Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions

Area and Volume Calculation of Necrotic Tissue regions of heart using Interpolation

This paper attempts to develop an improved tool, which would read two dimensional(2D) cardiac MRI images and compute areas and volume of the scar tissue. Here the computation would be done on the cardiac MR images to quantify the extent of damage inflicted by myocardial infarction on the cardiac muscle (myocardium) using Interpolation

Study of chemical properties and evaluation of collagen in mantle, epidermal connective tissue and tentacle of Indian Squid, Loligo duvauceli Orbigny

The chemical composition and evaluation of Indian squid (Loligo duvauceli) mantle, epidermal connective tissue and tentacle is investigated in this current study. It is observed that squid mantle contains 22.2% total protein; 63.5% of the total protein is myofibrillar protein. The unique property of squid myofibrillar protein is its water solubility. Squid mantle contains 12.0% total collagen. Epidermal connective tissue has highest amounts of total collagen (17.8%). SDS-PAGE of total collagen identified high molecular weight α-, β- and γ- sub-chains. Amino acid profile analysis indicates that mantle and tentacle contain essential amino acids. Arginine forms a major portion of mantle collagen (272.5 g/100 g N). Isoleucine, glutamic acid and lysine are other amino acids that are found in significantly high amounts in the mantle. Sulphur containing cystine is deficit in mantle collagen. Papain digest of mantle and epidermal connective tissue is rich in uronic acid, while papain digest, collagenase digest and urea digest of epidermal connective tissue has significant amounts of sialic acid (25.2, 33.2 and 99.8 μmol /100 g, respectively). PAS staining of papain digest, collagenase digest and urea digest also identify the association of hexoses with low molecular weight collagen fragments. Histochemical sectioning also emphasized the localized distribution of collagen in epidermal and dermal region and very sparse fibres traverse the myotome bundles

Effects of dietary lipid source on growth, digestibility and tissue fatty acid composition of Heterobranchus longifilis fingerlings

One of the major problems facing aquaculture is the inadequate supply of fish oil mostly used for fish feed manufacturing. The continued growth in aquaculture production cannot depend on this finite feed resources, therefore, it is imperative that cheap and readily available substitutes that do not compromise fish growth and fillet quality be found. To achieve this, a 12-week feeding trial with Heterobranchus longifilis fed diets differing in lipid source was conducted. Diets were supplemented with 6% lipid as fish oil, soybean oil, palm oil, coconut oil, groundnut oil and melon seed oil. Triplicate groups of 20 H. longifilis were fed the experimental diets two times a day to apparent satiation, over 84 days. Growth, digestibility, and muscle fatty acid profile were measured to assess diet effects. At the end of the study, survival, feed intake and hepatosomatic index were similar for fish fed experimental diets. However, weight gain, SGR and FCR of fish fed soybean oil-based diet was significantly reduced. Apparent nutrient digestibility coefficients were significantly lower in fish fed soybean, coconut and groundnut oil-based diets. Fillet and hepatic fatty acid compositions differed and reflected the fatty acid compositions of the diets. Docosahexaenoic acid (22:6n-3), 20:5n-3 and 20:4n-6 were conserved in vegetable oils-based diets fed fish possibly due to synthesis of HUFA from 18:3n-3 and 18:4n-6. Palm oil diet was the least expensive, and had the best economic conversion ratio. The use of vegetable oils in the diets had positive effect on growth and fillet composition of H. longifilis.

Segmentation of Brain Tissue from Magnetic Resonance Images

Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.

Apatite-Polymer Composites for the Controlled Dual Delivery of BMP-2 and BMP-6 for Bone Tissue Engineering

