Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

Development of a single photon counting computed tomography system using MPGDs

The development of computed tomography systems with energy resolving detectors is a current challenge in medical physics and biomedical engineering. A computed tomography system of this kind allows getting complementary informations relatively to conventional systems, that can help the medical diagnosis, being of great interest in medicine. The work described in this thesis is related to the development of a computed tomography system using micropattern gaseous detectors, which allow storing, simultaneously, information about the interaction position and the energy of each single photon that interacts with the detector. This kind of detectors has other advantages concerning the cost and characteristics of operation when compared with solid state detectors. Tomographic acquisitions were performed using a MicroHole & Strip Plate based detector, which allowed reconstructing cross-sectional images using energy windows, applying the energy weighting technique and performing multi-slice and tri-dimensional reconstructions. The contrast-to-noise ratio was improved by 31% by applying the energy weighting technique, comparing with the corresponding image obtained with the current medical systems. A prototype of a computed tomography with flexibility to change the detector was developed, making it possible to apply different detectors based on Thick-COBRA. Several images acquired with these detectors are presented and demonstrate their applicability in X-ray imaging. When operating in NeCH4, the detector allowed a charge gain of 8 104, an energy resolution of 20% (full width at half maximum at 8 keV), a count rate of 1 106 Hz/mm2, a very stable operation (gain fluctuations below 5%) and a spacial resolution of 1.2 mm for an energy photon of 3.6 keV. Operating the detector in pure Kr allowed increasing the detection efficiency and achieving a charge gain of 2 104, an energy resolution of 32% (full width at half maximum at 22 keV), a count rate of 1 105 Hz/mm2, very stable operation and a spatial resolution of 500 m. The software already existing in the group was improved and tools to correct geometric misalignments of the system were also developed. The reconstructions obtained after geometrical correction are free of artefacts due to the referred misalignments.

Control of endosomal Toll-like receptor (TLR) signaling by nanoparticles and applications in cancer therapy

Thesis (Ph.D.)--University of Washington, 2014

A theoretical study on modelling the respiratory tract with ladder networks by means of intrinsic fractal geometry

Fractional order modeling of biological systems has received significant interest in the research community. Since the fractal geometry is characterized by a recurrent structure, the self-similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. To demonstrate the link between the recurrence of the respiratory tree and the appearance of a fractional-order model, we develop an anatomically consistent representation of the respiratory system. This model is capable of simulating the mechanical properties of the lungs and we compare the model output with in vivo measurements of the respiratory input impedance collected in 20 healthy subjects. This paper provides further proof of the underlying fractal geometry of the human lungs, and the consequent appearance of constant-phase behavior in the total respiratory impedance.

