    Details
    In: Magnetic Resonance in Medicine, Wiley, Vol. 80, No. 1 ( 2018-07), p. 380-390
    Abstract: Knowledge of the positions of field probes in an NMR field camera is necessary for monitoring the B 0 field. The typical method of estimating these positions is by switching the gradients with known strengths and calculating the positions using the phases of the FIDs. We investigated improving the accuracy of estimating the probe positions and analyzed the effect of inaccurate estimations on field monitoring. Methods The field probe positions were estimated by 1) assuming ideal gradient fields, 2) using measured gradient fields (including nonlinearities), and 3) using measured gradient fields with relative position constraints. The fields measured with the NMR field camera were compared to fields acquired using a dual‐echo gradient recalled echo B 0 mapping sequence. Comparisons were done for shim fields from second‐ to fourth‐order shim terms. Results The position estimation was the most accurate when relative position constraints were used in conjunction with measured (nonlinear) gradient fields. The effect of more accurate position estimates was seen when compared to fields measured using a B 0 mapping sequence (up to 10%–15% more accurate for some shim fields). The models acquired from the field camera are sensitive to noise due to the low number of spatial sample points. Conclusion Position estimation of field probes in an NMR camera can be improved using relative position constraints and nonlinear gradient fields. Magn Reson Med 80:380–390, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    URL: Article
    DOI: 10.1002/mrm.v80.1
    DOI: 10.1002/mrm.27010
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1493786-4
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  • 10
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    Compressed sensing for high‐resolution nonlipid suppressed 1 H FID MRSI of the human brain at 9.4T
    Wiley ; 2018
    In:  Magnetic Resonance in Medicine Vol. 80, No. 6 ( 2018-12), p. 2311-2325
    Details
    In: Magnetic Resonance in Medicine, Wiley, Vol. 80, No. 6 ( 2018-12), p. 2311-2325
    Abstract: The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra‐short TR and TE 1 H FID MRSI sequence at 9.4T. Methods X‐t sparse compressed sensing reconstruction was optimized for nonlipid suppressed 1 H FID MRSI data. Coil‐by‐coil x‐t sparse reconstruction was compared with SENSE x‐t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared. Results Coil‐by‐coil x‐t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x‐t sparse). For acceleration factors of up to 5, both the low‐rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved. Conclusion By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min.
    Type of Medium: Online Resource
    ISSN: 0740-3194 , 1522-2594
    URL: Issue
    URL: Article
    DOI: 10.1002/mrm.v80.6
    DOI: 10.1002/mrm.27225
    Language: English
    Publisher: Wiley
    Publication Date: 2018
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