Embryo-scale epithelial buckling forms a propagating furrow that initiates gastrulation.

Cell apical constriction driven by actomyosin contraction forces is a conserved mechanism during tissue folding in embryo development. While much is now understood of the molecular mechanism responsible for apical constriction and of the tissue-scale integration of the ensuing in-plane deformations, it is still not clear if apical actomyosin contraction forces are necessary or sufficient per se to drive tissue folding. To tackle this question, we use the Drosophila embryo model system that forms a furrow on the ventral side, initiating mesoderm internalization. Past computational models support the idea that cell apical contraction forces may not be sufficient and that active or passive cell apico-basal forces may be necessary to drive cell wedging leading to tissue furrowing. By using 3D computational modelling and in toto embryo image analysis and manipulation, we now challenge this idea and show that embryo-scale force balance at the tissue surface, rather than cell-autonomous shape changes, is necessary and sufficient to drive a buckling of the epithelial surface forming a furrow which propagates and initiates embryo gastrulation.

A multiscale analysis of early flower development in Arabidopsis provides an integrated view of molecular regulation and growth control.

We have analyzed the link between the gene regulation and growth during the early stages of flower development in Arabidopsis. Starting from time-lapse images, we generated a 4D atlas of early flower development, including cell lineage, cellular growth rates, and the expression patterns of regulatory genes. This information was introduced in MorphoNet, a web-based platform. Using computational models, we found that the literature-based molecular network only explained a minority of the gene expression patterns. This was substantially improved by adding regulatory hypotheses for individual genes. Correlating growth with the combinatorial expression of multiple regulators led to a set of hypotheses for the action of individual genes in morphogenesis. This identified the central factor LEAFY as a potential regulator of heterogeneous growth, which was supported by quantifying growth patterns in a leafy mutant. By providing an integrated view, this atlas should represent a fundamental step toward mechanistic models of flower development.

Contact area-dependent cell communication and the morphological invariance of ascidian embryogenesis.

Marine invertebrate ascidians display embryonic reproducibility: Their early embryonic cell lineages are considered invariant and are conserved between distantly related species, despite rapid genomic divergence. Here, we address the drivers of this reproducibility. We used light-sheet imaging and automated cell segmentation and tracking procedures to systematically quantify the behavior of individual cells every 2 minutes during Phallusia mammillata embryogenesis. Interindividual reproducibility was observed down to the area of individual cell contacts. We found tight links between the reproducibility of embryonic geometries and asymmetric cell divisions, controlled by differential sister cell inductions. We combined modeling and experimental manipulations to show that the area of contact between signaling and responding cells is a key determinant of cell communication. Our work establishes the geometric control of embryonic inductions as an alternative to classical morphogen gradients and suggests that the range of cell signaling sets the scale at which embryonic reproducibility is observed.

A stochastic framework to model axon interactions within growing neuronal populations.

The confined and crowded environment of developing brains imposes spatial constraints on neuronal cells that have evolved individual and collective strategies to optimize their growth. These include organizing neurons into populations extending their axons to common target territories. How individual axons interact with each other within such populations to optimize innervation is currently unclear and difficult to analyze experimentally in vivo. Here, we developed a stochastic model of 3D axon growth that takes into account spatial environmental constraints, physical interactions between neighboring axons, and branch formation. This general, predictive and robust model, when fed with parameters estimated on real neurons from the Drosophila brain, enabled the study of the mechanistic principles underlying the growth of axonal populations. First, it provided a novel explanation for the diversity of growth and branching patterns observed in vivo within populations of genetically identical neurons. Second, it uncovered that axon branching could be a strategy optimizing the overall growth of axons competing with others in contexts of high axonal density. The flexibility of this framework will make it possible to investigate the rules underlying axon growth and regeneration in the context of various neuronal populations.

In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level.

The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource. VIDEO ABSTRACT.

Planar cell polarity genes frizzled4 and frizzled6 exert patterning influence on arterial vessel morphogenesis.

