Mapping the human connectome at multiple scales with diffusion spectrum MRI.

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

Towards a diffusion image processing validation and accuracy prediction framework

Validation is the main bottleneck preventing theadoption of many medical image processing algorithms inthe clinical practice. In the classical approach,a-posteriori analysis is performed based on someobjective metrics. In this work, a different approachbased on Petri Nets (PN) is proposed. The basic ideaconsists in predicting the accuracy that will result froma given processing based on the characterization of thesources of inaccuracy of the system. Here we propose aproof of concept in the scenario of a diffusion imaginganalysis pipeline. A PN is built after the detection ofthe possible sources of inaccuracy. By integrating thefirst qualitative insights based on the PN withquantitative measures, it is possible to optimize the PNitself, to predict the inaccuracy of the system in adifferent setting. Results show that the proposed modelprovides a good prediction performance and suggests theoptimal processing approach.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Long-term monitoring of post-stroke plasticity after transient cerebral ischemia in mice using in vivo and ex vivo diffusion tensor MRI.

WE USED A MURINE MODEL OF TRANSIENT FOCAL CEREBRAL ISCHEMIA TO STUDY: 1) in vivo DTI long-term temporal evolution of the apparent diffusion coefficient (ADC) and diffusion fractional anisotropy (FA) at days 4, 10, 15 and 21 after stroke 2) ex vivo distribution of a plasticity-related protein (GAP-43) and its relationship with the ex vivo DTI characteristics of the striato-thalamic pathway (21 days). All animals recovered motor function. In vivo ADC within the infarct was significantly increased after stroke. In the stroke group, GAP-43 expression and FA values were significantly higher in the ipsilateral (IL) striatum and contralateral (CL) hippocampus compared to the shams. DTI tractography showed fiber trajectories connecting the CL striatum to the stroke region, where increased GAP43 and FA were observed and fiber tracts from the CL striatum terminating in the IL hippocampus.Our data demonstrate that DTI changes parallel histological remodeling and recovery of function.

Mechanisms underlying functional recovery after in vivo focal cerebral ischemia : from preconditioning to diffusion MRI

