Sift-based sequence registration and flow-based cortical vessel segmentation applied to high resolution optical imaging data

International audienceSeveral functional and biomedical imaging techniques rely on determining hemodynamic variables and their changes in large vascular networks. To do so at micro-vascular resolution requires taking into account the - usually small but often non-rigid - mechanical deformations of the imaged vasculature induced by the cardiac pulsation and/or the subjects'body movements. Here, we present two new algorithmic approaches, allowing (i) to efficiently and accurately co-register large sets of such images in a non-rigid manner using Scale-Invariant Feature Transform (SIFT) keypoints, and (ii) to extract blood vessels and their diameters based on blood-flow information using a fast marching algorithm. These methods were applied to optical imaging data of intrinsic signals from awake monkey visual cortex at high spatiotemporal resolution (30μm, 5ms). The movement of red blood cells in the sequences could be enhanced by a Beer-Lambert-based image preprocessing. Our SIFT-based registration could be directly compared to a rigid registration, whereas the vessel extraction algorithm was tested by verifying flow conservation in vascular branching points. Finally, both methods together proved to improve a lot the estimation of the blood velocity in the vessels

Parameter estimation efficiency using nonlinear models in fMRI

There is an increasing interest in using physiologically plausible models in fMRI analysis. These models do raise new mathematical problems in terms of parameters estimation and interpretation of the measured data. We present some theoretical contributions in this area, using different variations of the Balloon Model (Buxton98,Friston00,Buxton04) as example models. We propose 1) a method to analyze the models dynamics and their stability around equilibrium, 2) a new way to derive least square energy gradient for parameter estimation, 3) a quantitative measurement of parameter estimation efficiency, and 4) a statistical test for detecting voxel activations. We use these methods in a visual perception checker-board experiment. It appears that the different hemodynamic models considered better capture some features of the response than linear models. In particular, they account for small nonlinearities observed for stimulation durations between 1 and 8 seconds. Nonlinearities for stimulation shorter than one second can also be explained by a neural habituation model (Buxton04), but further investigations should assess whether they are rather not due to nonlinear effects of the flow response. Moreover, the tools we have developed prove that statistical methods that work well for the GLM can be nicely adapted to nonlinear models. The activation maps obtained in both frameworks are comparable

Cerebral blood flow recorded at high sensitivity in two dimensions using high resolution optical imaging

Knowledge about sensory-evoked blood-flow changes is essential for constraining hemodynamic response models used to interpret functional brain imaging signals, such as fMRI. Here, we extracted 2-dimensional blood-flow and its temporal modulations from high-resolution optical imaging data in the awake monkey. Optical imaging allows to track moving erythrocytes (or small clusters thereof), thus providing, albeit noisy, information about their velocity in individual blood vessels, across the whole imaged area. Here, we illustrate the algorithms that allowed us to extract, at the single micro-vessel level, red blood cell (RBC) motion information from the noisy optical signals. For this purpose, we developed an algorithm that is both robust and computationally efficient, using the structure tensor, known to detect an average direction of image intensity gradient. This structure tensor tool is applied to detect trajectory directions in the spatio-temporal data. Since blood-flow modulation by the cardiac pulsation was clearly detected, our method should be applicable also to study blood-flow modulations by neuronal activity, and their spatio-temporal patterns

Morpho-chemistry in secondary sludge filtration cakes: a case study

International audienceLight Microscopy, Transmission Electron Microscopy (TEM, EDXS), and Fourier Transform Infra Red MicroSpectroscopy (FTIRMS) were used to describe the organization and chemical distribution of major constituents in a sludge filtration cake. Samples were obtained from a municipal wastewater treatment plant using conventional ferric chloride and lime sludge conditioning.Various samples collected at different stages of the process were embedded in an Epoxy resin after acetone-dehydration, and sectioned using an ultra-microtome. The thickness of the sections was adapted to the experimental techniques used. TEM showed that in the activated sludge, bacterial colonies, isolated bacteria and debris are trapped within a gel matrix of exocellular polymeric substances, whereas those same components are compacted and distorted in the filtration cake. Furthermore, conditioning chemicals appeared in the cake as amorphous aggregated colloids and acicular particles which do not form inside the colonies. A chemical mapping was obtained by determining and integrating FTIR bands characteristics of specific components of the cake. Preliminary results showed that the amounts of resin can be used to assess the relative compacity at different levels of the cake

Epidemiological analysis of peripartum hysterectomy across nine European countries