Quantitative analysis of the vascular network anatomy is critical for the understanding of the vasculature structure and function. In this study, we have combined microcomputed tomography (microCT) and computational analysis to provide quantitative three-dimensional geometrical and topological characterization of the normal kidney vasculature, and to investigate how 2 core genes of the Wnt/planar cell polarity, Frizzled4 and Frizzled6, affect vascular network morphogenesis. Experiments were performed on frizzled4 (Fzd4-/-) and frizzled6 (Fzd6-/-) deleted mice and littermate controls (WT) perfused with a contrast medium after euthanasia and exsanguination. The kidneys were scanned with a high-resolution (16 µm) microCT imaging system, followed by 3D reconstruction of the arterial vasculature. Computational treatment includes decomposition of 3D networks based on Diameter-Defined Strahler Order (DDSO). We have calculated quantitative (i) Global scale parameters, such as the volume of the vasculature and its fractal dimension (ii) Structural parameters depending on the DDSO hierarchical levels such as hierarchical ordering, diameter, length and branching angles of the vessel segments, and (iii) Functional parameters such as estimated resistance to blood flow alongside the vascular tree and average density of terminal arterioles. In normal kidneys, fractal dimension was 2.07±0.11 (n = 7), and was significantly lower in Fzd4-/- (1.71±0.04; n = 4), and Fzd6-/- (1.54±0.09; n = 3) kidneys. The DDSO number was 5 in WT and Fzd4-/-, and only 4 in Fzd6-/-. Scaling characteristics such as diameter and length of vessel segments were altered in mutants, whereas bifurcation angles were not different from WT. Fzd4 and Fzd6 deletion increased vessel resistance, calculated using the Hagen-Poiseuille equation, for each DDSO, and decreased the density and the homogeneity of the distal vessel segments. Our results show that our methodology is suitable for 3D quantitative characterization of vascular networks, and that Fzd4 and Fzd6 genes have a deep patterning effect on arterial vessel morphogenesis that may determine its functional efficiency.

Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software.

INTRODUCTION: Statistical parametric mapping (SPM) provides useful voxel-by-voxel analyses of brain images from (18)F-fluorodesoxyglucose positron emission tomography (FDG-PET) after an initial step of spatial normalization through an anatomical template model. In the setting of the preoperative workup of patients with temporal epilepsy, this study aimed at assessing a block-matching (BM) normalization method, where most transformations are computed through small blocks, a principle that minimizes artefacts and overcomes additional image-filtering. METHODS: Brain FDG-PET images from 31 patients with well-characterised temporal lobe epilepsy and among whom 22 had common mesial temporal lobe epilepsy were retrospectively analysed using both BM and conventional SPM normalization methods and with PET images from age-adjusted controls. Different threshold p values corrected for cluster volume were considered (0.01, 0.005, and 0.001). RESULTS: The use of BM provided equivalent values to those of SPM with regard to the overall volumes of temporal and extra-temporal hypometabolism, as well as similar sensitivity for detecting the involved temporal lobe, reaching 87 and 94 % for SPM and BM, respectively, at a threshold p value of 0.01. However, the ability to more accurately localize brain lesions within the mesial portion of the temporal lobe was a little higher with BM than with SPM with respective sensitivities reaching 78 % for BM and 45 % for SPM (p < 0.05). CONCLUSIONS: BM normalization compares well with conventional SPM for the voxel-based quantitative analysis of the FDG-PET images from temporal epilepsy patients. Further studies in different population are needed to determine whether BM is truly an accurate alternative to SPM in this setting.

Age-related changes in FDG brain uptake are more accurately assessed when applying an adaptive template to the SPM method of voxel-based quantitative analysis.

INTRODUCTION: The impact of age is crucial and must be taken into account when applying a voxel-based quantitative analysis on brain images from [¹8F]-fluorodeoxyglucose Positron Emission Tomography (FDG-PET). This study aimed to determine whether age-related changes in brain FDG-PET images are more accurately assessed when the conventional statistical parametric mapping (SPM) normalization method is used with an adaptive template, obtained from analysed PET images using a Block-Matching (BM) algorithm to fit with the characteristics of these images. METHODS: Age-related changes in FDG-PET images were computed with linear models in 84 neurologically healthy subjects (35 women, 19 to 82-year-old), and compared between results provided by the SPM normalization algorithm applied on its dedicated conventional template or on the adaptive BM template. A threshold P value of 0.05 was used together with a family-wise error correction. RESULTS: The age-related changes in FDG-PET images were much more apparent when computed with the adaptive template than with the conventional template as evidenced by: (1) stronger correlation coefficients with age for the overall frontal and temporal uptake values (respective R² values of 0.20 and 0.07) and (2) larger extents of involved areas (13 and 5% of whole brain template volume, respectively), leading to reveal several age-dependent areas (especially in dorsolateral prefrontal, inferior temporal/fusiform and primary somatosensory cortices). CONCLUSION: Age-related changes in brain FDG uptake may be more accurately determined when applying the SPM method of voxel-based quantitative analysis on a template that best fits the characteristics of the analysed TEP images.

