ObjectiveWe used magnetization transfer imaging to assess white matter tissue integrity in migraine, to explore whether white matter microstructure was more diffusely affected beyond visible white... Show moreObjectiveWe used magnetization transfer imaging to assess white matter tissue integrity in migraine, to explore whether white matter microstructure was more diffusely affected beyond visible white matter hyperintensities (WMHs), and to explore whether focal invisible microstructural changes precede visible focal WMHs in migraineurs.MethodsWe included 137 migraineurs (79 with aura, 58 without aura) and 74 controls from the Cerebral Abnormalities in Migraine, an Epidemiological Risk Analysis (CAMERA) study, a longitudinal population-based study on structural brain lesions in migraine patients, who were scanned at baseline and at a 9-year follow-up. To assess microstructural brain tissue integrity, baseline magnetization transfer ratio (MTR) values were calculated for whole brain white matter. Baseline MTR values were determined for areas of normal-appearing white matter (NAWM) that had progressed into MRI-detectable WMHs at follow-up and compared to MTR values of contralateral NAWM.ResultsMTR values for whole brain white matter did not differ between migraineurs and controls. In migraineurs, but not in controls, NAWM that later progressed to WMHs at follow-up had lower mean MTR (mean [SD] 0.354 [0.009] vs 0.356 [0.008], p = 0.047) at baseline as compared to contralateral white matter.ConclusionsWe did not find evidence for widespread microstructural white matter changes in migraineurs compared to controls. However, our findings suggest that a gradual or stepwise process might be responsible for evolution of focal invisible microstructural changes into focal migraine-related visible WMHs. Show less
Buijs, M.; Doan, N.T.; Rooden, S. van; Versluis, M.J.; Lew, B. van; Milles, J.; ... ; Buchem, M.A. van 2017
BACKGROUND AND PURPOSE:MTI is a quantitative MR imaging technique that has recently demonstrated structural integrity differences between controls and patients with HD. Potentially, MTI can be used... Show moreBACKGROUND AND PURPOSE:MTI is a quantitative MR imaging technique that has recently demonstrated structural integrity differences between controls and patients with HD. Potentially, MTI can be used as a biomarker for monitoring disease progression. To establish the value of MTI as a biomarker, we aimed to examine the change in these measures during the course of HD.MATERIALS AND METHODS:From the Leiden TRACK-HD study, 25 controls, 21 premanifest gene carriers, and 21 patients with manifest HD participated at baseline and during a 2-year follow-up visit. Brain segmentation of the cortical gray matter, white matter, caudate nucleus, putamen, pallidum, thalamus, amygdala, and hippocampus was performed by using the automated tools FAST and FIRST in FSL. Individual MTR values were calculated from these regions, and MTR histograms were constructed.RESULTS:In the premanifest HD group stage "far from disease onset," a significant increase in MTR peak height of the putamen was observed with time. During the manifest HD stage, neither the mean MTR nor the MTR peak height showed a significant change during a 2-year follow-up.CONCLUSIONS:MTI-derived measures are not suitable for monitoring in Huntington disease during a 2-year period because there was no decrease in structural integrity detected in any of the manifest HD groups longitudinally. The finding of increased putaminal MTR peak height in the premanifest far from disease onset group could relate to a predegenerative process, compensatory mechanisms, or aberrant development but should be interpreted with caution until future studies confirm this finding. Show less
Doan, N.T.; Rooden, S. van; Versluis, M.J.; Webb, A.G.; Grond, J. van der; Buchem, M.A. van; ... ; Milles, J. 2012
Huntington's disease (HD) is characterized by brain atrophy. Localized atrophy of a specific structure could potentially be a more sensitive biomarker reflecting neuropathologic changes rather than... Show moreHuntington's disease (HD) is characterized by brain atrophy. Localized atrophy of a specific structure could potentially be a more sensitive biomarker reflecting neuropathologic changes rather than global volume variation. We examined 90 TRACK-HD participants of which 30 were premanifest HD, 30 were manifest HD and 30 were controls. Using FMRIB's Integrated Registration and Segmentation Tool, segmentations were obtained for the pallidum, caudate nucleus, putamen, thalamus, accumbens nucleus, amygdala, and hippocampus and overall volumes were calculated. A point distribution model of each structure was obtained using Growing and Adaptive Meshes. Permutation testing between groups was performed to detect local displacement in shape between groups. In premanifest HD overall volume loss occurred in the putamen, accumbens and caudate nucleus. Overall volume reductions in manifest HD were found in all subcortical structures, except the amygdala, as compared to controls. In premanifest HD shape analysis showed small areas of displacement in the putamen, pallidum, accumbens and caudate nucleus. When the premanifest group was split into two groups according to predicted disease onset, the premanifest HD group close to expected disease onset showed more pronounced displacements in caudate nucleus and putamen compared to premanifest HD far from disease onset or the total premanifest group. Analysis of shape in manifest HD showed widespread shape differences, most prominently in the caudal part of the accumbens nucleus, body of the caudate nucleus, putamen and dorsal part of the pallidum. We conclude that shape analysis provides new insights in localized intrastructural atrophy patterns in HD, but can also potentially serve as specific target areas for disease tracking. (C) 2011 Elsevier B.V. All rights reserved. Show less
