We describe a new method to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls, based on multidimensional classification ...of hippocampal shape features. This approach uses spherical harmonics (SPHARM) coefficients to model the shape of the hippocampi, which are segmented from magnetic resonance images (MRI) using a fully automatic method that we previously developed. SPHARM coefficients are used as features in a classification procedure based on support vector machines (SVM). The most relevant features for classification are selected using a bagging strategy. We evaluate the accuracy of our method in a group of 23 patients with AD (10 males, 13 females, age±standard-deviation (SD)=73±6 years, mini-mental score (MMS)=24.4±2.8), 23 patients with amnestic MCI (10 males, 13 females, age±SD=74±8 years, MMS=27.3±1.4) and 25 elderly healthy controls (13 males, 12 females, age±SD=64±8 years), using leave-one-out cross-validation. For AD vs controls, we obtain a correct classification rate of 94%, a sensitivity of 96%, and a specificity of 92%. For MCI vs controls, we obtain a classification rate of 83%, a sensitivity of 83%, and a specificity of 84%. This accuracy is superior to that of hippocampal volumetry and is comparable to recently published SVM-based whole-brain classification methods, which relied on a different strategy. This new method may become a useful tool to assist in the diagnosis of Alzheimer's disease.
Recently, several high dimensional classification methods have been proposed to automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and ...elderly controls (CN) based on T1-weighted MRI. However, these methods were assessed on different populations, making it difficult to compare their performance. In this paper, we evaluated the performance of ten approaches (five voxel-based methods, three methods based on cortical thickness and two methods based on the hippocampus) using 509 subjects from the ADNI database. Three classification experiments were performed: CN vs AD, CN vs MCIc (MCI who had converted to AD within 18months, MCI converters — MCIc) and MCIc vs MCInc (MCI who had not converted to AD within 18months, MCI non-converters — MCInc). Data from 81 CN, 67 MCInc, 39 MCIc and 69 AD were used for training and hyperparameters optimization. The remaining independent samples of 81 CN, 67 MCInc, 37 MCIc and 68 AD were used to obtain an unbiased estimate of the performance of the methods. For AD vs CN, whole-brain methods (voxel-based or cortical thickness-based) achieved high accuracies (up to 81% sensitivity and 95% specificity). For the detection of prodromal AD (CN vs MCIc), the sensitivity was substantially lower. For the prediction of conversion, no classifier obtained significantly better results than chance. We also compared the results obtained using the DARTEL registration to that using SPM5 unified segmentation. DARTEL significantly improved six out of 20 classification experiments and led to lower results in only two cases. Overall, the use of feature selection did not improve the performance but substantially increased the computation times.
► Alzheimer vs controls : high accuracies with whole-brain methods (up to 81% sensitivity - 95% specificity). ► For the detection of prodromal Alzheimer, the sensitivity was substantially lower. ► For the prediction of conversion, the accuracy was only slightly higher than chance.
OBJECTIVE. 7-Tesla MRI of the hippocampus enhances the visualization of its internal substructures. Among these substructures, the cornu Ammonis and subiculum form a contiguous folded ribbon of gray ...matter. Here, we propose a method to analyze local thickness measurements of this ribbon. METHODS. We introduce an original approach based upon the estimation of a diffeomorphic vector field that traverses the ribbon. The method is designed to handle specificities of the hippocampus and corresponding 7-Tesla acquisitions: highly convoluted surface, non closed ribbon, incompletely defined inner/outer boundaries, anisotropic acquisitions. We furthermore propose to conduct group comparisons using a population template built from the central surfaces of individual subjects. RESULTS. We first assessed the robustness of our approach to anisotropy, as well as to inter-rater variability, on a post-mortem scan and on in vivo acquisitions respectively. We then conducted a group study on a dataset of in vivo MRI from temporal lobe epilepsy (TLE) patients and healthy controls. The method detected local thinning patterns in patients, predominantly ipsilaterally to the seizure focus, which is consistent with medical knowledge. CONCLUSION. This new technique allows measuring the thickness of the hippocampus from 7-Tesla MRI. It shows good robustness with respect to anisotropy and inter-rater variability and has the potential to detect local atrophy in patients. SIGNIFICANCE. As 7-Tesla MRI is increasingly available, this new method may become a useful tool to study local alterations of the hippocampus in brain disorders. It is made freely available to the community (code: https://github.com/aramis-lab/hiplay7-thickness, postmortem segmentation: https://doi.org/10.5281/zenodo.3533264).