A tree-topology preserving pairing for 3D/2D registration.

PURPOSE: Fusing preoperative and intra-operative information into a single space aims at taking advantage of two complementary modalities and necessitates a step of registration that must provide good alignment and relevant correspondences. This paper addresses both purposes in the case of 3D/2D vessel tree matching. METHOD: We propose a registration algorithm endorsing this vascular tree nature by providing a pairing procedure that preserves the tree topology and by integrating this pairing into an iterative algorithm maintaining pairing coherence. In addition, we define two complementary error measures quantifying the resulting alignment error and pairing error, and both are based on manual ground-truth that is independent of the type of transformation to retrieve. RESULTS: Experiments were conducted on a database of 63 clinical cases, evaluating robustness and accuracy of our approach with respect to the iterative closest point algorithm. CONCLUSION: The proposed method exhibits good results in terms of both pairing and alignment as well as low sensitivity to rotations to be compensated (up to 30°).

Assessing the ability of the 2D Fisher-KPP equation to model cell-sheet wound closure.

We address in this paper the ability of the Fisher-KPP equations to render some of the dynamical features of epithelial cell-sheets during wound closure. Our approach is based on nonlinear parameter identification, in a two-dimensional setting, and using advanced 2D image processing of the video acquired sequences. As original contribution, we lead a detailed study of the profiles of the classically used cost functions, and we address the "wound constant speed" assumption, showing that it should be handled with care. We study five MDCK cell monolayer assays in a reference, activated and inhibited migration conditions. Modulo the inherent variability of biological assays, we show that in the assay where migration is not exogeneously activated or inhibited, the wound velocity is constant. The Fisher-KPP equation is able to accurately predict, until the final closure of the wound, the evolution of the wound area, the mean velocity of the cell front, and the time at which the closure occurred. We also show that for activated as well as for inhibited migration assays, many of the cell-sheet dynamics cannot be well captured by the Fisher-KPP model. Finally, we draw some conclusions related to the identified model parameters, and possible utilization of the model.

The HV3 Score: A New Simple Tool to Suspect Cognitive Impairment in Multiple Sclerosis in Clinical Practice.

INTRODUCTION: Cognitive impairment in multiple sclerosis (MS) is common even in the early stages of the disease. Our objective was to improve early detection of cognitive impairment in MS. METHODS: Seventy-five patients with relapsing remitting (RR) MS and 20 controls were enrolled. Two RRMS groups were defined according to their results at the Paced Auditory Serial Addition Test (PASAT). Patients with a z score below two standard deviations were considered impaired. We quantified T2 and T1 lesion volumes, and cerebral white and grey matter volumes on a conventional brain magnetic resonance imaging (MRI) scan. Global brain atrophy was evaluated using the third ventricle (V3) width (in mm). An average brain model was built based on controls and compared with the patient's MRI to quantify regional volumetric changes. RESULTS: Sixteen (21.3%) patients with RRMS had low PASAT performance. They had a higher Expanded Disability Status Scale (EDSS) score (P = 0.019). T2 and T1 lesion volumes, and grey and white matter volumes were the same in both groups. An enlargement of the V3 width was observed in the low performer group (P = 0.044) and V3 width was correlated with the PASAT score (r = -0.271; P = 0.021). A composite score, named HV3, was obtained by adding the EDSS and V3 width (in mm) and correlated with the PASAT (r = -0.325; P = 0.006). A cutoff HV3 score of over 5.5 identified patients with low PASAT performance, with a positive predictive value of 92.5% and an accuracy of 70.1%. Focal atrophy was detected in the supplementary motor area, the cingulate gyrus, the right thalamus, and the inferior parietal lobules of patients with lower PASAT performance. CONCLUSION: Specific brain morphological changes, including an enlargement of the V3 width, are associated with low PASAT performance in patients with RRMS. The HV3 score is an additional and complementary tool, accessible in clinical practice, to suspect easily cognitive impairment in patients with RRMS and to better identify patients requiring a complete cognitive assessment.