Version abregée L'ischémie cérébrale est la troisième cause de mort dans les pays développés, et la maladie responsable des plus sérieux handicaps neurologiques. La compréhension des bases moléculaires et anatomiques de la récupération fonctionnelle après l'ischémie cérébrale est donc extrêmement importante et représente un domaine d'intérêt crucial pour la recherche fondamentale et clinique. Durant les deux dernières décennies, les chercheurs ont tenté de combattre les effets nocifs de l'ischémie cérébrale à l'aide de substances exogènes qui, bien que testées avec succès dans le domaine expérimental, ont montré un effet contradictoire dans l'application clinique. Une approche différente mais complémentaire est de stimuler des mécanismes intrinsèques de neuroprotection en utilisant le «modèle de préconditionnement» : une brève insulte protège contre des épisodes d'ischémie plus sévères à travers la stimulation de voies de signalisation endogènes qui augmentent la résistance à l'ischémie. Cette approche peut offrir des éléments importants pour clarifier les mécanismes endogènes de neuroprotection et fournir de nouvelles stratégies pour rendre les neurones et la glie plus résistants à l'attaque ischémique cérébrale. Dans un premier temps, nous avons donc étudié les mécanismes de neuroprotection intrinsèques stimulés par la thrombine, un neuroprotecteur «préconditionnant» dont on a montré, à l'aide de modèles expérimentaux in vitro et in vivo, qu'il réduit la mort neuronale. En appliquant une technique de microchirurgie pour induire une ischémie cérébrale transitoire chez la souris, nous avons montré que la thrombine peut stimuler les voies de signalisation intracellulaire médiées par MAPK et JNK par une approche moléculaire et l'analyse in vivo d'un inhibiteur spécifique de JNK (L JNK) .Nous avons également étudié l'impact de la thrombine sur la récupération fonctionnelle après une attaque et avons pu démontrer que ces mécanismes moléculaires peuvent améliorer la récupération motrice. La deuxième partie de cette étude des mécanismes de récupération après ischémie cérébrale est basée sur l'investigation des bases anatomiques de la plasticité des connections cérébrales, soit dans le modèle animal d'ischémie transitoire, soit chez l'homme. Selon des résultats précédemment publiés par divers groupes ,nous savons que des mécanismes de plasticité aboutissant à des degrés divers de récupération fonctionnelle sont mis enjeu après une lésion ischémique. Le résultat de cette réorganisation est une nouvelle architecture fonctionnelle et structurelle, qui varie individuellement selon l'anatomie de la lésion, l'âge du sujet et la chronicité de la lésion. Le succès de toute intervention thérapeutique dépendra donc de son interaction avec la nouvelle architecture anatomique. Pour cette raison, nous avons appliqué deux techniques de diffusion en résonance magnétique qui permettent de détecter les changements de microstructure cérébrale et de connexions anatomiques suite à une attaque : IRM par tenseur de diffusion (DT-IR1V) et IRM par spectre de diffusion (DSIRM). Grâce à la DT-IRM hautement sophistiquée, nous avons pu effectuer une étude de follow-up à long terme chez des souris ayant subi une ischémie cérébrale transitoire, qui a mis en évidence que les changements microstructurels dans l'infarctus ainsi que la modification des voies anatomiques sont corrélés à la récupération fonctionnelle. De plus, nous avons observé une réorganisation axonale dans des aires où l'on détecte une augmentation d'expression d'une protéine de plasticité exprimée dans le cône de croissance des axones (GAP-43). En appliquant la même technique, nous avons également effectué deux études, rétrospective et prospective, qui ont montré comment des paramètres obtenus avec DT-IRM peuvent monitorer la rapidité de récupération et mettre en évidence un changement structurel dans les voies impliquées dans les manifestations cliniques. Dans la dernière partie de ce travail, nous avons décrit la manière dont la DS-IRM peut être appliquée dans le domaine expérimental et clinique pour étudier la plasticité cérébrale après ischémie. Abstract Ischemic stroke is the third leading cause of death in developed countries and the disease responsible for the most serious long-term neurological disability. Understanding molecular and anatomical basis of stroke recovery is, therefore, extremely important and represents a major field of interest for basic and clinical research. Over the past 2 decades, much attention has focused on counteracting noxious effect of the ischemic insult with exogenous substances (oxygen radical scavengers, AMPA and NMDA receptor antagonists, MMP inhibitors etc) which were successfully tested in the experimental field -but which turned out to have controversial effects in clinical trials. A different but complementary approach to address ischemia pathophysiology and treatment options is to stimulate and investigate intrinsic mechanisms of neuroprotection using the "preconditioning effect": applying a brief insult protects against subsequent prolonged and detrimental ischemic episodes, by up-regulating powerful endogenous pathways that increase resistance to injury. We believe that this approach might offer an important insight into the molecular mechanisms responsible for endogenous neuroprotection. In addition, results from preconditioning model experiment may provide new strategies for making brain cells "naturally" more resistant to ischemic injury and accelerate their rate of functional recovery. In the first part of this work, we investigated down-stream mechanisms of neuroprotection induced by thrombin, a well known neuroprotectant which has been demonstrated to reduce stroke-induced cell death in vitro and in vivo experimental models. Using microsurgery to induce transient brain ischemia in mice, we showed that thrombin can stimulate both MAPK and JNK intracellular pathways through a molecular biology approach and an in vivo analysis of a specific kinase inhibitor (L JNK1). We also studied thrombin's impact on functional recovery demonstrating that these molecular mechanisms could enhance post-stroke motor outcome. The second part of this study is based on investigating the anatomical basis underlying connectivity remodeling, leading to functional improvement after stroke. To do this, we used both a mouse model of experimental ischemia and human subjects with stroke. It is known from previous data published in literature, that the brain adapts to damage in a way that attempts to preserve motor function. The result of this reorganization is a new functional and structural architecture, which will vary from patient to patient depending on the anatomy of the damage, the biological age of the patient and the chronicity of the lesion. The success of any given therapeutic intervention will depend on how well it interacts with this new architecture. For this reason, we applied diffusion magnetic resonance techniques able to detect micro-structural and connectivity changes following an ischemic lesion: diffusion tensor MRI (DT-MRI) and diffusion spectrum MRI (DS-MRI). Using DT-MRI, we performed along-term follow up study of stroke mice which showed how diffusion changes in the stroke region and fiber tract remodeling is correlating with stroke recovery. In addition, axonal reorganization is shown in areas of increased plasticity related protein expression (GAP 43, growth axonal cone related protein). Applying the same technique, we then performed a retrospective and a prospective study in humans demonstrating how specific DTI parameters could help to monitor the speed of recovery and show longitudinal changes in damaged tracts involved in clinical symptoms. Finally, in the last part of this study we showed how DS-MRI could be applied both to experimental and human stroke and which perspectives it can open to further investigate post stroke plasticity.