Gilles de la Tourette syndrome is a childhood-onset neurodevelopmental disorder characterized by tics that are often associated with psychiatric co-morbidities. The clinical heterogeneity of Gilles ...de la Tourette syndrome has been attributed to the disturbance of functionally distinct cortico-striato-thalamo-cortical circuits, but this remains to be demonstrated. The aim of this study was to determine the structural correlates of the diversity of symptoms observed in Gilles de la Tourette syndrome. We examined 60 adult patients and 30 age- and gender-matched control subjects using cortical thickness measurement and 3 T high-resolution T1-weighted images. Patients were divided into three clinical subgroups: (i) simple tics; (ii) simple and complex tics and (iii) tics with associated obsessive–compulsive disorders. Patients with Gilles de la Tourette syndrome had reduced cortical thickness in motor, premotor, prefrontal and lateral orbito-frontal cortical areas. The severity of tics was assessed using the Yale Global Tic Severity Scale and correlated negatively with cortical thinning in these regions, as well as in parietal and temporal cortices. The pattern of cortical thinning differed among the clinical subgroups of patients. In patients with simple tics, cortical thinning was mostly found in primary motor regions. In patients with simple and complex tics, thinning extended into larger premotor, prefrontal and parietal regions. In patients with associated obsessive–compulsive disorders, there was a trend for reduced cortical thickness in the anterior cingulate cortex and hippocampal morphology was altered. In this clinical subgroup, scores on the Yale–Brown Obsessive–Compulsive Scale correlated negatively with cortical thickness in the anterior cingulate cortex and positively in medial premotor regions. These data support the hypothesis that different symptom dimensions in Gilles de la Tourette syndrome are associated with dysfunction of distinct cortical areas and have clear implications for the current neuroanatomical model of this syndrome.
Recent advances in miniaturization technology make polymer electrolyte membrane fuel cells very attractive as power sources for portable devices. Ion‐exchange membranes for microscale fuel cells are ...synthesized by plasma polymerization (using a precursor containing ion‐exchange groups) and intensively characterized. Ion‐exchange plasma membranes are thin, amorphous, and dense materials with no defects. Spectroscopic analyses reveal a polymer‐type matrix containing a rather high concentration of ion‐exchange groups. Under the best synthesis conditions, membranes show a satisfying ionic conduction level and a high compatibility with other active layers of fuel cells, making them suitable for insertion in such power‐supply devices.
Ion‐exchange membranes are synthesized by plasma polymerization. Under the best synthesis conditions, the fabricated membranes show a satisfying ionic conduction level and a high compatibility with other active layers of microscale fuel cells, which enables envisaging their insertion in such power‐supply devices for portable electronics.
The Free and Cued Selective Reminding Test (FCSRT) is a verbal episodic memory test used to identify patients with mild Alzheimer's disease (AD). The present study investigates the relationships ...between performance on FCSRT and grey matter atrophy assessed with structural MRI in patients with AD. Three complementary MRI-based analyses (VBM analysis, ROI-based analysis, and three-dimensional hippocampal surface-based shape analysis) were performed in 35 patients with AD to analyze correlations between regional atrophy and their scores for episodic memory using the FCSRT. With VBM analysis, the total score on the FCSRT was correlated with left medial temporal lobe atrophy including the left hippocampus but also the thalami. In addition, using ROI-based analysis, the total recall score on the FCSRT was correlated with the left hippocampal volume. With three-dimensional hippocampal surface-based shape analysis, both free recall and total recall scores were correlated with regions corresponding approximately to the CA1 field. No correlation was found with short term memory scores using any of these methods of analysis. In AD, the FCSRT may be considered as a useful clinical marker of memory disorders due to medial temporal damage, specially the CA1 field of the hippocampus.
Thin and uniform Ti-containing silicalite-1 (TS-1) membranes were prepared for the first time by a microwave-assisted secondary growth method. The influence of synthesis temperature (150–200°C), ...duration (90–150min) and Ti concentration in the mother sol (molar ratio Si/Ti=16–100) on the membrane formation were studied. The quantity of Ti species inserted in the silicalite-1 network was found to vary with these parameters, as well as the membrane quality and performance. TS-1 membranes with a Si/Ti molar ratio in the range 25–40 were successfully prepared from mother sols with compositions in the range Si/Ti=16–100. An original parabolic evolution of membrane thickness vs. Si/Ti in the mother sol was evidenced, with a minimum thickness for Si/Ti around 50. In all cases Ti species were inserted within the zeolite network as far as no TiO2 clusters were detected after the thermal treatment at 550°C. The membranes were typically 0.1–2μm thick top-layers and crystal preferential orientation varied from oblique- to c-crystal preferential orientation (CPO) when the temperature was increased from 160°C to 200°C. The permeances of He, N2, O2, CO2 were high and lied in the range 1.9–7.48×10−6molm−2s−1Pa−1 when measured between 25°C and 200°C. The most selective membrane, prepared at 190°C during 120min with a molar ratio Si/Ti=75 in the mother sol, had an ideal selectivity of 40 for n/i-C4H10 at 150°C and 105 for CO2/SF6 at 25°C.