The release of growth factors from tissue engineering scaffolds provides signals that influence the migration, differentiation, and proliferation of cells. The incorporation of a drug delivery platform that is capable of tunable release will give tissue engineers greater versatility in the direction of tissue regeneration. We have prepared a novel composite of two biomaterials with proven track records - apatite and poly(lactic-co-glycolic acid) (PLGA) – as a drug delivery platform with promising controlled release properties. These composites have been tested in the delivery of a model protein, bovine serum albumin (BSA), as well as therapeutic proteins, recombinant human bone morphogenetic protein-2 (rhBMP-2) and rhBMP-6. The controlled release strategy is based on the use of a polymer with acidic degradation products to control the dissolution of the basic apatitic component, resulting in protein release. Therefore, any parameter that affects either polymer degradation or apatite dissolution can be used to control protein release. We have modified the protein release profile systematically by varying the polymer molecular weight, polymer hydrophobicity, apatite loading, apatite particle size, and other material and processing parameters. Biologically active rhBMP-2 was released from these composite microparticles over 100 days, in contrast to conventional collagen sponge carriers, which were depleted in approximately 2 weeks. The released rhBMP-2 was able to induce elevated alkaline phosphatase and osteocalcin expression in pluripotent murine embryonic fibroblasts. To augment tissue engineering scaffolds with tunable and sustained protein release capabilities, these composite microparticles can be dispersed in the scaffolds in different combinations to obtain a superposition of the release profiles. We have loaded rhBMP-2 into composite microparticles with a fast release profile, and rhBMP-6 into slow-releasing composite microparticles. An equi-mixture of these two sets of composite particles was then injected into a collagen sponge, allowing for dual release of the proteins from the collagenous scaffold. The ability of these BMP-loaded scaffolds to induce osteoblastic differentiation in vitro and ectopic bone formation in a rat model is being investigated. We anticipate that these apatite-polymer composite microparticles can be extended to the delivery of other signalling molecules, and can be incorporated into other types of tissue engineering scaffolds.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, and many others, offer tremendous promise for the personalized treatment of cancer. These technologies measure the amount of specific proteins, RNA, DNA or other molecular targets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumor specimens are heterogeneous; an individual specimen typically contains unknown amounts of multiple tissues types. Thus, the measured molecular concentrations result from an unknown mixture of tissue types, and must be normalized to account for the composition of the mixture. For example, a breast tumor biopsy may contain normal, dysplastic and cancerous epithelial cells, as well as stromal components (fatty and connective tissue) and blood and lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic and cancerous epithelial cells. The remaining tissue components serve to “contaminate” the signal of interest. The proportion of each of the tissue components changes as a function of patient characteristics (e.g., age), and varies spatially across the tumor region. Because each of the tissue components produces a different molecular signature, and the amount of each tissue type is specimen dependent, we must estimate the tissue composition of the specimen, and adjust the molecular signal for this composition. Using the idea of a chemical mass balance, we consider the total measured concentrations to be a weighted sum of the individual tissue signatures, where weights are determined by the relative amounts of the different tissue types. We develop a compositional source apportionment model to estimate the relative amounts of tissue components in a tumor specimen. We then use these estimates to infer the tissuespecific concentrations of key molecular targets for sub-typing individual tumors. We anticipate these specific measurements will greatly improve our ability to discriminate between different classes of tumors, and allow more precise matching of each patient to the appropriate treatment

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

HLA-A Typing in formalin-fixed paraffin embedded tissue samples : towards potential retrospective analysis

El Antígeno Leucocitario Humano (HLA en inglés) ha sido descrito en muchos casos como factor de pronóstico para cáncer. La característica principal de los genes de HLA, localizados en el cromosoma 6 (6p21.3), son sus numerosos polimorfismos. Los análisis de secuencia de nucleótidos muestran que la variación está restringida predominantemente a los exones que codifican los dominios de unión a péptidos de la proteína. Por lo tanto, el polimorfismo del HLA define el repertorio de péptidos que se unen a los alotipos de HLA y este hecho define la habilidad de un individuo para responder a la exposición a muchos agentes infecciosos durante su vida. La tipificación de HLA se ha convertido en un análisis importante en clínica. Muestras de tejido embebidas en parafina y fijadas con formalina (FFPE en inglés) son recolectadas rutinariamente en oncología. Este procedimiento podría ser utilizado como una buena fuente de ADN, dado que en estudios en el pasado los ensayos de recolección de ADN no eran normalmente llevados a cabo de casi ningún tejido o muestra en procedimientos clínicos regulares. Teniendo en cuenta que el problema más importante con el ADN de muestras FFPE es la fragmentación, nosotros propusimos un nuevo método para la tipificación del alelo HLA-A desde muestras FFPE basado en las secuencias del exón 2, 3 y 4. Nosotros diseñamos un juego de 12 cebadores: cuatro para el exón 2 de HLA-A, tres para el exón 3 de HLA-A y cinco para el exón 4 de HLA-A, cada uno de acuerdo las secuencias flanqueantes de su respectivo exón y la variación en la secuencia entre diferentes alelos. 17 muestran FFPE colectadas en el Hospital Universitario de Karolinska en Estocolmo Suecia fueron sometidas a PCR y los productos fueron secuenciados. Finalmente todas las secuencias obtenidas fueron analizadas y comparadas con la base de datos del IMGT-HLA. Las muestras FFPE habían sido previamente tipificadas para HLA y los resultados fueron comparados con los de este método. De acuerdo con nuestros resultados, las muestras pudieron ser correctamente secuenciadas. Con este procedimiento, podemos concluir que nuestro estudio es el primer método de tipificación basado en secuencia que permite analizar muestras viejas de ADN de las cuales no se tiene otra fuente. Este estudio abre la posibilidad de desarrollar análisis para establecer nuevas relaciones entre HLA y diferentes enfermedades como el cáncer también.

