| 1. |
- Tapper, Sofie, et al.
(author)
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Retrospective artifact elimination in MEGA-PRESS using a correlation approach
- 2019
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In: Magnetic Resonance in Medicine. - : John Wiley & Sons. - 0740-3194 .- 1522-2594. ; 81:4, s. 2223-2237
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Journal article (peer-reviewed)abstract
- PurposeTo develop a method for retrospective artifact elimination of MRS data. This retrospective method was based on an approach that combines jackknife analyses with the correlation of spectral windows, and therefore termed “JKC.”MethodsTwelve healthy volunteers performed 3 separate measurement protocols using a 3T MR system. One protocol consisted of 2 cerebellar MEGA‐PRESS measurements: 1 reference and 1 measurement including head movements. One‐third of the artifact‐influenced datasets were treated as training data for the implementation the JKC method, and the rest were used for validation.ResultsThe implemented JKC method correctly characterized most of the validation data. Additionally, after elimination of the detected artifacts, the resulting concentrations were much closer to those computed for the reference datasets. Moreover, when the JKC method was applied to the reference data, the estimated concentrations were not affected, compared with standard averaging.ConclusionThe implemented JKC method can be applied without any extra cost to MRS data, regardless of whether the dataset has been contaminated by artifacts. Furthermore, the results indicate that the JKC method could be used as a quality control of a dataset, or as an indication of whether a shift in voxel placement has occurred during the measurement.
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| 2. |
- Helms, Gunther, et al.
(author)
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Cross-vendor transfer and RF coil comparison of a high-resolution MP2RAGE protocol for brain imaging at 7T
- 2020
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In: Acta Scientiarum Lundensia. - 1651-5013. ; 2020:001, s. 1-12
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Journal article (peer-reviewed)abstract
- Abstract. An established MP2RAGE protocol for semi-quantitative structural brain MRI was transferred from one 7T MR scanner to that of another vendor featuring comparable hardware, but opposite polarity. On this system, the scan time could be reduced from 11 to 8 minutes by elliptical k-space sampling. Three configurations of radio-frequency (RF) transmission were compared (single channel with quadrature slitting, two and eight channels of fixed phase delays). Data processing for offline calculation MP2RAGE images is described in detail. The DICOM scaling of scanner B entails a loss of precision and accuracy and stronger artifacts in regions of low RF field, which can be improved by dielectric pads. For comparison and multi-site studies, though, use of an identical scan protocol and identical RF hardware is recommended.
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| 3. |
- Tabelow, Karsten, et al.
(author)
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hMRI – A toolbox for quantitative MRI in neuroscience and clinical research
- 2019
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In: NeuroImage. - : Elsevier BV. - 1095-9572 .- 1053-8119. ; 194, s. 191-210
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Journal article (peer-reviewed)abstract
- Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates and , proton density and magnetisation transfer saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.
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| 4. |
- Ahlstedt, Jonatan, et al.
(author)
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Growth pattern of experimental glioblastoma
- 2020
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In: Histology and Histopathology. - 1699-5848. ; 35:8, s. 871-886
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Journal article (peer-reviewed)abstract
- Glioblastoma multiforme (GBM) is an aggressive primary brain malignancy with a very poor prognosis. Researchers employ animal models to develop potential therapies. It is important that these models have clinical relevance. This means that old models, propagated for decades in cultures, should be questioned. Parameters to be evaluated include whether animals are immune competent or not, the infiltrative growth pattern of the tumor, tumor volume resulting in symptoms and growth rate.We here describe the growth pattern of an experimental glioblastoma model in detail with GFP positive glioblastoma cells in fully immune competent animalsand study tumor growth rate and tumor mass as a function of time from inoculation.We were able to correlate findings made with classical immunohistochemistry and MR findings. The tumor growth rate was fitted by a Gompertz function. The model predicted the time until onset of symptoms for 5000 inoculated cells to 18.7±0.4 days, and the tumor mass at days 10 and 14, which are commonly used as the start of treatment in therapeutic studies, were 5.97±0.62 mg and 29.1±3.0 mg, respectively.We want to raise the question regarding the clinical relevance of the outline of glioblastoma experiments, where treatment is ofteninitiated at a very early stage. The approach presented here could potentially be modified to gain information also from other tumor models.