Ferrarini, L.; Veer, I.M.; Lew, B. van; Oei, N.Y.L.; Buchem, M.A. van; Reiber, J.H.C.; ... ; Milles, J. 2011
In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological... Show moreIn recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover. functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however. was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r2 statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches. based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. (C) 2011 Elsevier Inc. All rights reserved. Show less
Nested or intersecting surfaces are proven techniques for visualizing shape differences between static 3D objects (Weigle and Taylor II, IEEE Visualization, Proceedings, pp. 503-510, 2005). In this... Show moreNested or intersecting surfaces are proven techniques for visualizing shape differences between static 3D objects (Weigle and Taylor II, IEEE Visualization, Proceedings, pp. 503-510, 2005). In this paper we present an image-based formulation for these techniques that extends their use to dynamic scenarios, in which surfaces can be manipulated or even deformed interactively. The formulation is based on our new layered rendering pipeline, a generic image-based approach for rendering nested surfaces based on depth peeling and deferred shading. We use layered rendering to enhance the intersecting surfaces visualization. In addition to enabling interactive performance, our enhancements address several limitations of the original technique. Contours remove ambiguity regarding the shape of intersections. Local distances between the surfaces can be visualized at any point using either depth fogging or distance fields: Depth fogging is used as a cue for the distance between two surfaces in the viewing direction, whereas closest-point distance measures are visualized interactively by evaluating one surface's distance field on the other surface. Furthermore, we use these measures to define a three-way surface segmentation, which visualizes regions of growth, shrinkage, and no change of a test surface compared with a reference surface. Finally, we demonstrate an application of our technique in the visualization of statistical shape models. We evaluate our technique based on feedback provided by medical image analysis researchers, who are experts in working with such models. Show less
Alzheimer's disease (AD) is a progressive disease usually accompanied by regional atrophy that can be detected noninvasively using structural magnetic resonance imaging (MRI). An abundant... Show moreAlzheimer's disease (AD) is a progressive disease usually accompanied by regional atrophy that can be detected noninvasively using structural magnetic resonance imaging (MRI). An abundant literature has demonstrated the value of quantitative measurements of regional atrophy in AD, suggesting that MR based volumetry and morphometry could be valuable and useful in clinical practice. The aim of this paper is mainly to recall the most critical points to consider when using MRI for automated brain volumetry and morphometry and review briefly the main findings in the literature on brain volumetry and morphometry in AD. Show less
Baiker, M.; Milles, J.; Dijkstra, J.; Henning, T.D.; Weber, A.W.; Que, I.; ... ; Lelieveldt, B.P.F. 2010
This paper presents a fully automated method for atlas-based whole-body segmentation in non-contrast-enhanced Micro-CT data of mice. The position and posture of mice in such studies may vary to a... Show moreThis paper presents a fully automated method for atlas-based whole-body segmentation in non-contrast-enhanced Micro-CT data of mice. The position and posture of mice in such studies may vary to a large extent, complicating data comparison in cross-sectional and follow-up studies. Moreover. Micro-CT typically yields only poor soft-tissue contrast for abdominal organs. To overcome these challenges, we propose a method that divides the problem into an atlas constrained registration based on high-contrast organs in Micro-CT (skeleton, lungs and skin), and a soft tissue approximation step for low-contrast organs. We first present a modification of the MOBY mouse atlas (Segars et al., 2004) by partitioning the skeleton into individual bones, by adding anatomically realistic joint types and by defining a hierarchical atlas tree description. The individual bones as well as the lungs of this adapted MOBY atlas are then registered one by one traversing the model tree hierarchy. To this end, we employ the Iterative Closest Point method and constrain the Degrees of Freedom of the local