Tissue- specific DNA methylation profiles in newborns

Experimental and epidemiological studies demonstrate that fetal growth restriction and low birth weight enhance the risk of chronic diseases in adulthood. Derangements in tissue-specific epigenetic programming of fetal and placental tissues are a suggested mechanism of which DNA methylation is best understood. DNA methylation profiles in human tissue are mostly performed in DNA from white blood cells. The objective of this study was to assess DNA methylation profiles of IGF2 DMR and H19 in DNA derived from four tissues of the newborn. We obtained from 6 newborns DNA from fetal placental tissue (n = 5), umbilical cord CD34+ hematopoietic stem cells (HSC) and CD34- mononuclear cells (MNC) (n = 6), and umbilical cord Wharton jelly (n = 5). HCS were isolated using magnetic-activated cell separation. DNA methylation of the imprinted fetal growth genes IGF2 DMR and H19 was measured in all tissues using quantitative mass spectrometry. ANOVA testing showed tissue-specific differences in DNA methylation of IGF2 DMR (p value 0.002) and H19 (p value 0.001) mainly due to a higher methylation of IGF2 DMR in Wharton jelly (mean 0.65, sd 0.14) and a lower methylation of H19 in placental tissue (mean 0.25, sd 0.02) compared to other tissues. This study demonstrates the feasibility of the assessment of differential tissue specific DNA methylation. Although the results have to be confirmed in larger sample sizes, our approach gives opportunities to investigate epigenetic profiles as underlying mechanism of associations between pregnancy exposures and outcome, and disease risks in later life.

Evaluación de una herramienta educativa en conocimiento de donación y trasplante de órganos y tejidos en Colombia

El trasplante de órganos es considerado uno de los avances más significativos de la medicina moderna y es un procedimiento cada vez más exitoso en términos de supervivencia de los pacientes, siendo actualmente la mejor opción de tratamiento para los pacientes con innumerables patologías. El proceso de donación es insuficiente para cubrir las necesidades de trasplante de la población, por lo tanto, se hace necesario el desarrollo de nuevas estrategias para fortalecer la experiencia y efectividad de los programas existentes. La falta de conocimiento de los profesionales de la salud, su percepción y actitud hacia temas relacionados con el proceso de donación, pueden convertirlos en facilitadores o barreras para la identificación de potenciales donantes. Por esta razón, los recursos disponibles, las actitudes hacia la donación, la legislación y conocimiento de los procesos involucrados en la donación de tejidos y órganos son críticos. Dada la influencia de los profesionales de salud se definen los objetivos de este proyecto de tesis: determinar cuál es el conocimiento y las habilidades de los profesionales de la salud encargados de los trasplantes de órganos y de tejidos en la regional 1, evaluados mediante una herramienta educativa para contribuir a mejorar un programa eficiente de Donación de Órganos y tejidos y así mismo, fijar recomendaciones en aras de aumentar las tasas de donación, con especial énfasis en la actividad hospitalaria en el país. METODOLOGIA Se realizó un estudio basado en el análisis de la evaluación de conocimientos del proceso donación- trasplante de órganos y tejidos en el personal de salud participante en la herramienta educativa llamada “Curso taller primer respondiente del potencial donante de órganos y tejidos”. Este curso incluía un formato evaluativo que fue diligenciado de manera anónima por los participantes antes y después de recibir el contenido del curso. El estudio se desarrolló en personal de la Salud de IPS pertenecientes a la Regional I, de la Red Nacional de donación y trasplantes de órganos y tejidos. Con el fin de evidenciar si existen diferencias en el conocimiento de los participantes del curso antes y después de asistir al mismo, se utilizó la prueba de McNemar (p< 0.05). RESULTADOS Entre julio del 2011 y junio del 2012, se realizó el “Curso taller primer respondiente del potencial donante de órganos y tejidos” y se obtuvieron 303 encuestados incluidos médicos, enfermeras y auxiliares de enfermería. Al inicio del curso las respuestas acertadas con relación a legislación, selección del donante, muerte encefálica y mantenimiento del donante estuvieron alrededor del 50%. No fue posible detectar la profesión que pudiese generar riesgo en la detección del donante y los procesos asociados. Posterior al curso, el 72% de las preguntas se respondieron de manera correcta, lo que representa un incremento estadísticamente significativo. Este cambio evidenció significancia estadística al usar la prueba de McNemar y arrojar un valor de p=0.00. .DISCUSIÓN El personal de salud participante en el curso taller proveniente de unidades involucradas como generadoras de donantes muestra un déficit de conocimientos del proceso donación trasplantes lo que puede convertirlos en limitantes para dicho proceso

