Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Voluntary Explicit versus Involuntary Conceptual Memory Are Associated with Dissociable fMRI Responses in Hippocampus, Amygdala, and Parietal Cortex for Emotional and Neutral Word Pairs.

Although functional neuroimaging studies have supported the distinction between explicit and implicit forms of memory, few have matched explicit and implicit tests closely, and most of these tested perceptual rather than conceptual implicit memory. We compared event-related fMRI responses during an intentional test, in which a group of participants used a cue word to recall its associate from a prior study phase, with those in an incidental test, in which a different group of participants used the same cue to produce the first associate that came to mind. Both semantic relative to phonemic processing at study, and emotional relative to neutral word pairs, increased target completions in the intentional test, but not in the incidental test, suggesting that behavioral performance in the incidental test was not contaminated by voluntary explicit retrieval. We isolated the neural correlates of successful retrieval by contrasting fMRI responses to studied versus unstudied cues for which the equivalent "target" associate was produced. By comparing the difference in this repetition-related contrast across the intentional and incidental tests, we could identify the correlates of voluntary explicit retrieval. This contrast revealed increased bilateral hippocampal responses in the intentional test, but decreased hippocampal responses in the incidental test. A similar pattern in the bilateral amygdale was further modulated by the emotionality of the word pairs, although surprisingly only in the incidental test. Parietal regions, however, showed increased repetition-related responses in both tests. These results suggest that the neural correlates of successful voluntary explicit memory differ in directionality, even if not in location, from the neural correlates of successful involuntary implicit (or explicit) memory, even when the incidental test taps conceptual processes.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Brain Surface Segmentation of Magnetic Resonance Images of the Fetus

In this work we present a method for the image analysisof Magnetic Resonance Imaging (MRI) of fetuses. Our goalis to segment the brain surface from multiple volumes(axial, coronal and sagittal acquisitions) of a fetus. Tothis end we propose a two-step approach: first, a FiniteGaussian Mixture Model (FGMM) will segment the image into3 classes: brain, non-brain and mixture voxels. Second, aMarkov Random Field scheme will be applied tore-distribute mixture voxels into either brain ornon-brain tissue. Our main contributions are an adaptedenergy computation and an extended neighborhood frommultiple volumes in the MRF step. Preliminary results onfour fetuses of different gestational ages will be shown.

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness.

The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.

Daytime sleepiness with and without cataplexy in Chinese-Taiwanese patients.

BACKGROUND AND PURPOSE: Investigation of Chinese-Taiwanese patients with excessive sleepiness, but no association with other sleep disorders, and with the presence or absence of cataplexy. PATIENTS AND METHODS: Thirty-five patients, successively referred between 2002 and 2004, underwent polysomnography (PSG), repeat multiple sleep latency test (MSLT), and human leukocyte antigen (HLA) typing. Three patients without cataplexy also had cerebrospinal fluid (CSF) hypocretin measurements. RESULTS: DQB1*0602 was associated with cataplexy in over 90% of Chinese-Taiwanese cases. Absence of cataplexy and <2 sleep-onset REM periods (SOREMPs) was seen in only two subjects, but presence of two SOREMPs did not dissociate DQB1*0602 positive and negative or cataplexy positive and negative subjects. As a group, narcoleptics with cataplexy had a higher number of SOREMPs, and the mean sleep latency was much shorter in narcoleptics with cataplexy than in the non-cataplectic patients, independent of the number of SOREMPs. CONCLUSIONS: Chinese-Taiwanese patients with cataplexy present with similar HLA findings as Black and Caucasian patients, but the presence of two or more SOREMPs in Chinese-Taiwanese patients is not a sufficient diagnostic tool to identify narcolepsy. When cataplexy is not present, description of PSG nd HLA findings may be a better approach than using a label with little scientific significance, allowing for better collection of patients' phenotype.

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy.

Blood pressure and LDL-cholesterol targets for prevention of recurrent strokes and cognitive decline in the hypertensive patient: design of the European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment randomized trial.

BACKGROUND AND OBJECTIVES: The SBP values to be achieved by antihypertensive therapy in order to maximize reduction of cardiovascular outcomes are unknown; neither is it clear whether in patients with a previous cardiovascular event, the optimal values are lower than in the low-to-moderate risk hypertensive patients, or a more cautious blood pressure (BP) reduction should be obtained. Because of the uncertainty whether 'the lower the better' or the 'J-curve' hypothesis is correct, the European Society of Hypertension and the Chinese Hypertension League have promoted a randomized trial comparing antihypertensive treatment strategies aiming at three different SBP targets in hypertensive patients with a recent stroke or transient ischaemic attack. As the optimal level of low-density lipoprotein cholesterol (LDL-C) level is also unknown in these patients, LDL-C-lowering has been included in the design. PROTOCOL DESIGN: The European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment trial is a prospective multinational, randomized trial with a 3 × 2 factorial design comparing: three different SBP targets (1, <145-135; 2, <135-125; 3, <125 mmHg); two different LDL-C targets (target A, 2.8-1.8; target B, <1.8 mmol/l). The trial is to be conducted on 7500 patients aged at least 65 years (2500 in Europe, 5000 in China) with hypertension and a stroke or transient ischaemic attack 1-6 months before randomization. Antihypertensive and statin treatments will be initiated or modified using suitable registered agents chosen by the investigators, in order to maintain patients within the randomized SBP and LDL-C windows. All patients will be followed up every 3 months for BP and every 6 months for LDL-C. Ambulatory BP will be measured yearly. OUTCOMES: Primary outcome is time to stroke (fatal and non-fatal). Important secondary outcomes are: time to first major cardiovascular event; cognitive decline (Montreal Cognitive Assessment) and dementia. All major outcomes will be adjudicated by committees blind to randomized allocation. A Data and Safety Monitoring Board has open access to data and can recommend trial interruption for safety. SAMPLE SIZE CALCULATION: It has been calculated that 925 patients would reach the primary outcome after a mean 4-year follow-up, and this should provide at least 80% power to detect a 25% stroke difference between SBP targets and a 20% difference between LDL-C targets.