Quantitative functional MRI of the Cerebrovascular Reactivity to CO2

Le dioxyde de carbone (CO2) est un résidu naturel du métabolisme cellulaire, la troisième substance la plus abondante du sang, et un important agent vasoactif. À la moindre variation de la teneur en CO2 du sang, la résistance du système vasculaire cérébral et la perfusion tissulaire cérébrale subissent des changements globaux. Bien que les mécanismes exacts qui sous-tendent cet effet restent à être élucidés, le phénomène a été largement exploité dans les études de réactivité vasculaire cérébrale (RVC). Une voie prometteuse pour l’évaluation de la fonction vasculaire cérébrale est la cartographie de la RVC de manière non-invasive grâce à l’utilisation de l’Imagerie par Résonance Magnétique fonctionnelle (IRMf). Des mesures quantitatives et non-invasives de de la RVC peuvent être obtenus avec l’utilisation de différentes techniques telles que la manipu- lation du contenu artériel en CO2 (PaCO2) combinée à la technique de marquage de spin artériel (Arterial Spin Labeling, ASL), qui permet de mesurer les changements de la perfusion cérébrale provoqués par les stimuli vasculaires. Toutefois, les préoccupations liées à la sensibilité et la fiabilité des mesures de la RVC limitent de nos jours l’adoption plus large de ces méthodes modernes de IRMf. J’ai considéré qu’une analyse approfondie ainsi que l’amélioration des méthodes disponibles pourraient apporter une contribution précieuse dans le domaine du génie biomédical, de même qu’aider à faire progresser le développement de nouveaux outils d’imagerie de diagnostique. Dans cette thèse je présente une série d’études où j’examine l’impact des méthodes alternatives de stimulation/imagerie vasculaire sur les mesures de la RVC et les moyens d’améliorer la sensibilité et la fiabilité de telles méthodes. J’ai aussi inclus dans cette thèse un manuscrit théorique où j’examine la possible contribution d’un facteur méconnu dans le phénomène de la RVC : les variations de la pression osmotique du sang induites par les produits de la dissolution du CO2. Outre l’introduction générale (Chapitre 1) et les conclusions (Chapitre 6), cette thèse comporte 4 autres chapitres, au long des quels cinq différentes études sont présentées sous forme d’articles scientifiques qui ont été acceptés à des fins de publication dans différentes revues scientifiques. Chaque chapitre débute par sa propre introduction, qui consiste en une description plus détaillée du contexte motivant le(s) manuscrit(s) associé(s) et un bref résumé des résultats transmis. Un compte rendu détaillé des méthodes et des résultats peut être trouvé dans le(s) dit(s) manuscrit(s). Dans l’étude qui compose le Chapitre 2, je compare la sensibilité des deux techniques ASL de pointe et je démontre que la dernière implémentation de l’ASL continue, la pCASL, offre des mesures plus robustes de la RVC en comparaison à d’autres méthodes pulsés plus âgées. Dans le Chapitre 3, je compare les mesures de la RVC obtenues par pCASL avec l’utilisation de quatre méthodes respiratoires différentes pour manipuler le CO2 artérielle (PaCO2) et je démontre que les résultats peuvent varier de manière significative lorsque les manipulations ne sont pas conçues pour fonctionner dans l’intervalle linéaire de la courbe dose-réponse du CO2. Le Chapitre 4 comprend deux études complémentaires visant à déterminer le niveau de reproductibilité qui peut être obtenu en utilisant des méthodes plus récentes pour la mesure de la RVC. La première étude a abouti à la mise au point technique d’un appareil qui permet des manipulations respiratoires du CO2 de manière simple, sécuritaire et robuste. La méthode respiratoire améliorée a été utilisée dans la seconde étude – de neuro-imagerie – où la sensibilité et la reproductibilité de la RVC, mesurée par pCASL, ont été examinées. La technique d’imagerie pCASL a pu détecter des réponses de perfusion induites par la variation du CO2 dans environ 90% du cortex cérébral humain et la reproductibilité de ces mesures était comparable à celle d’autres mesures hémodynamiques déjà adoptées dans la pratique clinique. Enfin, dans le Chapitre 5, je présente un modèle mathématique qui décrit la RVC en termes de changements du PaCO2 liés à l’osmolarité du sang. Les réponses prédites par ce modèle correspondent étroitement aux changements hémodynamiques mesurés avec pCASL ; suggérant une contribution supplémentaire à la réactivité du système vasculaire cérébral en lien avec le CO2.

Semiautomatic Detection of Scoliotic Rib Borders From Posteroanterior Chest Radiographs

3-D assessment of scoliotic deformities relies on an accurate 3-D reconstruction of bone structures from biplanar X-rays, which requires a precise detection and matching of anatomical structures in both views. In this paper, we propose a novel semiautomated technique for detecting complete scoliotic rib borders from PA-0° and PA-20° chest radiographs, by using an edge-following approach with multiple-path branching and oriented filtering. Edge-following processes are initiated from user starting points along upper and lower rib edges and the final rib border is obtained by finding the most parallel pair among detected edges. The method is based on a perceptual analysis leading to the assumption that no matter how bent a scoliotic rib is, it will always present relatively parallel upper and lower edges. The proposed method was tested on 44 chest radiographs of scoliotic patients and was validated by comparing pixels from all detected rib borders against their reference locations taken from the associated manually delineated rib borders. The overall 2-D detection accuracy was 2.64 ± 1.21 pixels. Comparing this accuracy level to reported results in the literature shows that the proposed method is very well suited for precisely detecting borders of scoliotic ribs from PA-0° and PA-20° chest radiographs.

