Noninvasive monitoring of serial changes in pulmonary vascular resistance and acute vasodilator testing using cardiac magnetic resonance

Objectives The study sought to evaluate the ability of cardiac magnetic resonance (CMR) to monitor acute and long-term changes in pulmonary vascular resistance (PVR) noninvasively. Background PVR monitoring during the follow-up of patients with pulmonary hypertension (PH) and the response to vasodilator testing require invasive right heart catheterization. Methods An experimental study in pigs was designed to evaluate the ability of CMR to monitor: 1) an acute increase in PVR generated by acute pulmonary embolization (n = 10); 2) serial changes in PVR in chronic PH (n = 22); and 3) changes in PVR during vasodilator testing in chronic PH (n = 10). CMR studies were performed with simultaneous hemodynamic assessment using a CMR-compatible Swan-Ganz catheter. Average flow velocity in the main pulmonary artery (PA) was quantified with phase contrast imaging. Pearson correlation and mixed model analysis were used to correlate changes in PVR with changes in CMR-quantified PA velocity. Additionally, PVR was estimated from CMR data (PA velocity and right ventricular ejection fraction) using a formula previously validated. Results Changes in PA velocity strongly and inversely correlated with acute increases in PVR induced by pulmonary embolization (r = –0.92), serial PVR fluctuations in chronic PH (r = –0.89), and acute reductions during vasodilator testing (r = –0.89, p ≤ 0.01 for all). CMR-estimated PVR showed adequate agreement with invasive PVR (mean bias –1.1 Wood units,; 95% confidence interval: –5.9 to 3.7) and changes in both indices correlated strongly (r = 0.86, p < 0.01). Conclusions CMR allows for noninvasive monitoring of acute and chronic changes in PVR in PH. This capability may be valuable in the evaluation and follow-up of patients with PH.

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.

Nrf2 is essential for protection against acute pulmonary injury in mice

Nrf2 is a member of the “cap ‘n’ collar” family of transcription factors. These transcription factors bind to the NF-E2 binding sites (GCTGAGTCA) that are essential for the regulation of erythroid-specific genes. Nrf2 is expressed in a wide range of tissues, many of which are sites of expression for phase 2 detoxification genes. Nrf2−/− mice are viable and have a normal phenotype under normal laboratory conditions. The NF-E2 binding site is a subset of the antioxidant response elements that have the sequence GCNNNGTCA. The antioxidant response elements are regulatory sequences found on promoters of several phase 2 detoxification genes that are inducible by xenobiotics and antioxidants. We report here that Nrf2−/− mice are extremely susceptible to the administration of the antioxidant butylated hydroxytoluene. With doses of butylated hydroxytoluene that are tolerated by wild-type mice, the Nrf2−/− mice succumb from acute respiratory distress syndrome. Gene expression studies show that the expression of several detoxification enzymes is altered in the Nrf2−/− mice. The Nrf2−/− mice may prove to be a good in vivo model for toxicological studies. As oxidative damage causes DNA breakage, these mice may also be useful for testing carcinogenic agents.

Multi-component assessment of chronic obstructive pulmonary disease : an evaluation of the ADO and DOSE indices and the global obstructive lung disease categories in international primary care data sets

Funding The International Primary Care Respiratory Group (IPCRG) provided funding for this research project as an UNLOCK group study for which the funding was obtained through an unrestricted grant by Novartis AG, Basel, Switzerland. The latter funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Database access for the OPCRD was provided by the Respiratory Effectiveness Group (REG) and Research in Real Life; the OPCRD statistical analysis was funded by REG. The Bocholtz Study was funded by PICASSO for COPD, an initiative of Boehringer Ingelheim, Pfizer and the Caphri Research Institute, Maastricht University, The Netherlands.

Respiratory microbiota resistance and resilience to pulmonary exacerbation and subsequent antimicrobial intervention

This study was supported by the UK Natural Environment Research Council (NE/H019456/1) to CJvdG, by the Wellcome Trust (WT 098051) to AWW and JP for sequencing costs, and by The Anna Trust (KB2008) to KDB. AWW and The Rowett Institute of Nutrition and Health, University of Aberdeen, receive core funding support from the Scottish Government Rural and Environmental Science and Analysis Service (RESAS). We thank Paul Scott, Richard Rance and the Wellcome Trust Sanger Institute’s sequencing team for generating 16S rRNA gene sequence data.