Introduction Peripartum hysterectomy is a surgical procedure performed for severe obstetric complications such as major obstetric hemorrhage. The prevalence of peripartum hysterectomy in high-resource settings is relatively low. Hence, international comparisons and studying indications and associations with mode of birth rely on the use of national obstetric survey data. Objectives were to calculate the prevalence and indications of peripartum hysterectomy and its association with national cesarean section rates and mode of birth in nine European countries. Material and methods We performed a descriptive, multinational, population-based study among women who underwent peripartum hysterectomy. Data were collected from national or multiregional databases from nine countries participating in the International Network of Obstetric Survey Systems. We included hysterectomies performed from 22 gestational weeks up to 48 hours postpartum for obstetric hemorrhage, as this was the most restrictive, overlapping case definition between all countries. Main outcomes were prevalence and indications of peripartum hysterectomy. Additionally, we compared prevalence of peripartum hysterectomy between women giving birth vaginally and by cesarean section, and between women giving birth with and without previous cesarean section. Finally, we calculated correlation between prevalence of peripartum hysterectomy and national cesarean section rates, as well as national rates of women giving birth after a previous cesarean section. Results A total of 1302 peripartum hysterectomies were performed in 2 498 013 births, leading to a prevalence of 5.2 per 10 000 births ranging from 2.6 in Denmark to 10.7 in Italy. Main indications were uterine atony (35.3%) and abnormally invasive placenta (34.8%). Relative risk of hysterectomy after cesarean section compared with vaginal birth was 9.1 (95% CI 8.0-10.4). Relative risk for hysterectomy for birth after previous cesarean section compared with birth without previous cesarean section was 10.6 (95% CI 9.4-12.1). A strong correlation was observed between national cesarean section rate and prevalence of peripartum hysterectomy (rho = 0.67, P < .05). Conclusions Prevalence of peripartum hysterectomy may vary considerably between high-income countries. Uterine atony and abnormally invasive placenta are the commonest indications for hysterectomy. Birth by cesarean section and birth after previous cesarean section are associated with nine-fold increased risk of peripartum hysterectomy

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience

Authors' reply re: Wide differences in mode of delivery within Europe: risk-stratified analyses of aggregated routine data from the Euro-Peristat study

To access publisher's full text version of this article click on the hyperlink at the bottom of the pageTo use data from routine sources to compare rates of obstetric intervention in Europe both overall and for subgroups at higher risk of intervention.Retrospective analysis of aggregated routine data.Thirty-one European countries or regions contributing data on mode of delivery to the Euro-Peristat project.Births in participating countries in 2010.Countries provided aggregated data about overall rates of obstetric intervention and about caesarean section rates for specified subgroups.Mode of delivery.Rates of caesarean section ranged from 14.8% to 52.2% of all births and rates of instrumental vaginal delivery ranged from 0.5% to 16.4%. Overall, there was no association between rates of instrumental vaginal delivery and rates of caesarean section, but similarities were observed between some countries that are geographically close and may share common traditions of practice. Associations were observed between caesarean section rates for women with breech and vertex births and with singleton and multiple births but patterns of association for women who had and had not had previous caesarean sections were more complex.The persisting wide variations in caesarean section and instrumental vaginal delivery rates point to a lack of consensus about practice and raise questions for further investigation. Further research is needed to explore the impact of differences in clinical guidelines, healthcare systems and their financing and parents' and professionals' attitudes to care at delivery.info:eu-repo/grantAgreement/EC/FP7/2010130

Modèles Hémodynamiques: Investigation et Application à l'Analyse en Imagerie Cérébrale