Objective: 7-Tesla MRI of the hippocampus enhances the visualization of its internal substructures. Among these substructures, the cornu Ammonis and subiculum form a contiguous folded ribbon of gray ...matter. Here, we propose a method to analyze local thickness measurements of this ribbon. Methods: We introduce an original approach based upon the estimation of a diffeomorphic vector field that traverses the ribbon. The method is designed to handle specificities of the hippocampus and corresponding 7-Tesla acquisitions: highly convoluted surface, non-closed ribbon, incompletely defined inner/outer boundaries, anisotropic acquisitions. We furthermore propose to conduct group comparisons using a population template built from the central surfaces of individual subjects. Results: We first assessed the robustness of our approach to anisotropy, as well as to inter-rater variability, on a post-mortem scan and on in vivo acquisitions respectively. We then conducted a group study on a dataset of in vivo MRI from temporal lobe epilepsy (TLE) patients and healthy controls. The method detected local thinning patterns in patients, predominantly ipsilaterally to the seizure focus, which is consistent with medical knowledge. Conclusion: This new technique allows measuring the thickness of the hippocampus from 7-Tesla MRI. It shows good robustness with respect to anisotropy and inter-rater variability and has the potential to detect local atrophy in patients. Significance: As 7-Tesla MRI is increasingly available, this new method may become a useful tool to study local alterations of the hippocampus in brain disorders. It is made freely available to the community (code: https://github.com/aramis-lab/hiplay7-thickness , postmortem segmentation: https://doi.org/10.5281/zenodo.3533264 ).
L’hippocampe est une structure de substance grise du lobe temporal qui joue un rôle fondamental dans les processus de mémoire ainsi que dans de nombreuses pathologies (maladie d’Alzheimer, épilepsie, ...dépression...).Le développement de modèles morphométriques est essentiel pour étudier l’anatomie fonctionnelle de cette structure et les altérations associées à différentes pathologies. L’objectif de cette thèse est de développer et de valider des méthodes de morphométrie de l’hippocampe dans deux contextes distincts : l’étude de la forme externe de l’hippocampe à partir d’IRM conventionnelles (1.5T ou 3T) à résolution millimétrique, l’étude de sa structure interne à partir d’IRM 7T à très haute résolution spatiale. Ces deux contextes correspondent aux deux parties principales de la thèse.Dans une première partie, nous proposons une méthode pour la classification automatique de patients à partir de descripteurs morphométriques. Cette méthode repose sur une décomposition en harmoniques sphériques qui est combinée à un classifieur de type support vectormachine (SVM). La méthode est évaluée dans le contexte de la classification automatique de patients avec une maladie d’Alzheimer (MA), de patients mild cognitive impairment (MCI) et de sujets sains âgés. Elle est également comparée à d’autres approches et une validation plus exhaustive est proposée dans une population de 509 sujets issus de la base ADNI. Nous présentons enfin une autre application de la morphométrie pour l’étude des altérations structurelles associées au syndrome de Gilles de la Tourette.La seconde partie de la thèse est consacrée à la morphométrie de la structure interne de l’hippocampe à partir d’IRM à 7 Tesla. En effet, la structure interne de l’hippocampe est riche et complexe mais inaccessible à l’IRM conventionnelle. Nous proposons tout d’abord un atlas de la structure interne de l’hippocampe à partir de données postmortem acquises à 9.4T. Ensuite, nous proposons de modéliser la corne d’Ammon et le subiculum sous la forme d’un squelette et d’une mesure locale d’épaisseur. Pour ce faire, nous introduisons une méthode variationnelle originale utilisant des espaces de Hilbert à noyaux reproduisants. La méthode est ensuite validée sur l’atlas postmortem et évaluée sur des données in vivo de sujets sains et de patients avec épilepsie acquises à 7T.
The hippocampus is a gray matter structure in the temporal lobe that plays a key role in memory processes and in many diseases (Alzheimer's disease, epilepsy, depression ...).The development of morphometric models is essential for the study of the functional anatomy and structure alterations associated with different pathologies. The objective of this thesis is to develop and validate methods for morphometry of the hippocampus in two contexts: the study of the external shape of the hippocampus from conventional MRI (1.5T or 3T) with millimeter resolution, and the study of its internal structure from 7T MRI with high spatial resolution. These two settings correspond to the two main parts of the thesis.In the first part, we propose a method for the automatic classification of patients from shape descriptors. This method is based on a spherical harmonic decomposition which is combined with a support vector machine classifier (SVM). The method is evaluated in the context of automatic classification of patients with Alzheimer's disease (AD) patients, mild cognitive impairment (MCI) patients and healthy elderly subjects. It is also compared to other approaches and a more comprehensive validation is available in a population of 509 subjects from the ADNI database. Finally, we present another application of morphometry to study structural alterations associated with the syndrome of Gilles de la Tourette.The second part of the thesis is devoted to the morphometry of the internal structure of the hippocampus from MRI at 7 Tesla. Indeed, the internal structure of the hippocampus is rich and complex but inaccessible to conventional MRI. We first propose an atlas of the internal structure of the hippocampus from postmortem data acquired at 9.4T. Then, we propose to model the Ammon’s horn and the subiculum as a skeleton and a local measure thickness. To do this, we introduce a variational method using original Hilbert spaces reproducing kernels. The method is validated on the postmortem atlas and evaluated on in vivo data from healthy subjects and patients with epilepsy acquired at 7T.
PDF
