| 1. |
- Dechent, Peter, et al.
(author)
-
Basal cerebral blood volume during the poststimulation undershoot in BOLD MRI of the human brain
- 2011
-
In: Journal of Cerebral Blood Flow and Metabolism. - : SAGE Publications. - 1559-7016 .- 0271-678X. ; 31:1, s. 82-89
-
Journal article (peer-reviewed)abstract
- One of the characteristics of the blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) response to functional challenges of the brain is the poststimulation undershoot, which has been suggested to originate from a delayed recovery of either cerebral blood volume (CBV) or cerebral metabolic rate of oxygen to baseline. Using bolus-tracking MRI in humans, we recently showed that relative CBV rapidly normalizes after the end of stimulation. As this observation contradicts at least part of the blood-pool contrast agent studies performed in animals, we reinvestigated the CBV contribution by dynamic T1-weighted three-dimensional MRI (8 seconds temporal resolution) and Vasovist at 3 T (12 subjects). Initially, we determined the time constants of individual BOLD responses. After injection of Vasovist, CBV-related T1-weighted signal changes revealed a signal increase during visual stimulation (1.7%±0.4%), but no change relative to baseline in the poststimulation phase (0.2%±0.3%). This finding renders the specific nature of the contrast agent unlikely to be responsible for the discrepancy between human and animal studies. With the assumption of normalized cerebral blood flow after stimulus cessation, a normalized CBV lends support to the idea that the BOLD MRI undershoot reflects a prolonged elevation of oxidative metabolism.
|
|
| 2. |
|
|
| 3. |
- Ahlstedt, Jonatan, et al.
(author)
-
Growth pattern of experimental glioblastoma
- 2020
-
In: Histology and Histopathology. - 1699-5848. ; 35:8, s. 871-886
-
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.
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
- Callaghan, Martina F, et al.
(author)
-
Example dataset for the hMRI toolbox
- 2019
-
In: Data in Brief. - : Elsevier BV. - 2352-3409.
-
Journal article (peer-reviewed)abstract
- The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner’s transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research.
|
|
| 9. |
|
|
| 10. |
- Dathe, Henning, et al.
(author)
-
Exact algebraization of the signal equation of spoiled gradient echo MRI
- 2010
-
In: Physics in Medicine and Biology. - : IOP Publishing. - 1361-6560 .- 0031-9155. ; 55, s. 4231-4245
-
Journal article (peer-reviewed)abstract
- The Ernst equation for Fourier transform nuclear magnetic resonance (MR) describes the spoiled steady-state signal created by periodic partial excitation. In MR imaging (MRI), it is commonly applied to spoiled gradient-echo acquisition in the steady state, created by a small flip angle α at a repetition time TR much shorter than the longitudinal relaxation time T1. We describe two parameter transformations of α and TR/T1, which render the Ernst equation as a low-order rational function. Computer algebra can be readily applied for analytically solving protocol optimization, as shown for the dual flip angle experiment. These transformations are based on the half-angle tangent substitution and its hyperbolic analogue. They are monotonic and approach identity for small α and small TR/T1 with a third-order error. Thus, the exact algebraization can be readily applied to fast gradient echo MRI to yield a rational approximation in α and TR/T1. This reveals a fundamental relationship between the square of the flip angle and TR/T1 which characterizes the Ernst angle, constant degree of T1-weighting and the influence of the local radiofrequency field.
|
|
