Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

A methodology to event reconstruction from trace images

The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally, as clues in investigation and crime reconstruction processes.

Detection of ingested cocaine-filled packets: comparison of filtered back projection CT with adaptive statistical iterative reconstructed images

Purpose: To evaluate the diagnostic value and image quality of CT with filtered back projection (FBP) compared with adaptive statistical iterative reconstructed images (ASIR) in body stuffers with ingested cocaine-filled packets.Methods and Materials: Twenty-nine body stuffers (mean age 31.9 years, 3 women) suspected for ingestion of cocaine-filled packets underwent routine-dose 64-row multidetector CT with FBP (120kV, pitch 1.375, 100-300 mA and automatic tube current modulation (auto mA), rotation time 0.7sec, collimation 2.5mm), secondarily reconstructed with 30 % and 60 % ASIR. In 13 (44.83%) out of the body stuffers cocaine-filled packets were detected, confirmed by exact analysis of the faecal content including verification of the number (range 1-25). Three radiologists independently and blindly evaluated anonymous CT examinations (29 FBP-CT and 68 ASIR-CT) for the presence and number of cocaine-filled packets indicating observers' confidence, and graded them for diagnostic quality, image noise, and sharpness. Sensitivity, specificity, area under the receiver operating curve (ROC) Az and interobserver agreement between the 3 radiologists for FBP-CT and ASIR-CT were calculated.Results: The increase of the percentage of ASIR significantly diminished the objective image noise (p<0.001). Overall sensitivity and specificity for the detection of the cocaine-filled packets were 87.72% and 76.15%, respectively. The difference of ROC area Az between the different reconstruction techniques was significant (p= 0.0101), that is 0.938 for FBP-CT, 0.916 for 30 % ASIR-CT, and 0.894 for 60 % ASIR-CT.Conclusion: Despite the evident image noise reduction obtained by ASIR, the diagnostic value for detecting cocaine-filled packets decreases, depending on the applied ASIR percentage.