A Novel Method for the 3-D Reconstruction of Scoliotic Ribs From Frontal and Lateral Radiographs

Among the external manifestations of scoliosis, the rib hump, which is associated with the ribs' deformities and rotations, constitutes the most disturbing aspect of the scoliotic deformity for patients. A personalized 3-D model of the rib cage is important for a better evaluation of the deformity, and hence, a better treatment planning. A novel method for the 3-D reconstruction of the rib cage, based only on two standard radiographs, is proposed in this paper. For each rib, two points are extrapolated from the reconstructed spine, and three points are reconstructed by stereo radiography. The reconstruction is then refined using a surface approximation. The method was evaluated using clinical data of 13 patients with scoliosis. A comparison was conducted between the reconstructions obtained with the proposed method and those obtained by using a previous reconstruction method based on two frontal radiographs. A first comparison criterion was the distances between the reconstructed ribs and the surface topography of the trunk, considered as the reference modality. The correlation between ribs axial rotation and back surface rotation was also evaluated. The proposed method successfully reconstructed the ribs of the 6th-12th thoracic levels. The evaluation results showed that the 3-D configuration of the new rib reconstructions is more consistent with the surface topography and provides more accurate measurements of ribs axial rotation.

Patient-specific anisotropic model of human trunk based on MR data

There are many ways to generate geometrical models for numerical simulation, and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient-specific three-dimensional geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as gray levels, we built a metric to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of the Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster. Copyright © 2015 John Wiley & Sons, Ltd.

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in meal estimation

Gel vs aceite mineral en el tratamiento del fotoenvejecimiento de manos con luz pulsada intensa

Introducción: En el tratamiento con Luz Pulsada Intensa (LPI) para el fotoenvejecimiento de las manos no se encuentran estudios que evidencien si existe alguna diferencia estadísticamente significativa en el grado de efectividad y seguridad al utilizar gel o aceite mineral como medios de acople. Objetivo: Determinar la efectividad y seguridad terapéutica en el uso de gel vs aceite mineral. Materiales y Métodos: Estudio observacional analítico de cohorte retrospectivo que involucró 29 pacientes. Realizado en tres fases; selección y recolección de las historias clínicas, evaluación fotográfica de registros pre tratamiento y pos tratamiento con determinación del grado de mejoría global en el fotoenvejecimiento de las manos por parte de tres evaluadores cegados, y análisis estadístico de los datos obtenidos por medio de las pruebas de Mann Whitney y Wilcoxon. Resultados: Se encontró mejoría dada por disminución en un grado del fotoenvejecimiento para los dos medios de acople con la misma significancia estadística. La percepción subjetiva mostró mejoría en todos los pacientes evaluados. La seguridad es similar en los dos grupos pero se evidenció mayor severidad en los efectos secundarios con el uso de aceite, con diferencias estadísticamente significativas en los efectos moderados y severos. Conclusión: La efectividad es la misma independiente del medio de acople que se use. La seguridad a pesar de evidenciar un perfil similar es mayor con el uso de gel en cuanto a la menor severidad de los efectos presentados. Se requieren más estudios de tipo ensayos clínicos controlados que permitan determinar una mayor evidencia.

Caracterización de la gestión del mantenimiento de equipo biomédico en servicios de urgencia de clínicas y hospitales de Medellín en el período 2008-2009

La gestión de mantenimiento es una herramienta de gran impacto que apoya al personal de Ingeniería en el desarrollo, control y dirección de programas de mantenimiento para el equipo médico. Objetivo: caracterizar la gestión de mantenimiento en servicios de urgencia de clínicas y hospitales del área metropolitana de Medellín en el período 2008-2009. Materiales y métodos: se realizó una encuesta a jefes y técnicos de mantenimiento en once entidades prestadoras de servicios de salud, clasificadas en tercer nivel y pertenecientes a la red de salud del municipio de Medellín. Resultados: entre las instituciones encuestadas se encontró que la causa de falla más común en los equipos del servicio de urgencia es el mal manejo de los equipos (75%) por partede los operarios y que 70% del mantenimiento es realizado por personal con experiencia en el área (tecnólogos en mantenimiento de equipo biomédico e ingenieros biomédicos). En las once instituciones públicas y privadas encuestadas se halló que solo se contaban con cronogramas de mantenimiento y/o con información desactualizada concerniente a las hojas de vida de los equipos, planes de mantenimiento o adquisición y baja de equipos. Conclusión: el estudio muestra la existencia de debilidades en ciertos puntos de la gestión, incluyendo mala organización, poca disponibilidad de repuestos originales y falta de capacitación en el personal que maneja los equipos.

Prediction of Parkinson's disease tremor onset using artificial neural networks

In this paper we present the initial results using an artificial neural network to predict the onset of Parkinson's Disease tremors in a human subject. Data for the network was obtained from implanted deep brain electrodes. A tuned artificial neural network was shown to be able to identify the pattern of the onset tremor from these real time recordings.