Iterative closest curve: a framework for curvilinear structure registration application to 2D/3D coronary arteries registration.

Treatment coronary arteries endovascular involves catheter navigation through patient vasculature. The projective angiography guidance is limited in the case of chronic total occlusion where occluded vessel can not be seen. Integrating standard preoperative CT angiography information with live fluoroscopic images addresses this limitation but requires alignment of both modalities. This article proposes a structure-based registration method that intrinsically preserves both the geometrical and topological coherencies of the vascular centrelines to be registered, by the means of a dedicated curve-to-curve distance pairs of closest curves are identified, while pairing their points. Preliminary experiments demonstrate that the proposed approach performs better than the standard Iterative Closest Point method giving a wider attraction basin and improved accuracy.

Voxel-based quantitative analysis of brain images from ¹8F-FDG PET with a block-matching algorithm for spatial normalization.

OBJECTIVE: Statistical Parametric Mapping (SPM) is widely used for the quantitative analysis of brain images from ¹8F fluorodeoxyglucose positron emission tomography (FDG PET). SPM requires an initial step of spatial normalization to align all images to a standard anatomic model (the template), but this may lead to image distortion and artifacts, especially in cases of marked brain abnormalities. This study aimed at assessing a block-matching (BM) normalization algorithm, where most transformations are not directly computed on the overall brain volume but through small blocks, a principle that is likely to minimize artifacts. METHODS: Large and/or small hypometabolic areas were artificially simulated in initially normal FDG PET images to compare the results provided by statistical tests computed after either SPM or BM normalization. RESULTS: Results were enhanced by BM, compared with SPM, with regard to (i) errors in the estimation of large defects volumes (about 2-fold lower) because of a lower image distortion, and (ii) rates of false-positive foci when numerous or extended abnormalities were simulated. These observations were strengthened by analyses of FDG PET examinations from epileptic patients. CONCLUSIONS: Results obtained with the BM normalization of brain FDG PET appear more precise and robust than with SPM normalization, especially in cases of numerous or extended abnormalities.

Dentalmaps: automatic dental delineation for radiotherapy planning in head-and-neck cancer.

PURPOSE: To propose an automatic atlas-based segmentation framework of the dental structures, called Dentalmaps, and to assess its accuracy and relevance to guide dental care in the context of intensity-modulated radiotherapy. METHODS AND MATERIALS: A multi-atlas-based segmentation, less sensitive to artifacts than previously published head-and-neck segmentation methods, was used. The manual segmentations of a 21-patient database were first deformed onto the query using nonlinear registrations with the training images and then fused to estimate the consensus segmentation of the query. RESULTS: The framework was evaluated with a leave-one-out protocol. The maximum doses estimated using manual contours were considered as ground truth and compared with the maximum doses estimated using automatic contours. The dose estimation error was within 2-Gy accuracy in 75% of cases (with a median of 0.9 Gy), whereas it was within 2-Gy accuracy in 30% of cases only with the visual estimation method without any contour, which is the routine practice procedure. CONCLUSIONS: Dose estimates using this framework were more accurate than visual estimates without dental contour. Dentalmaps represents a useful documentation and communication tool between radiation oncologists and dentists in routine practice. Prospective multicenter assessment is underway on patients extrinsic to the database.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

[Towards a personalized digital patient for diagnosis and therapy guided by image]. / Vers un patient numérique personnalisé pour le diagnostic et la thérapie guidés par l'image - Représentation en sciences du vivant (5).

