Pulmonary Artery-Vein Segmentation in Real and Synthetic CT Images = Segmentación Arteria-Vena Pulmonares en Imágenes de CT Reales y Sintéticas

La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.

Contributions of cell kill and posttreatment tumor growth rates to the repopulation of intracerebral 9L tumors after chemotherapy: An MRI study

The drought of progress in clinical brain tumor therapy provides an impetus for developing new treatments as well as methods for testing therapeutics in animal models. The inability of traditional assays to simultaneously measure tumor size, location, growth kinetics, and cell kill achieved by a treatment complicates the interpretation of therapy experiments in animal models. To address these issues, tumor volume measurements obtained from serial magnetic resonance images were used to noninvasively estimate cell kill values in individual rats with intracerebral 9L tumors after treatment with 0.5, 1, or 2 × LD10 doses of 1,3-bis(2-chloroethyl)-1-nitrosourea. The calculated cell kill values were consistently lower than those reported using traditional assays. A dose-dependent increase in 9L tumor doubling time after treatment was observed that significantly contributed to the time required for surviving cells to repopulate the tumor mass. This study reveals that increases in animal survival are not exclusively attributable to the fraction of tumor cells killed but rather are a function of the cell kill and repopulation kinetics, both of which vary with treatment dose.

Binding site of brefeldin A at the interface between the small G protein ADP-ribosylation factor 1 (ARF1) and the nucleotide-exchange factor Sec7 domain

Sec7 domains (Sec7d) catalyze the exchange of guanine nucleotide on ARFs. Recent studies indicated that brefeldin A (BFA) inhibits Sec7d-catalyzed nucleotide exchange on ARF1 in an uncompetitive manner by trapping an early intermediate of the reaction: a complex between GDP-bound ARF1 and Sec7d. Using 3H-labeled BFA, we show that BFA binds to neither isolated Sec7d nor isolated ARF1–GDP, but binds to the transitory Sec7d–ARF1–GDP complex and stabilizes it. Two pairs of residues at positions 190–191 and 198–208 (Arno numbering) in Sec7d contribute equally to the stability of BFA binding, which is also sensitive to mutation of H80 in ARF1. The catalytic glutamic (E156) residue of Sec7d is not necessary for BFA binding. In contrast, BFA does not bind to the intermediate catalytic complex between nucleotide-free ARF1 and Sec7d. These results suggest that, on initial docking steps between ARF1–GDP and Sec7d, BFA inserts like a wedge between the switch II region of ARF1–GDP and a surface encompassing residues 190–208, at the border of the characteristic hydrophobic groove of Sec7d. Bound BFA would prevent the switch regions of ARF1–GDP from reorganizing and forming tighter contacts with Sec7d and thereby would maintain the bound GDP of ARF1 at a distance from the catalytic glutamic finger of Sec7d.

Dynamic evolution of plant mitochondrial genomes: Mobile genes and introns and highly variable mutation rates

We summarize our recent studies showing that angiosperm mitochondrial (mt) genomes have experienced remarkably high rates of gene loss and concomitant transfer to the nucleus and of intron acquisition by horizontal transfer. Moreover, we find substantial lineage-specific variation in rates of these structural mutations and also point mutations. These findings mostly arise from a Southern blot survey of gene and intron distribution in 281 diverse angiosperms. These blots reveal numerous losses of mt ribosomal protein genes but, with one exception, only rare loss of respiratory genes. Some lineages of angiosperms have kept all of their mt ribosomal protein genes whereas others have lost most of them. These many losses appear to reflect remarkably high (and variable) rates of functional transfer of mt ribosomal protein genes to the nucleus in angiosperms. The recent transfer of cox2 to the nucleus in legumes provides both an example of interorganellar gene transfer in action and a starting point for discussion of the roles of mechanistic and selective forces in determining the distribution of genetic labor between organellar and nuclear genomes. Plant mt genomes also acquire sequences by horizontal transfer. A striking example of this is a homing group I intron in the mt cox1 gene. This extraordinarily invasive mobile element has probably been acquired over 1,000 times separately during angiosperm evolution via a recent wave of cross-species horizontal transfers. Finally, whereas all previously examined angiosperm mtDNAs have low rates of synonymous substitutions, mtDNAs of two distantly related angiosperms have highly accelerated substitution rates.

The cellulose-binding domain of the major cellobiohydrolase of Trichoderma reesei exhibits true reversibility and a high exchange rate on crystalline cellulose.

Cellulose-binding domains (CBDs) bind specifically to cellulose, and form distinct domains of most cellulose degrading enzymes. The CBD-mediated binding of the enzyme has a fundamental role in the hydrolysis of the solid cellulose substrate. In this work we have investigated the reversibility and kinetics of the binding of the CBD from Trichoderma reesei cellobiohydrolase I on microcrystalline cellulose. The CBD was produced in Escherichia coli, purified, and radioactively labeled by reductive alkylation with 3H. Sensitive detection of the labeled CBD allowed more detailed analysis of its behavior than has been possible before, and important novel features were resolved. Binding of the CBD was found to be temperature sensitive, with an increased affinity at lower temperatures. The interaction of the CBD with cellulose was shown to be fully reversible and the CBD could be eluted from cellulose by simple dilution. The rate of exchange measured for the CBD-cellulose interaction compares well with the hydrolysis rate of cellobiohydrolase I, which is consistent with its proposed mode of action as a processive exoglucanase.

A dominant-negative mutant of human poly(ADP-ribose) polymerase affects cell recovery, apoptosis, and sister chromatid exchange following DNA damage.

Poly(ADP-ribose) polymerase [PARP; NAD+ ADP-ribosyltransferase; NAD+:poly(adenosine-diphosphate-D-ribosyl)-acceptor ADP-D-ribosyltransferase, EC 2.4.2.30] is a zinc-dependent eukaryotic DNA-binding protein that specifically recognizes DNA strand breaks produced by various genotoxic agents. To study the biological function of this enzyme, we have established stable HeLa cell lines that constitutively produce the 46-kDa DNA-binding domain of human PARP (PARP-DBD), leading to the trans-dominant inhibition of resident PARP activity. As a control, a cell line was constructed, producing a point-mutated version of the DBD, which has no affinity for DNA in vitro. Expression of the PARP-DBD had only a slight effect on undamaged cells but had drastic consequences for cells treated with genotoxic agents. Exposure of cell lines expressing the wild-type (wt) or the mutated PARP-DBD, with low doses of N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) resulted in an increase in their doubling time, a G2 + M accumulation, and a marked reduction in cell survival. However, UVC irradiation had no preferential effect on the cell growth or viability of cell lines expressing the PARP-DBD. These PARP-DBD-expressing cells treated with MNNG presented the characteristic nucleosomal DNA ladder, one of the hallmarks of cell death by apoptosis. Moreover, these cells exhibited chromosomal instability as demonstrated by higher frequencies of both spontaneous and MNNG-induced sister chromatid exchanges. Surprisingly, the line producing the mutated DBD had the same behavior as those producing the wt DBD, indicating that the mechanism of action of the dominant-negative mutant involves more than its DNA-binding function. Altogether, these results strongly suggest that PARP is an element of the G2 checkpoint in mammalian cells.