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| 5. |
- Helms, Gunther
(author)
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Challenges in quantitative MRI
- 2018
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In: Challenges in quantitative MRI : Abstracts from the 2nd European Congress of Medical Physics - Abstracts from the 2nd European Congress of Medical Physics. - : Elsevier BV. - 1120-1797. ; 52:Suppl. 1, s. 7-7
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Conference paper (other academic/artistic)abstract
- PurposeQuantitative MRI (qMRI) yields reproducible “maps” of physiological and/or biophysical tissue parameters. These spatially resolved metrics are mainly used in clinical imaging research for cross-sectional and longitudinal studies. The field of qMRI has considerable expanded during the past two decades. Rather than focusing on particular methods, this talk highlights general concepts of accuracy and precision, the relationship to QA, and ongoing endeavors for validation. MethodsParameters are derived from models of the MR experiment. They thus share the limited resolution of MRI. At a second level, physiological and microscopic properties of tissue can be derived. Adequate QA has to be performed to control systematic error (bias), especially when comparing results obtained on scanners of different makes and model. Increasingly, validation experiments are performed to relate macroscopic maps to underlying microscopic tissue properties. ResultsFlip angle (B1+) mapping is a prime example for bias correction, especially at high and ultra-high magnetic field strength. However, magnetic field strength and model-specific implementations still can be large source of bias. Ideally, individual correction should also comprise control or correction for gross and physiological patient motion. Regular QA is advised to maintain the comparability of metrics over time. Recent progress in validation has mainly focused on tissue iron and myelin for improved interpretation of qMRI metrics as given by ever more-complex models of microscopic tissue properties.Conclusions In-depth knowledge of the MR system’s performance increases accuracy and is a prerequisite for validation and interpretation. Quantitative MRI across different platforms and field strengths remain challenging.
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| 6. |
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| 7. |
- Weiskopf, Nikolaus, et al.
(author)
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Quantitative magnetic resonance imaging of brain anatomy and in vivo histology
- 2021
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In: Nature Reviews Physics. - : Springer Science and Business Media LLC. - 2522-5820.
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Research review (peer-reviewed)abstract
- Quantitative magnetic resonance imaging (qMRI) goes beyond conventional MRI, which aims primarily at local image contrast. It provides specific physical parameters related to the nuclear spin of protons in water, such as relaxation times. These parameters carry information about the local microstructural environment of the protons (such as myelin in the brain). Non- invasive in vivo histology using MRI (hMRI) aims to use this information to directly characterize biological tissue microstructure, partially replacing or complementing classical invasive histology. The understanding of MRI tissue contrast provided by hMRI is, in turn, crucial for further improvements of qMRI, and they should be considered closely interlinked. We discuss concepts, models and validation approaches, pointing out challenges and the latest advances in this field. Further, we point out links to physics, including computational and analytical approaches and developments in materials science and photonics, that aid in reference data acquisition and model validation.
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| 8. |
- Novén, Mikael, et al.
(author)
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Cortical and white matter correlates of language-learning aptitudes
- 2021
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In: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 42:15, s. 5037-5050
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Journal article (peer-reviewed)abstract
- People learn new languages with varying degrees of success but what are the neuroanatomical correlates of the difference in language-learning aptitude? In this study, we set out to investigate how differences in cortical morphology and white matter microstructure correlate with aptitudes for vocabulary learning, phonetic memory, and grammatical inferencing as measured by the first-language neutral LLAMA test battery. We used ultra-high field (7T) magnetic resonance imaging to estimate the cortical thickness and surface area from sub-millimeter resolved image volumes. Further, diffusion kurtosis imaging was used to map diffusion properties related to the tissue microstructure from known language-related white matter tracts. We found a correlation between cortical surface area in the left posterior-inferior precuneus and vocabulary learning aptitude, possibly indicating a greater predisposition for storing word-figure associations. Moreover, we report negative correlations between scores for phonetic memory and axial kurtosis in left arcuate fasciculus as well as mean kurtosis, axial kurtosis, and radial kurtosis of the left superior longitudinal fasciculus III, which are tracts connecting cortical areas important for phonological working memory.
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| 9. |
- Helms, Gunther, et al.
(author)
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High-resolution maps of magnetization transfer with inherent correction for RF inhomogeneity and T1 relaxation obtained from 3D FLASH MRI
- 2008
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In: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 60:6, s. 1396-1407
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Journal article (peer-reviewed)abstract
- An empirical equation for the magnetization transfer (MT) FLASH signal is derived by analogy to dual-excitation FLASH, introducing a novel semiquantitative parameter for MT, the percentage saturation imposed by one MT pulse during TR. This parameter is obtained by a linear transformation of the inverse signal, using two reference experiments of proton density and T1 weighting. The influence of sequence parameters on the MT saturation was studied. An 8.5-min protocol for brain imaging at 3T was based on nonselective sagittal 3D-FLASH at 1.25mm isotropic resolution using partial acquisition techniques (TR/TE/flipangle = 25ms/4.9ms/5° or 11ms/4.9ms/15° for the T1 reference). A 12.8 ms Gaussian MT pulse was applied 2.2 kHz off-resonance with 540° flip angle. The MT saturation maps showed an excellent contrast in the brain due to clearly separated distributions for white and gray matter and cerebrospinal fluid. Within the limits of the approximation (excitation <15°, TR/T1<<1) the MT term depends mainly on TR, the energy and offset of the MT pulse, but hardly on excitation and T1 relaxation. It is inherently compensated for inhomogeneities of receive and transmit RF fields. The MT saturation appeared to be a sensitive parameter to depict MS lesions and alterations of normal-appearing white matter.
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