Dose reconstruction in the context of tomotherapy

In vivo dosimetry is a way to verify the radiation dose delivered to the patient in measuring the dose generally during the first fraction of the treatment. It is the only dose delivery control based on a measurement performed during the treatment. In today's radiotherapy practice, the dose delivered to the patient is planned using 3D dose calculation algorithms and volumetric images representing the patient. Due to the high accuracy and precision necessary in radiation treatments, national and international organisations like ICRU and AAPM recommend the use of in vivo dosimetry. It is also mandatory in some countries like France. Various in vivo dosimetry methods have been developed during the past years. These methods are point-, line-, plane- or 3D dose controls. A 3D in vivo dosimetry provides the most information about the dose delivered to the patient, with respect to ID and 2D methods. However, to our knowledge, it is generally not routinely applied to patient treatments yet. The aim of this PhD thesis was to determine whether it is possible to reconstruct the 3D delivered dose using transmitted beam measurements in the context of narrow beams. An iterative dose reconstruction method has been described and implemented. The iterative algorithm includes a simple 3D dose calculation algorithm based on the convolution/superposition principle. The methodology was applied to narrow beams produced by a conventional 6 MV linac. The transmitted dose was measured using an array of ion chambers, as to simulate the linear nature of a tomotherapy detector. We showed that the iterative algorithm converges quickly and reconstructs the dose within a good agreement (at least 3% / 3 mm locally), which is inside the 5% recommended by the ICRU. Moreover it was demonstrated on phantom measurements that the proposed method allows us detecting some set-up errors and interfraction geometry modifications. We also have discussed the limitations of the 3D dose reconstruction for dose delivery error detection. Afterwards, stability tests of the tomotherapy MVCT built-in onboard detector was performed in order to evaluate if such a detector is suitable for 3D in-vivo dosimetry. The detector showed stability on short and long terms comparable to other imaging devices as the EPIDs, also used for in vivo dosimetry. Subsequently, a methodology for the dose reconstruction using the tomotherapy MVCT detector is proposed in the context of static irradiations. This manuscript is composed of two articles and a script providing further information related to this work. In the latter, the first chapter introduces the state-of-the-art of in vivo dosimetry and adaptive radiotherapy, and explains why we are interested in performing 3D dose reconstructions. In chapter 2 a dose calculation algorithm implemented for this work is reviewed with a detailed description of the physical parameters needed for calculating 3D absorbed dose distributions. The tomotherapy MVCT detector used for transit measurements and its characteristics are described in chapter 3. Chapter 4 contains a first article entitled '3D dose reconstruction for narrow beams using ion chamber array measurements', which describes the dose reconstruction method and presents tests of the methodology on phantoms irradiated with 6 MV narrow photon beams. Chapter 5 contains a second article 'Stability of the Helical TomoTherapy HiArt II detector for treatment beam irradiations. A dose reconstruction process specific to the use of the tomotherapy MVCT detector is presented in chapter 6. A discussion and perspectives of the PhD thesis are presented in chapter 7, followed by a conclusion in chapter 8. The tomotherapy treatment device is described in appendix 1 and an overview of 3D conformai- and intensity modulated radiotherapy is presented in appendix 2. - La dosimétrie in vivo est une technique utilisée pour vérifier la dose délivrée au patient en faisant une mesure, généralement pendant la première séance du traitement. Il s'agit de la seule technique de contrôle de la dose délivrée basée sur une mesure réalisée durant l'irradiation du patient. La dose au patient est calculée au moyen d'algorithmes 3D utilisant des images volumétriques du patient. En raison de la haute précision nécessaire lors des traitements de radiothérapie, des organismes nationaux et internationaux tels que l'ICRU et l'AAPM recommandent l'utilisation de la dosimétrie in vivo, qui est devenue obligatoire dans certains pays dont la France. Diverses méthodes de dosimétrie in vivo existent. Elles peuvent être classées en dosimétrie ponctuelle, planaire ou tridimensionnelle. La dosimétrie 3D est celle qui fournit le plus d'information sur la dose délivrée. Cependant, à notre connaissance, elle n'est généralement pas appliquée dans la routine clinique. Le but de cette recherche était de déterminer s'il est possible de reconstruire la dose 3D délivrée en se basant sur des mesures de la dose transmise, dans le contexte des faisceaux étroits. Une méthode itérative de reconstruction de la dose a été décrite et implémentée. L'algorithme itératif contient un algorithme simple basé sur le principe de convolution/superposition pour le calcul de la dose. La dose transmise a été mesurée à l'aide d'une série de chambres à ionisations alignées afin de simuler la nature linéaire du détecteur de la tomothérapie. Nous avons montré que l'algorithme itératif converge rapidement et qu'il permet de reconstruire la dose délivrée avec une bonne précision (au moins 3 % localement / 3 mm). De plus, nous avons démontré que cette méthode permet de détecter certaines erreurs de positionnement du patient, ainsi que des modifications géométriques qui peuvent subvenir entre les séances de traitement. Nous avons discuté les limites de cette méthode pour la détection de certaines erreurs d'irradiation. Par la suite, des tests de stabilité du détecteur MVCT intégré à la tomothérapie ont été effectués, dans le but de déterminer si ce dernier peut être utilisé pour la dosimétrie in vivo. Ce détecteur a démontré une stabilité à court et à long terme comparable à d'autres détecteurs tels que les EPIDs également utilisés pour l'imagerie et la dosimétrie in vivo. Pour finir, une adaptation de la méthode de reconstruction de la dose a été proposée afin de pouvoir l'implémenter sur une installation de tomothérapie. Ce manuscrit est composé de deux articles et d'un script contenant des informations supplémentaires sur ce travail. Dans ce dernier, le premier chapitre introduit l'état de l'art de la dosimétrie in vivo et de la radiothérapie adaptative, et explique pourquoi nous nous intéressons à la reconstruction 3D de la dose délivrée. Dans le chapitre 2, l'algorithme 3D de calcul de dose implémenté pour ce travail est décrit, ainsi que les paramètres physiques principaux nécessaires pour le calcul de dose. Les caractéristiques du détecteur MVCT de la tomothérapie utilisé pour les mesures de transit sont décrites dans le chapitre 3. Le chapitre 4 contient un premier article intitulé '3D dose reconstruction for narrow beams using ion chamber array measurements', qui décrit la méthode de reconstruction et présente des tests de la méthodologie sur des fantômes irradiés avec des faisceaux étroits. Le chapitre 5 contient un second article intitulé 'Stability of the Helical TomoTherapy HiArt II detector for treatment beam irradiations'. Un procédé de reconstruction de la dose spécifique pour l'utilisation du détecteur MVCT de la tomothérapie est présenté au chapitre 6. Une discussion et les perspectives de la thèse de doctorat sont présentées au chapitre 7, suivies par une conclusion au chapitre 8. Le concept de la tomothérapie est exposé dans l'annexe 1. Pour finir, la radiothérapie «informationnelle 3D et la radiothérapie par modulation d'intensité sont présentées dans l'annexe 2.