Descripción del estado acido base en pacientes con quemaduras térmicas agudas: serie de casos

Introducción: Los pacientes con lesiones térmicas presentan alteraciones fisiológicas complejas que hacen difícil la caracterización del estado ácido-base y así mismo alteraciones electrolíticas e hipoalbuminemia que pudieran estar relacionados con un peor pronóstico. Se ha estudiado la base déficit (BD) y el lactato, encontrando una gran divergencia en los resultados. Por lo anterior, el análisis físico-químico del estado ácido-base podría tener un rendimiento superior a los métodos tradicionales. Metodología: Se realizó el análisis de una serie de casos de 15 pacientes mayores de 15 años, con superficie corporal quemada mayor al 20% que ingresaron a una unidad de cuidado intensivo (UCI) de quemados, dentro de las siguientes 48 horas del trauma. Para el análisis se utilizaron tres métodos distintos: 1) método convencional basado en la teoría de Henderson-Hasselbalch, 2) anión-gap (AG) y anión-gap corregido por albúmina, 3) análisis físico-químico del estado ácido-base según la teoría de Stewart modificado por Fencl y Figge. Resultados: Por el método de Henderson-Hasselbalch, 8 pacientes cursaron con acidosis metabólica, 4 pacientes con una BD leve, 5 pacientes con una BD moderada y 5 pacientes con una BD severa. El AG resultó menor a 16 mmol/dl en 10 pacientes, pero al corregirlo por albumina sólo 2 pacientes cursaron con AG normal. La diferencia de iones fuertes (DIF) se encontraba anormalmente elevada en la totalidad de los pacientes. Conclusión:El análisis del AG corregido por albumina y el análisis físico-químico del estado ácido-base, podrían tener mayor rendimiento al identificar las alteraciones metabólicas de estos pacientes.

Polimorfismos del gen Butirilcolinesterasa responsables de reacciones adversas en pacientes consumidores de “cocaína”

La butirilcolinesterasa humana (BChE; EC 3.1.1.8) es una enzima polimórfica sintetizada en el hígado y en el tejido adiposo, ampliamente distribuida en el organismo y encargada de hidrolizar algunos ésteres de colina como la procaína, ésteres alifáticos como el ácido acetilsalicílico, fármacos como la metilprednisolona, el mivacurium y la succinilcolina y drogas de uso y/o abuso como la heroína y la cocaína. Es codificada por el gen BCHE (OMIM 177400), habiéndose identificado más de 100 variantes, algunas no estudiadas plenamente, además de la forma más frecuente, llamada usual o silvestre. Diferentes polimorfismos del gen BCHE se han relacionado con la síntesis de enzimas con niveles variados de actividad catalítica. Las bases moleculares de algunas de esas variantes genéticas han sido reportadas, entre las que se encuentra las variantes Atípica (A), fluoruro-resistente del tipo 1 y 2 (F-1 y F-2), silente (S), Kalow (K), James (J) y Hammersmith (H). En este estudio, en un grupo de pacientes se aplicó el instrumento validado Lifetime Severity Index for Cocaine Use Disorder (LSI-C) para evaluar la gravedad del consumo de “cocaína” a lo largo de la vida. Además, se determinaron Polimorfismos de Nucleótido Simple (SNPs) en el gen BCHE conocidos como responsables de reacciones adversas en pacientes consumidores de “cocaína” mediante secuenciación del gen y se predijo el efecto delos SNPs sobre la función y la estructura de la proteína, mediante el uso de herramientas bio-informáticas. El instrumento LSI-C ofreció resultados en cuatro dimensiones: consumo a lo largo de la vida, consumo reciente, dependencia psicológica e intento de abandono del consumo. Los estudios de análisis molecular permitieron observar dos SNPs codificantes (cSNPs) no sinónimos en el 27.3% de la muestra, c.293A>G (p.Asp98Gly) y c.1699G>A (p.Ala567Thr), localizados en los exones 2 y 4, que corresponden, desde el punto de vista funcional, a la variante Atípica (A) [dbSNP: rs1799807] y a la variante Kalow (K) [dbSNP: rs1803274] de la enzima BChE, respectivamente. Los estudios de predicción In silico establecieron para el SNP p.Asp98Gly un carácter patogénico, mientras que para el SNP p.Ala567Thr, mostraron un comportamiento neutro. El análisis de los resultados permite proponer la existencia de una relación entre polimorfismos o variantes genéticas responsables de una baja actividad catalítica y/o baja concentración plasmática de la enzima BChE y algunas de las reacciones adversas ocurridas en pacientes consumidores de cocaína.