An accurate analysis of functional MRI measurements requires a precise understanding of the physiological processes involved in this measure. This PhD work shows both investigations in hemodynamic models and algorithms to use such models in the analysis of brain imaging measurements. A particular concern with functional MRI is the temporal modeling of the responses to neural activity. Today, the most standard analysis methods use the General Linear Model framework, which supposes a linear relationship between brain activity and the BOLD response. We show how it is possible alternatively to use nonlinear models in data analysis. Our estimation of parameters by energy minimization is the equivalent to linear regression, and our adaptation of the Fisher statistical test enables activation detection, hypothesis testing, and eventually comparison between different models. We then have extended our methods to the analysis of multiple modalities data, and in particular, proposed a method to estimate the cortical activity underlying simultaneous fMRI and EEG measurements. We were able to achieve accurate estimation on synthetic data. Additionally to these methodological researches, we have investigated the model equations with an Optical Imaging experiment. We have focused on the dynamic of the blood flow, which is at a crossroad between electrical, metabolism and oxygenation processes. We have identified specific questioning facts about this dynamic, such as nonlinearity with respect to electrical synaptic activity, and delays with respect to the blood volume response. Furthermore, we have conceived a new method for estimating fast erythrocyte motions in the blood from intrinsic optical imaging signal, which might provide a new useful measurement of this blood flow. In the following synopsis, we summarize the main features of this PhD work, through highlighting the purposes, methods, conclusions and implications of each chapter. Also, we tried to present an objective criticism of this work, through mentioning both its original contributions and its weaknesses. We hope that this summary will help the reader to rapidly navigate through the thesis, while understanding the relations between its different components.L'enjeu de la présente thèse est de proposer de nouvelles méthodes d'analyse des données d'imagerie cérébrale acquises en Imagerie par Résonance Magnétique fonctionnelle (IRMf). Elle s'est concentrée en particulier sur la compréhension des signaux temporels mesurés en IRMf et leur lien avec l'activité cérébrale. En effet, les variations du signal que l'on observe en IRMf sont dues à des changements de l'afflux du sang dans le cerveau et de l'oxygénation de ce sang. Ces changements sont liés à l'activité des neurones, et l'on nomme ce phénomène la réponse hémodynamique. Cette réponse hémodynamique fait l'objet d'un important effort de modélisation, de manière à mieux pouvoir interpréter les données d'IRMf. Et cette thèse contient des travaux liés à la fois à la modélisation pour elle-même, avec l'étude de certains détails des modèles hémodynamiques, et à la fois à l'utilisation de ces modèles pour l'analyse des données, avec en particulier l'analyse des données IRMf et la fusion entre des données d'IRMf et d'Electroencéphalographie (EEG). Ainsi, la première partie de la thèse est consacrée à l'utilisation de modèles hémodynamiques en IRMf. En effet, aujourd'hui, les méthodes standard d'analyse de données d'IRM fonctionnelle utilisent le Modèle Général Linéaire (GLM), qui suppose une relation linéaire entre l'activité des neurones, la réponse hémodynamique et les mesures IRMf. Nous montrons qu'il est aussi possible d'utiliser des modèles plus plausible du point de vue biologique, et éventuellement non-linéaires pour analyser les données. A la place de la régression linéaire utilisée habituellement, nous proposons une identification de modèle basées sur une minimisation d'énergie, et nous proposons d'adapter les tests de Fisher utilisés habituellement dans le cadre du GLM pour pouvoir réaliser dans le nouveau cadre la détection d'activations, le test d'hypothèses cognitives, ainsi que des comparaisons entre différents modèles. La seconde partie quant à elle est expérimentale: nous avons étudié les équations de différents modèles hémodynamiques grâce à des expérience d'Imagerie Optique chez le singe éveillé, dans le cadre d'une collaboration avec Ivo Vanzetta dans l'équipe "Dynamique de la perception visuelle et de l'action'' au CNRS Marseille. Nous nous sommes intéressés en particulier à la dynamique du flux sanguin, qui est de première importance car elle fait le lien entre les activités électriques et métaboliques et les changements du volume et de l'oxygénation du sang. Nous avons mis en évidence des aspects de la réponse hémodynamique qui ne sont pas prévus par les modèles actuels, tels qu'une non-linéarité de cette réponse du flux par rapport à l'intensité de la réponse électrique. Par ailleurs, dans le cadre de la même collaboration, nous avons conçu une méthode pour estimer la vitesse des globules rouges dans les vaisseaux sanguins filmés en Imagerie Optique, qui constitue une nouvelle technique de mesure de ce flux sanguin. Enfin, dans la troisième partie, nous avons étendu les méthodes présentées dans la première partie à l'analyse de données de modalités multiple, et en particulier, proposons une méthode pour estimer l'activité cérébrale à partir d'enregistrement simultanés en IRMf et en EEG. Cette méthode est validée sur des données synthétiques. Le présent synopsis résume les points importants de ces travaux: les objectifs, les méthodes, les conclusions et conséquences pour chaque chapitre. Nous avons également tenté d'en présenter une critique objective, en mentionnant à la fois ce qui constitue des contributions originales et les faiblesses restantes. Nous espérons que ce résumé permettra au lecteur de se repérer rapidement dans cette thèse, et de bien comprendre les relations entre ses différentes composantes