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Frans M. Vos

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4 papers
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4

YNICL Journal 2023 Journal Article

White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis

  • Martijn A. Nagtegaal
  • Ingo Hermann
  • Sebastian Weingärtner
  • Eloy Martinez-Heras
  • Elisabeth Solana
  • Sara Llufriu
  • Achim Gass
  • Dirk H.J. Poot

T 2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component’s volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0. 004 (0. 0006–0. 008), p = 0. 02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0. 47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

YNIMG Journal 2020 Journal Article

Sharpness in motion corrected quantitative imaging at 7T

  • Pierre-Louis Bazin
  • Hannah E. Nijsse
  • Wietske van der Zwaag
  • Daniel Gallichan
  • Anneke Alkemade
  • Frans M. Vos
  • Birte U. Forstmann
  • Matthan W.A. Caan

Sub-millimeter imaging at 7T has opened new possibilities for qualitatively and quantitatively studying brain structure as it evolves throughout the life span. However, subject motion introduces image blurring on the order of magnitude of the spatial resolution and is thus detrimental to image quality. Such motion can be corrected for, but widespread application has not yet been achieved and quantitative evaluation is lacking. This raises a need to quantitatively measure image sharpness throughout the brain. We propose a method to quantify sharpness of brain structures at sub-voxel resolution, and use it to assess to what extent limited motion is related to image sharpness. The method was evaluated in a cohort of 24 healthy volunteers with a wide and uniform age range, aiming to arrive at results that largely generalize to larger populations. Using 3D fat-excited motion navigators, quantitative R 1, R 2 * and Quantitative Susceptibility Maps and T 1-weighted images were retrospectively corrected for motion. Sharpness was quantified in all modalities for selected regions of interest (ROI) by fitting the sigmoidally shaped error function to data within locally homogeneous clusters. A strong, almost linear correlation between motion and sharpness improvement was observed, and motion correction significantly improved sharpness. Overall, the Full Width at Half Maximum reduced from 0. 88 mm to 0. 70 mm after motion correction, equivalent to a 2. 0 times smaller voxel volume. Motion and sharpness were not found to correlate with the age of study participants. We conclude that in our data, motion correction using fat navigators is overall able to restore the measured sharpness to the imaging resolution, irrespective of the amount of motion observed during scanning.

YNICL Journal 2020 Journal Article

Spatial versus angular resolution for tractography-assisted planning of deep brain stimulation

  • Luka C. Liebrand
  • Guido A. van Wingen
  • Frans M. Vos
  • Damiaan Denys
  • Matthan W.A. Caan

Given the restricted total scanning time for clinical neuroimaging, it is unclear whether clinical diffusion MRI protocols would benefit more from higher spatial resolution or higher angular resolution. In this work, we investigated the relative benefit of improving spatial or angular resolution in diffusion MRI to separate two parallel running white matter tracts that are targets for deep brain stimulation: the anterior thalamic radiation and the supero-lateral branch of the medial forebrain bundle. Both these tracts are situated in the ventral anterior limb of the internal capsule, and recent studies suggest that targeting a specific tract could improve treatment efficacy. Therefore, we scanned 19 healthy volunteers at 3T and 7T according to three diffusion MRI protocols with respectively standard clinical settings, increased spatial resolution of 1. 4 mm, and increased angular resolution (64 additional gradient directions at b = 2200s/mm2). We performed probabilistic tractography for all protocols and quantified the separability of both tracts. The higher spatial resolution protocol improved separability by 41% with respect to the clinical standard, presumably due to decreased partial voluming. The higher angular resolution protocol resulted in increased apparent tract volumes and overlap, which is disadvantageous for application in precise treatment planning. We thus recommend to increase the spatial resolution for deep brain stimulation planning to 1. 4 mm while maintaining angular resolution. This recommendation complements the general advice to aim for high angular resolution to resolve crossing fibers, confirming that the specific application and anatomical considerations are leading in clinical diffusion MRI protocol optimization.

YNIMG Journal 2013 Journal Article

Improving alignment in Tract-based spatial statistics: Evaluation and optimization of image registration

  • Marius de Groot
  • Meike W. Vernooij
  • Stefan Klein
  • M. Arfan Ikram
  • Frans M. Vos
  • Stephen M. Smith
  • Wiro J. Niessen
  • Jesper L.R. Andersson

Anatomical alignment in neuroimaging studies is of such importance that considerable effort is put into improving the registration used to establish spatial correspondence. Tract-based spatial statistics (TBSS) is a popular method for comparing diffusion characteristics across subjects. TBSS establishes spatial correspondence using a combination of nonlinear registration and a “skeleton projection” that may break topological consistency of the transformed brain images. We therefore investigated feasibility of replacing the two-stage registration-projection procedure in TBSS with a single, regularized, high-dimensional registration. To optimize registration parameters and to evaluate registration performance in diffusion MRI, we designed an evaluation framework that uses native space probabilistic tractography for 23 white matter tracts, and quantifies tract similarity across subjects in standard space. We optimized parameters for two registration algorithms on two diffusion datasets of different quality. We investigated reproducibility of the evaluation framework, and of the optimized registration algorithms. Next, we compared registration performance of the regularized registration methods and TBSS. Finally, feasibility and effect of incorporating the improved registration in TBSS were evaluated in an example study. The evaluation framework was highly reproducible for both algorithms (R2 0. 993; 0. 931). The optimal registration parameters depended on the quality of the dataset in a graded and predictable manner. At optimal parameters, both algorithms outperformed the registration of TBSS, showing feasibility of adopting such approaches in TBSS. This was further confirmed in the example experiment.

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