An active strain electromechanical model for cardiac tissue

We propose a finite element approximation of a system of partial differential equations describing the coupling between the propagation of electrical potential and large deformations of the cardiac tissue. The underlying mathematical model is based on the active strain assumption, in which it is assumed that a multiplicative decomposition of the deformation tensor into a passive and active part holds, the latter carrying the information of the electrical potential propagation and anisotropy of the cardiac tissue into the equations of either incompressible or compressible nonlinear elasticity, governing the mechanical response of the biological material. In addition, by changing from an Eulerian to a Lagrangian configuration, the bidomain or monodomain equations modeling the evolution of the electrical propagation exhibit a nonlinear diffusion term. Piecewise quadratic finite elements are employed to approximate the displacements field, whereas for pressure, electrical potentials and ionic variables are approximated by piecewise linear elements. Various numerical tests performed with a parallel finite element code illustrate that the proposed model can capture some important features of the electromechanical coupling, and show that our numerical scheme is efficient and accurate.

Valuing equity-linked death benefits in jump diffusion models

The paper is motivated by the valuation problem of guaranteed minimum death benefits in various equity-linked products. At the time of death, a benefit payment is due. It may depend not only on the price of a stock or stock fund at that time, but also on prior prices. The problem is to calculate the expected discounted value of the benefit payment. Because the distribution of the time of death can be approximated by a combination of exponential distributions, it suffices to solve the problem for an exponentially distributed time of death. The stock price process is assumed to be the exponential of a Brownian motion plus an independent compound Poisson process whose upward and downward jumps are modeled by combinations (or mixtures) of exponential distributions. Results for exponential stopping of a Lévy process are used to derive a series of closed-form formulas for call, put, lookback, and barrier options, dynamic fund protection, and dynamic withdrawal benefit with guarantee. We also discuss how barrier options can be used to model lapses and surrenders.

Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T.

PURPOSE: To determine whether a mono-, bi- or tri-exponential model best fits the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) signal of normal livers. MATERIALS AND METHODS: The pilot and validation studies were conducted in 38 and 36 patients with normal livers, respectively. The DWI sequence was performed using single-shot echoplanar imaging with 11 (pilot study) and 16 (validation study) b values. In each study, data from all patients were used to model the IVIM signal of normal liver. Diffusion coefficients (Di ± standard deviations) and their fractions (fi ± standard deviations) were determined from each model. The models were compared using the extra sum-of-squares test and information criteria. RESULTS: The tri-exponential model provided a better fit than both the bi- and mono-exponential models. The tri-exponential IVIM model determined three diffusion compartments: a slow (D1 = 1.35 ± 0.03 × 10(-3) mm(2)/s; f1 = 72.7 ± 0.9 %), a fast (D2 = 26.50 ± 2.49 × 10(-3) mm(2)/s; f2 = 13.7 ± 0.6 %) and a very fast (D3 = 404.00 ± 43.7 × 10(-3) mm(2)/s; f3 = 13.5 ± 0.8 %) diffusion compartment [results from the validation study]. The very fast compartment contributed to the IVIM signal only for b values ≤15 s/mm(2) CONCLUSION: The tri-exponential model provided the best fit for IVIM signal decay in the liver over the 0-800 s/mm(2) range. In IVIM analysis of normal liver, a third very fast (pseudo)diffusion component might be relevant. KEY POINTS: ? For normal liver, tri-exponential IVIM model might be superior to bi-exponential ? A very fast compartment (D = 404.00 ± 43.7 × 10 (-3)  mm (2) /s; f = 13.5 ± 0.8 %) is determined from the tri-exponential model ? The compartment contributes to the IVIM signal only for b ≤ 15 s/mm (2.)