Genome reconstruction and comparative genomics of pneumocystis jirovecii

Pneumocystis jirovecii is a fungus belonging to a basal lineage of the Ascomycotina, the Taphrinomycotina subphylum. It is a parasite specific to humans that dwells primarily in the lung and can cause severe pneumonia in individuals with debilitated immune system. Despite its clinical importance, many aspects of its biology remain poorly understood, at least in part because of the lack of a continuous in vitro cultivation system. The present thesis consists in the genome reconstruction and comparative genomics of P. jirovecii. It is made of three parts: (i) the de novo sequencing of P. jirovecii genome starting from a single broncho- alveolar lavage fluid of a single patient (ii) the de novo sequencing of the genome of the plant pathogen Taphrina deformans, a fungus closely related to P. jirovecii, and (iii) the genome scale comparison of P. jirovecii to other Taphrinomycotina members. Enrichment in P. jirovecii cells by immuno-precipitation, whole DNA random amplification, two complementary high throughput DNA sequencing methods, and in silico sorting and assembly of sequences were used for the de novo reconstruction of P. jirovecii genome from the microbiota of a single clinical specimen. An iterative ad hoc pipeline as well as numerical simulations was used to recover P. jirovecii sequences while purging out contaminants and assembly or amplification chimeras. This strategy produced a 8.1 Mb assembly, which encodes 3,898 genes. Homology searches, mapping on biochemical pathways atlases, and manual validations revealed that this genome lacks (i) most of the enzymes dedicated to the amino acids biosyntheses, and (ii) most virulence factors observed in other fungi, e.g. the glyoxylate shunt pathway and specific peptidases involved in the degradation of the host cell membrane. The same analyses applied to the available genomic sequences from Pneumocystis carinii the species infecting rats and Pneumocystis murina the species infecting mice revealed the same deficiencies. The genome sequencing of T. deformans yielded a 13 Mb assembly, which encodes 5,735 genes. T. deformans possesses enzymes involved plant cell wall degradation, secondary metabolism, the glyoxylate cycle, detoxification, sterol biosynthesis, as well as the biosyntheses of plant hormones such as abscisic acid or indole-3-acetic acid. T. deformans also harbors gene subsets that have counterparts in plant saprophytes or pathogens, which is consistent with its alternate saprophytic and pathogenic lifestyles. Mating genes were also identified. The homothallism of this fungus suggests a mating-type switching mechanism. Comparative analyses indicated that 81% of P. jirovecii genes are shared with eight other Taphrinomycotina members, including T. deformans, P. carinii and P. murina. These genes are mostly involved in housekeeping activities. The genes specific to the Pneumocystis genus represent 8%, and are involved in RNA metabolism and signaling. The signaling is known to be crucial for interaction of Pneumocystis spp with their environment. Eleven percent are unique to P. jirovecii and encode mostly proteins of unknown function. These genes in conjunction with other ones (e.g. the major surface glycoproteins) might govern the interaction of P. jirovecii with its human host cells, and potentially be responsible of the host specificity. P. jirovecii exhibits a reduced genome in size with a low GC content, and most probably scavenges vital compounds such as amino acids and cholesterol from human lungs. Consistently, its genome encodes a large set of transporters (ca. 22% of its genes), which may play a pivotal role in the acquisition of these compounds. All these features are generally observed in obligate parasite of various kingdoms (bacteria, protozoa, fungi). Moreover, epidemiological studies failed to evidence a free-living form of the fungus and Pneumocystis spp were shown to co-evolved with their hosts. Given also the lack of virulence factors, our observations strongly suggest that P. jirovecii is an obligate parasite specialized in the colonization of human lungs, and which causes disease only in individuals with compromised immune system. The same conclusion is most likely true for all other Pneumocystis spp in their respective mammalian host. - Pneumocystis jirovecii est un champignon appartenant à ine branche basale des Ascomycotina, le sous-embranchement des Taphrinomycotina. C'est un parasite spécifique aux humains qui réside principalement dans les poumons, et qui peut causer des pneumonies sévères chez des individus ayant un