A fully-automatic caudate nucleus segmentation of brain MRI: application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder

Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.

GDAP1-related autosomal dominant Charcot-Marie-Tooth disease: phenotypical and MRI features

El present estudi es basa en la descripció de quatre famílies portadores d’una mateixa mutació puntual (p.R120W) en el gen GDAP1 que segreguen d’una manera autosòmica dominant. Les trobades més rellevants foren:  Els individus afectats varen tindre un començament més tardà i un fenotipus més lleu que les mutacions recessives del gen GDAP-1, però amb una gran variabilitat clínica.  La Resonància Magnètica Muscular va demostrar una afectació selectiva de la musculatura intrínseca del peu i la part distal del panxell. El compartiment posterior superficial de la musculatura del panxell estava més afectat que el compartiment anterolateral.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Segmentació de teixit i lesions en imatges de MRI de malalts d'esclerosi múltiple

Actualment, en l'àmbit mèdic, la ressonància magnètica, MRI Magnetic Resonance Imaging, és un dels sistemes més utilitzats per a la realització de diagnòstics i el seguiment de l'evolució de malalties com l'esclerosi múltiple (EM). No obstant, la gran quantitat d'informació que proporciona aquesta modalitat té com a conseqüència una tasca feixuga d'anàlisi i d'interpretació per part dels radiòlegs i neuròlegs. L'objectiu general d'aquest projecte és desenvolupar un sistema per ajudar als metges a segmentar les imatges de MRI del cervell. S'ha implementat amb MATLAB. Durant tot el procés s'han utilitzat dades sintètiques, de la base de dades simulada BrainWeb, i reals, proporcionades pels grup de metges col•laboradors amb el grup VICOROB.El projecte s'emmarca dins d'un projecte de recerca del grup de Visió per Computador i Robòtica de la Universitat de Girona

Cardiac motion estimation by joint alignment of tagged MRI sequences

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

Virtual milgram : empathic concern or personal distress? Evidence from functional MRI and dispositional measures

One motive for behaving as the agent of another"s aggression appears to be anchored in as yet unelucidated mechanisms of obedience to authority. In a recent partial replication of Milgram"s obedience paradigm within an immersive virtual environment, participants administered pain to a female virtual human and observed her suffering. Whether the participants" response to the latter was more akin to other-oriented empathic concern for her well-being or to a self-oriented aversive state of personal distress in response to her distress is unclear. Using the stimuli from that study, this event-related fMRI-based study analysed brain activity during observation of the victim in pain versus not in pain. This contrast revealed activation in pre-defi ned brain areas known to be involved in affective processing but not in those commonly associated with affect sharing (e.g., ACC and insula). We then examined whether different dimensions of dispositional empathy predict activity within the same pre-defi ned brain regions: While personal distress and fantasy (i.e., tendency to transpose oneself into fi ctional situations and characters) predicted brain activity, empathic concern and perspective taking predicted no change in neuronal response associated with pain observation. These exploratory fi ndings suggest that there is a distinct pattern of brain activity associated with observing the pain-related behaviour of the victim within the context of this social dilemma, that this observation evoked a self-oriented aversive state of personal distress, and that the objective"reality" of pain is of secondary importance for this response. These fi ndings provide a starting point for experimentally more rigorous investigation of obedience.

Threshold Selection Criteria for Quantification of Lumbosacral Cerebrospinal Fluid and Root Volumes from MRI

BACKGROUND AND PURPOSE: The high variability of CSF volumes partly explains the inconsistency of anesthetic effects, but may also be due to image analysis itself. In this study, criteria for threshold selection are anatomically defined. METHODS: T2 MR images (n = 7 cases) were analyzed using 3-dimentional software. Maximal-minimal thresholds were selected in standardized blocks of 50 slices of the dural sac ending caudally at the L5-S1 intervertebral space (caudal blocks) and middle L3 (rostral blocks). Maximal CSF thresholds: threshold value was increased until at least one voxel in a CSF area appeared unlabeled and decreased until that voxel was labeled again: this final threshold was selected. Minimal root thresholds: thresholds values that selected cauda equina root area but not adjacent gray voxels in the CSF-root interface were chosen. RESULTS: Significant differences were found between caudal and rostral thresholds. No significant differences were found between expert and nonexpert observers. Average max/min thresholds were around 1.30 but max/min CSF volumes were around 1.15. Great interindividual CSF volume variability was detected (max/min volumes 1.6-2.7). CONCLUSIONS: The estimation of a close range of CSF volumes which probably contains the real CSF volume value can be standardized and calculated prior to certain intrathecal procedures