registration, dependent on the joint type and motion range. This atlas-based strategy renders the method highly robust to exceptionally large postural differences among scans and to moderate pathological bone deformations. The skin of the torso is registered by employing a novel method for matching distributions of geodesic distances locally, constrained by the registered skeleton. Because of the absence of image contrast between abdominal organs, they are interpolated from the atlas to the subject domain using Thin-Plate-Spline approximation, defined by correspondences on the already established registration of high-contrast structures (bones, lungs and skin). We extensively evaluate the proposed registration method, using 26 non-contrast-enhanced Micro-CT datasets of mice, and the skin registration and organ interpolation, using contrast-enhanced Micro-CT datasets of 15 mice. The posture and shape varied significantly among the animals and the data was acquired in vivo. After registration, the mean Euclidean distance was less than two voxel dimensions for the skeleton and the lungs respectively and less than one voxel dimension for the skin. Dice coefficients of volume overlap between manually segmented and interpolated skeleton and organs vary between 0.47 +/- 0.08 for the kidneys and 0.73 +/- 0.04 for the brain. These experiments demonstrate the method's effectiveness for overcoming exceptionally large variations in posture, yielding acceptable approximation accuracy even in the absence of soft-tissue contrast in in vivo Micro-CT data without requiring user initialization. (c) 2010 Elsevier B.V. All rights reserved. Show less
Gupta, V.; Hendriks, E.A.; Milles, J.; Geest, R.J. van der; Jerosch-Herold, M.; Reiber, J.H.C.; Lelieveldt, B.P.F. 2010
Rationale and Objectives: Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation... Show moreRationale and Objectives: Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation of the myocardium in a large number of images. To reduce the manual interaction and expedite the perfusion analysis, we propose an automatic registration and segmentation method for the derivation of perfusion linked parameters. Materials and Methods: A complete automation was accomplished by first registering misaligned images using a method based on independent component analysis, and then using the registered data to automatically segment the myocardium with active appearance models. We used 18 perfusion studies (100 images per study) for validation in which the automatically obtained (AO) contours were compared with expert drawn contours on the basis of point-to-curve error, Dice index, and relative perfusion upslope in the myocardium. Results: Visual inspection revealed successful segmentation in 15 out of 18 studies. Comparison of the AO contours with expert drawn contours yielded 2.23 0.53 mm and 0.91 +/- 0.02 as point-to-curve error and Dice index, respectively. The average difference between manually and automatically obtained relative upslope parameters was found to be statistically insignificant (P = .37). Moreover, the analysis time per slice was reduced from 20 minutes (manual) to 1.5 minutes (automatic), Conclusion: We proposed an automatic method that significantly reduced the time required for analysis of first-pass cardiac magnetic resonance perfusion images. The robustness and accuracy of the proposed method were demonstrated by the high spatial correspondence and statistically insignificant difference in perfusion parameters, when AO contours were compared with expert drawn contours. Show less
Bogaard, S.J.A. van den; Dumas, E.M.; Milles, J.; Buchem, M. van; Grond, J. van der; Roos, R.A.C. 2010
Accurate assessment of the size and distribution of a myocardial infarction (MI) from late gadolinium enhancement (LGE) MRI is of significant prognostic value for postinfarction patients. In this... Show moreAccurate assessment of the size and distribution of a myocardial infarction (MI) from late gadolinium enhancement (LGE) MRI is of significant prognostic value for postinfarction patients. In this paper, an automatic MI identification method combining both intensity and spatial information is presented in a clear framework of (i) initialization, (ii) false acceptance removal, and (iii) false rejection removal. The method was validated on LGE MR images of 20 chronic postinfarction patients, using manually traced MI contours from two independent observers as reference. Good agreement was observed between automatic and manual MI identification. Validation results showed that the average Dice indices, which describe the percentage of overlap between two regions, were 0.83 +/- 0.07 and 0.79 +/- 0.08 between the automatic identification and the manual tracing from observer 1 and observer 2, and the errors in estimated infarct percentage were 0.0 +/- 1.9% and 3.8 +/- 4.7% compared with observer 1 and observer 2. The difference between the automatic method and manual tracing is in the order of interobserver variation. In conclusion, the developed automatic method is accurate and robust in MI delineation, providing an objective tool for quantitative assessment of MI in LGE MR imaging. Magn Reson Med 64:586-594, 2010. (C) 2010 Wiley-Liss, Inc. Show less