système immunitaire déficient. En dépit de son importance clinique, de nombreux aspects de sa biologie demeurent,largement méconnus, au moins en partie à cause de l'absence d'un système de culture in vitro continu. Cette thèse traite de la reconstruction du génome et de la génomique comparative de P. jirovecii. Elle comporte trois parties: (i) le séquençage de novo du génome de P. jirovecii à partir d'un lavage broncho-alvéolaire provenant d'un seul patient, (ii) le séquençage de novo du génome d'un champignon pathogène de plante Taphrina deformans qui est phylogénétiquement proche de P. jirovecii, et (iii) la comparaison du génome de P. jirovecii à celui d'autres membres du sous-embranchement des Taphrinomycotina. Un enrichissement en cellules de P. jirovecii par immuno-précipitation, une amplification aléatoire des molécules d'ADN, deux méthodes complémentaires de séquençage à haut débit, un tri in silico et un assemblage des séquences ont été utilisés pour reconstruire de novo le génome de P. jirovecii à partir du microbiote d'un seul échantillon clinique. Un pipeline spécifique ainsi que des simulations numériques ont été utilisés pour récupérer les séquences de P. jirovecii tout en éliminant les séquences contaminants et les chimères d'amplification ou d'assemblage. Cette stratégie a produit un assemblage de 8.1 Mb, qui contient 3898 gènes. Les recherches d'homologies, de cartographie des voies métaboliques et des validations manuelles ont révélé que ce génome est dépourvu (i) de la plupart des enzymes dédiées à la biosynthèse des acides aminés, et (ii) de la plupart des facteurs de virulence observés chez d'autres champignons, par exemple, le cycle du glyoxylate ainsi que des peptidases spécifiques impliquées dans la dégradation de la membrane de la cellule hôte. Les analyses appliquées aux données génomiques disponibles de Pneumocystis carinii, l'espèce infectant les rats, et de Pneumocystis murina, l'espèce infectant les souris, ont révélé les mêmes déficiences. Le séquençage du génome de T. deformans a généré un assemblage de 13.3 Mb qui contient 5735 gènes. T. deformans possède les gènes codant pour les enzymes impliquées dans la dégradation des parois cellulaires des plantes, le métabolisme secondaire, le cycle du glyoxylate, la détoxification, la biosynthèse des stérols ainsi que la biosynthèse d'hormones de plantes telles que l'acide abscissique ou l'acide indole 3-acétique. T. deformans possède également des sous-ensembles de gènes présents exclusivement chez des saprophytes ou des pathogènes de plantes, ce qui est consistent avec son mode de vie alternatif saprophyte et pathogène. Des gènes impliqués dans la conjugaison ont été identifiés. L'homothallisme de ce champignon suggère mécanisme de permutation du type conjuguant. Les analyses comparatives ont démontré que 81% des gènes de P. jirovecii sont présent chez les autres membres du sous-embranchement des Taphrinomycotina. Ces gènes sont essentiellement impliqués dans le métabolisme basai. Les gènes spécifiques au genre Pneumocystis représentent 8%, et sont impliqués dans le métabolisme de l'ARN et la signalisation. La signalisation est connue pour être cruciale pour l'interaction des espèces de Pneumocystis avec leur environnement. Les gènes propres à P. jirovecii représentent 11% et codent en majorité pour des protéines dont la fonction est inconnue. Ces gènes en conjonction avec d'autres (par exemple, les glycoprotéines de surface), pourraient être déterminants dans l'interaction de P. jirovecii avec les cellules de l'hôte humain, et être potentiellement responsable de la spécificité d'hôte. P. jirovecii possède un génome de taille réduite à faible pourcentage en GC et récupère très probablement des composés vitaux comme les acides aminés et le cholestérol à partir des poumons humains. De manière consistante, son génome code pour de nombreux transporteurs (22% de ses gènes), qui pourraient jouer un rôle essentiel dans l'acquisition de ces composés. Ces caractéristiques sont généralement observées chez les parasites obligatoires de plusieurs règnes (bactéries, protozoaires, champignons). De plus, les études épidémiologiques n'ont pas réussi à prouver l'existence d'ime forme vivant librement du champignon. Etant donné également l'absence de facteurs de virulence, nos observations suggèrent que P. jirovecii est un parasite obligatoire spécialisé dans la colonisation des poumons humains, ne causant une maladie que chez des individus ayant un système immunitaire compromis. La même conclusion est très probablement applicable à toutes les autres espèces de Pneumocystis dans leur hôte mammifère respectif.

