Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

Endocarditis infecciosa : significado de la disfunción renal

Objetivo: Determinar la significación clínica y pronóstica de la disfunción renal en pacientes con Endocarditis Infecciosa (EI) Material y método: Estudio protocolizado, descriptivo, observacional y transversal de pacientes con EI diagnosticados según criterios de Duke. Se realizó un análisis comparativo entre los pacientes con EI sin (Grupo Sin) y con Disfunción Renal (Grupo DR), que se definió en base a uremia > 0.60 g/l y/o creatininemia > 1.5 mg/dl y/o hematuria o proteinuria. Fueron analizados en EPI info 6.04. Resultados: De un total de 110 EI incluidas, 58 (52.7%) presentaron DR principalmente secundaria a glomerulonefritis (n 22), sepsis (n 14), insuficiencia renal crónica (n 5), insuficiencia cardíaca, nefropatía diabética y nefrotoxicidad (n 4 cada una) y embólica (n 1). No hubo diferencias en la permanencia media hospitalaria (32 DS±23.3 vs 26.32 DS±17.28 días), el sexo (masculino: 60.3 vs 71.25%) y la demora diagnóstica (5.5 (DS±7.23) vs. 5.4 (DS±7.64 días)(pNS). La edad media fue mayor en el grupo DR en el LS (49.62 DS±15.71 vs 43.53 DS±17.94 años). El Grupo DR tuvo mas frecuentemente EI Definida (87.9 vs 67.3%) (p=0.0089) y no hubo diferencias en la localización Mitral (48.3 vs 48.1%) y Aórtica (44.8 vs 34.6%). La valvulopatía degenerativa se presentó en el LS en DR (34.5 VS 19.6%)(p=0.07). No hubo diferencias en la presencia de comórbidas (62.1 vs 71.2%) (pNS) pero la enfermedad últimamente fatal ocurrió mas frecuentemente en DR (51.4 vs 21.6%)(p=0.05). Al ingreso sólo la presencia de rales pulmonares (53.4 vs 32.7%) y púrpura cutánea (27.6 vs 13.5%) fueron más frecuentes en DR (p=0.05). La sepsis no controlada (34.5 vs 15.7%), insuficiencia cardíaca (51.7 vs 32.7%), encefalopatía (50 vs 27.5%), shock séptico (24.1 vs 7.8%) y fallo multiorgánico (34.5 vs 3.9%) fueron complicaciones más frecuentes en DR (p<0.05). La fiebre persistente se encontró en el LS en el grupo de DR (48.3 vs 32.7%)(p=0.09). No hubo diferencias en el hallazgo de vegetaciones por ecocardiografía (83.3 vs 75.6%). La anemia (Hb<9 mg/dl) (31.86 DS±53.41 vs 35.21 DS±7.85)(p=0.009), hipergammaglobulinemia (58.5 vs 29.8)(p=0.006) e hiperglucemia (36.1 vs 18.5)(p=0.03) se asociaron a DR. En el grupo con DR fue mas común la EI con cultivos negativos (31.5 vs 0%)(p=0.001) y el predominio de las infecciones por S. aureus Meticilino Resistente (MRSA)(21.6 vs 2.7%) (p=0.02). No hubo diferencias en la indicación de cirugía (31 vs 36.5%). La mortalidad hospitalaria fue significativamente mayor en DR (51.7 vs 25%)(p=0.0041)(OR 3.2, IC95%1.42-7.24). Conclusión: En los pacientes con EI la disfunción renal resultó ser un indicador de desarrollo de complicaciones infecciosas y cardíacas, de infección por MRSA y de mortalidad cruda hospitalaria.-

Factorial structure and reliability of a perceived influence on selection of a specialized plan of studies, IPEP, in secondary school students of Chillan, Chile

To evaluate these factors, the scale of perceived influences on the election of a specialized plan of studies, IPEP, was built and in this study its factorial structure and reliability were evaluated. The instrument was applied to 115 students, chosen by quote sampling. They were students of a subsidized private secondary school from the city of Chillan, Chile. An exploratory factorial analysis identified eight factors in the scale IPEP: Academic projection, Personal development, Maintenance of the social environment, Academic requirements, Satisfaction of others' expectations, Vocational information, Image of the plan and Family pressure. The results present an initial factorial structure, that empirically and theoretically adequate, whose factors were reliable and conceptually useful. These factors distinguish psychogenic and sociogenic aspects of the vocational process, and allow to initiate diagnostic and investigative actions in relation to this early vocational election that is established in secondary schools of the Chilean educational system

Factorial structure and reliability of a perceived influence on selection of a specialized plan of studies, IPEP, in secondary school students of Chillan, Chile