Recent advances in computer science and medical imaging allow the design of new computational models of the patient which are used to assist physicians. These models, whose parameters are optimized to fit in vivo acquired images, from cells to an entire body, are designed to better quantify the observations (computer aided diagnosis), to simulate the evolution of a pathology (computer aided prognosis), to plan and simulate an intervention to optimize its effects (computer aided therapy), therefore addressing some of the major challenges of medicine of 21(st) century.

Construction of patient specific atlases from locally most similar anatomical pieces.

Radiotherapy planning requires accurate delineations of the critical structures. To avoid manual contouring, atlas-based segmentation can be used to get automatic delineations. However, the results strongly depend on the chosen atlas, especially for the head and neck region where the anatomical variability is high. To address this problem, atlases adapted to the patient's anatomy may allow for a better registration, and already showed an improvement in segmentation accuracy. However, building such atlases requires the definition of a criterion to select among a database the images that are the most similar to the patient. Moreover, the inter-expert variability of manual contouring may be high, and therefore bias the segmentation if selecting only one image for each region. To tackle these issues, we present an original method to design a piecewise most similar atlas. Given a query image, we propose an efficient criterion to select for each anatomical region the K most similar images among a database by considering local volume variations possibly induced by the tumor. Then, we present a new approach to combine the K images selected for each region into a piecewise most similar template. Our results obtained with 105 CT images of the head and neck show that our method reduces the over-segmentation seen with an average atlas while being robust to inter-expert manual segmentation variability.

Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution.

Quantitative information on growing organs is required to better understand morphogenesis in both plants and animals. However, detailed analyses of growth patterns at cellular resolution have remained elusive. We developed an approach, multiangle image acquisition, three-dimensional reconstruction and cell segmentation-automated lineage tracking (MARS-ALT), in which we imaged whole organs from multiple angles, computationally merged and segmented these images to provide accurate cell identification in three dimensions and automatically tracked cell lineages through multiple rounds of cell division during development. Using these methods, we quantitatively analyzed Arabidopsis thaliana flower development at cell resolution, which revealed differential growth patterns of key regions during early stages of floral morphogenesis. Lastly, using rice roots, we demonstrated that this approach is both generic and scalable.

Grid-wide neuroimaging data federation in the context of the NeuroLOG project.

Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply superseded by grid services. This paper describes the NeuroLOG platform design and implementation, shedding light on its Data Management Layer. It addresses the integration of brain image files, associated relational metadata and neuroscience semantic data in a heterogeneous distributed environment, integrating legacy data managers through a mediation layer.

A pre-clinical assessment of an atlas-based automatic segmentation tool for the head and neck.

BACKGROUND AND PURPOSE: Accurate conformal radiotherapy treatment requires manual delineation of target volumes and organs at risk (OAR) that is both time-consuming and subject to large inter-user variability. One solution is atlas-based automatic segmentation (ABAS) where a priori information is used to delineate various organs of interest. The aim of the present study is to establish the accuracy of one such tool for the head and neck (H&N) using two different evaluation methods. MATERIALS AND METHODS: Two radiotherapy centres were provided with an ABAS tool that was used to outline the brainstem, parotids and mandible on several patients. The results were compared to manual delineations for the first centre (EM1) and reviewed/edited for the second centre (EM2), both of which were deemed as equally valid gold standards. The contours were compared in terms of their volume, sensitivity and specificity with the results being interpreted using the Dice similarity coefficient and a receiver operator characteristic (ROC) curve. RESULTS: Automatic segmentation took typically approximately 7min for each patient on a standard PC. The results indicated that the atlas contour volume was generally within +/-1SD of each gold standard apart from the parotids for EM1 and brainstem for EM2 that were over- and under-estimated, respectively (within +/-2SD). The similarity of the atlas contours with their respective gold standard was satisfactory with an average Dice coefficient for all OAR of 0.68+/-0.25 for EM1 and 0.82+/-0.13 for EM2. All data had satisfactory sensitivity and specificity resulting in a favourable position in ROC space. CONCLUSIONS: These tests have shown that the ABAS tool exhibits satisfactory sensitivity and specificity for the OAR investigated. There is, however, a systematic over-segmentation of the parotids (EM1) and under-segmentation of the brainstem (EM2) that require careful review and editing in the majority of cases. Such issues have been discussed with the software manufacturer and a revised version is due for release.