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

3D dose reconstruction for narrow beams using ion chamber array measurements.

3D dose reconstruction is a verification of the delivered absorbed dose. Our aim was to describe and evaluate a 3D dose reconstruction method applied to phantoms in the context of narrow beams. A solid water phantom and a phantom containing a bone-equivalent material were irradiated on a 6 MV linac. The transmitted dose was measured by using one array of a 2D ion chamber detector. The dose reconstruction was obtained by an iterative algorithm. A phantom set-up error and organ interfraction motion were simulated to test the algorithm sensitivity. In all configurations convergence was obtained within three iterations. A local reconstructed dose agreement of at least 3% / 3mm with respect to the planned dose was obtained, except in a few points of the penumbra. The reconstructed primary fluences were consistent with the planned ones, which validates the whole reconstruction process. The results validate our method in a simple geometry and for narrow beams. The method is sensitive to a set-up error of a heterogeneous phantom and interfraction heterogeneous organ motion.

Efficient total variation algorithm for fetal brain MRI reconstruction.

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy, Total Variation (TV)- based energies and more recently non-local means. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm or fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n2) and O(1/√ε), while existing techniques are in O(1/n2) and O(1/√ε). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Subclinical femoral neuropathy after anterior cruciate ligament reconstruction

Background and aim of the study: Patients with anterior cruciate ligament (ACL) reconstruction and femoral catheter analgesia may develop quadriceps amyotrophy. We aimed to determine whether this amyotrophy might be related to a femoral neuropathy. Material and method: After Ethical Committee approval and patients' written informed consent, 17 patients ASA I and II scheduled to undergo ACL reconstruction were recruited. An electromyography (EMG) was performed before the operation in order to exclude a femoral neuropathy. A femoral nerve catheter was inserted before the surgery with the aid of a nerve stimulator, and 20 ml of 0.5% ropivacaine was injected. The operation was done under spinal or general anaesthesia. Postoperative analgesia was provided with 0.2% ropivacaine for 72 hours, in association with oxycodone, paracetamol and ibuprofen. A second EMG was performed 4 weeks after the ACL repair. A femoral neuropathy was defined as a reduction of the surface of the motor response of more than 20%, compared to the first EMG. A third EMG was performed at 6 months if a neuropathy was present. Results: Mean age of this group of patients was 27 years old (range 18-38 y.). Among the 17 patients, 4 developed a transient femoral neuropathy (incidence of 24%) without clinical complain. Conclusion: In this study, the incidence of subclinical femoral neuropathy after ACL reconstruction is high. This lesion may be caused by the femoral catheter (mechanical damage, toxicity of local anaesthesia) or by the Tourniquet. Further studies are needed to investigate the incidence of subclinical neuropathy, according to the type of analgesia (epidural analgesia, PCA) and surgery.

Renal transplantation following aorto-iliac reconstruction is a safe a strategy

Introduction: Renal transplantation is considered the treatment of choice for end-stage renal disease. However, the association of occlusive aorto-iliac disease and chronic renal failure is frequent and aorto-iliac reconstruction may be necessary prior to renal transplantation. This retrospective study reviews the results of this operative strategy.Material and Methods: Between January 2001 and June 2010, 309 patients underwent renal transplantation at our institution and 8 patients had prior aorto-iliac reconstruction using prosthetic material. There were 6 men and 2 women with a median age of 62 years (range 51-70). Five aorto-bifemoral and 2 aorto-bi-iliac bypasses were performed for stage II (n=5), stage IV (n=1) and aortic aneurysm (n=1). In one patient, iliac kissing stents and an ilio-femoral bypass were implanted. 4 cadaveric and 4 living donor renal transplantations were performed with an interval of 2 months to 10 years after revascularization.The results were analysed with respect of graft and patients survival. Differences between groups were tested by the log rank method.Results: No complications and no death occurred in the post-operative period. All bypasses remained patent during follow-up. The median time of post transplantation follow-up was 46 months for all patients and 27 months for patients with prior revascularization. In the revascularized group and control group, the graft and patient survival at 1 year were respectively 100%/96%, 100%/99% and at 5 years 86%/86%, 86%/94%, without significant differences between both groups.Discussion: Our results suggest that renal transplantation following prior aorto-iliac revascularisation with prosthetic material is safe and effective. Patients with end-stage renal disease and concomitant aorto-iliac disease should therefore be considered for renal transplantation. However, caution in the interpretation of the results is indicated due to the small sample size of our study.

Evaluation of the reconstruction limits of a frequency-independent crosshole georadar waveform inversion scheme in the presence of dispersion

Waveform tomographic imaging of crosshole georadar data is a powerful method to investigate the shallow subsurface because of its ability to provide images of pertinent petrophysical parameters with extremely high spatial resolution. All current crosshole georadar waveform inversion strategies are based on the assumption of frequency-independent electromagnetic constitutive parameters. However, in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behavior. In this paper, we evaluate synthetically the reconstruction limits of a recently published crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. Our results indicate that, when combined with a source wavelet estimation procedure that provides a means of partially accounting for the frequency-dependent effects through an "effective" wavelet, the inversion algorithm performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.