To evaluate these factors, the scale of perceived influences on the election of a specialized plan of studies, IPEP, was built and in this study its factorial structure and reliability were evaluated. The instrument was applied to 115 students, chosen by quote sampling. They were students of a subsidized private secondary school from the city of Chillan, Chile. An exploratory factorial analysis identified eight factors in the scale IPEP: Academic projection, Personal development, Maintenance of the social environment, Academic requirements, Satisfaction of others' expectations, Vocational information, Image of the plan and Family pressure. The results present an initial factorial structure, that empirically and theoretically adequate, whose factors were reliable and conceptually useful. These factors distinguish psychogenic and sociogenic aspects of the vocational process, and allow to initiate diagnostic and investigative actions in relation to this early vocational election that is established in secondary schools of the Chilean educational system

Factorial structure and reliability of a perceived influence on selection of a specialized plan of studies, IPEP, in secondary school students of Chillan, Chile

To evaluate these factors, the scale of perceived influences on the election of a specialized plan of studies, IPEP, was built and in this study its factorial structure and reliability were evaluated. The instrument was applied to 115 students, chosen by quote sampling. They were students of a subsidized private secondary school from the city of Chillan, Chile. An exploratory factorial analysis identified eight factors in the scale IPEP: Academic projection, Personal development, Maintenance of the social environment, Academic requirements, Satisfaction of others' expectations, Vocational information, Image of the plan and Family pressure. The results present an initial factorial structure, that empirically and theoretically adequate, whose factors were reliable and conceptually useful. These factors distinguish psychogenic and sociogenic aspects of the vocational process, and allow to initiate diagnostic and investigative actions in relation to this early vocational election that is established in secondary schools of the Chilean educational system

Nonparametric Message Passing Methods for Cooperative Localization and Tracking

The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

Mechanical behaviour and rupture of normal and pathological human ascending aortic wall

The mechanical properties of aortic wall, both healthy and pathological, are needed in order to develop and improve diagnostic and interventional criteria, and for the development of mechanical models to assess arterial integrity. This study focuses on the mechanical behaviour and rupture conditions of the human ascending aorta and its relationship with age and pathologies. Fresh ascending aortic specimens harvested from 23 healthy donors, 12 patients with bicuspid aortic valve (BAV) and 14 with aneurysm were tensile-tested in vitro under physiological conditions. Tensile strength, stretch at failure and elbow stress were measured. The obtained results showed that age causes a major reduction in the mechanical parameters of healthy ascending aortic tissue, and that no significant differences are found between the mechanical strength of aneurysmal or BAV aortic specimens and the corresponding age-matched control group. The physiological level of the stress in the circumferential direction was also computed to assess the physiological operation range of healthy and diseased ascending aortas. The mean physiological wall stress acting on pathologic aortas was found to be far from rupture, with factors of safety (defined as the ratio of tensile strength to the mean wall stress) larger than six. In contrast, the physiological operation of pathologic vessels lays in the stiff part of the response curve, losing part of its function of damping the pressure waves from the heart.

B-LOG: A branch and bound methodology for the parallel execution of logic programs

We propose a computational methodology -"B-LOG"-, which offers the potential for an effective implementation of Logic Programming in a parallel computer. We also propose a weighting scheme to guide the search process through the graph and we apply the concepts of parallel "branch and bound" algorithms in order to perform a "best-first" search using an information theoretic bound. The concept of "session" is used to speed up the search process in a succession of similar queries. Within a session, we strongly modify the bounds in a local database, while bounds kept in a global database are weakly modified to provide a better initial condition for other sessions. We also propose an implementation scheme based on a database machine using "semantic paging", and the "B-LOG processor" based on a scoreboard driven controller.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases.

A Ground-Truth Video Dataset for the Development and Evaluation of Vision-based Sense-and-Avoid systems

The importance of vision-based systems for Sense-and-Avoid is increasing nowadays as remotely piloted and autonomous UAVs become part of the non-segregated airspace. The development and evaluation of these systems demand flight scenario images which are expensive and risky to obtain. Currently Augmented Reality techniques allow the compositing of real flight scenario images with 3D aircraft models to produce useful realistic images for system development and benchmarking purposes at a much lower cost and risk. With the techniques presented in this paper, 3D aircraft models are positioned firstly in a simulated 3D scene with controlled illumination and rendering parameters. Realistic simulated images are then obtained using an image processing algorithm which fuses the images obtained from the 3D scene with images from real UAV flights taking into account on board camera vibrations. Since the intruder and camera poses are user-defined, ground truth data is available. These ground truth annotations allow to develop and quantitatively evaluate aircraft detection and tracking algorithms. This paper presents the software developed to create a public dataset of 24 videos together with their annotations and some tracking application results.