Use of intrinsic modes in biology: Examples of indicial response of pulmonary blood pressure to ± step hypoxia

Recently, a new method to analyze biological nonstationary stochastic variables has been presented. The method is especially suitable to analyze the variation of one biological variable with respect to changes of another variable. Here, it is illustrated by the change of the pulmonary blood pressure in response to a step change of oxygen concentration in the gas that an animal breathes. The pressure signal is resolved into the sum of a set of oscillatory intrinsic mode functions, which have zero “local mean,” and a final nonoscillatory mode. With this device, we obtain a set of “mean trends,” each of which represents a “mean” in a definitive sense, and together they represent the mean trend systematically with different degrees of oscillatory content. Correspondingly, the oscillatory content of the signal about any mean trend can be represented by a set of partial sums of intrinsic mode functions. When the concept of “indicial response function” is used to describe the change of one variable in response to a step change of another variable, we now have a set of indicial response functions of the mean trends and another set of indicial response functions to describe the energy or intensity of oscillations about each mean trend. Each of these can be represented by an analytic function whose coefficients can be determined by a least-squares curve-fitting procedure. In this way, experimental results are stated sharply by analytic functions.

Phenotypic switching in the human pathogenic fungus Cryptococcus neoformans is associated with changes in virulence and pulmonary inflammatory response in rodents

High-frequency reversible changes in colony morphology were observed in three strains of Cryptococcus neoformans. For one strain (SB4, serotype A), this process produced three colony types: smooth (S), wrinkled (W), and serrated (C). The frequency of switching between colony types varied for the individual colony transitions and was as high as 10−3. Mice infected with colony type W died faster than those infected with other colony types. The rat inflammatory response to infection with colony types S, W, and C was C > S > W and ranged from intense granulomatous inflammation with caseous necrosis for infection with type C to minimal inflammation for infection with type W. Infection with the various colony types was associated with different antibody responses to cryptococcal proteins in rats. Analysis of cellular characteristics revealed differences between the three colony types. High-frequency changes in colony morphology were also observed in two additional strains of C. neoformans. For one strain (24067A, serotype D) the switching occurred between smooth and wrinkled colonies. For the other strain (J32A, serotype A), the switching occurred between mucoid and nonmucoid colonies. The findings indicate that C. neoformans undergoes phenotypic switching and that this process can affect virulence and host inflammatory and immune responses. Phenotypic switching may play a role in the ability of this fungus to escape host defenses and establish chronic infections.

Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis

The molecular mechanisms of pulmonary fibrosis are poorly understood. We have used oligonucleotide arrays to analyze the gene expression programs that underlie pulmonary fibrosis in response to bleomycin, a drug that causes lung inflammation and fibrosis, in two strains of susceptible mice (129 and C57BL/6). We then compared the gene expression patterns in these mice with 129 mice carrying a null mutation in the epithelial-restricted integrin β6 subunit (β6−/−), which develop inflammation but are protected from pulmonary fibrosis. Cluster analysis identified two distinct groups of genes involved in the inflammatory and fibrotic responses. Analysis of gene expression at multiple time points after bleomycin administration revealed sequential induction of subsets of genes that characterize each response. The availability of this comprehensive data set should accelerate the development of more effective strategies for intervention at the various stages in the development of fibrotic diseases of the lungs and other organs.

Nonlinear indicial response of complex nonstationary oscillations as pulmonary hypertension responding to step hypoxia

This paper is devoted to the quantization of the degree of nonlinearity of the relationship between two biological variables when one of the variables is a complex nonstationary oscillatory signal. An example of the situation is the indicial responses of pulmonary blood pressure (P) to step changes of oxygen tension (ΔpO2) in the breathing gas. For a step change of ΔpO2 beginning at time t1, the pulmonary blood pressure is a nonlinear function of time and ΔpO2, which can be written as P(t-t1 | ΔpO2). An effective method does not exist to examine the nonlinear function P(t-t1 | ΔpO2). A systematic approach is proposed here. The definitions of mean trends and oscillations about the means are the keys. With these keys a practical method of calculation is devised. We fit the mean trends of blood pressure with analytic functions of time, whose nonlinearity with respect to the oxygen level is clarified here. The associated oscillations about the mean can be transformed into Hilbert spectrum. An integration of the square of the Hilbert spectrum over frequency yields a measure of oscillatory energy, which is also a function of time, whose mean trends can be expressed by analytic functions. The degree of nonlinearity of the oscillatory energy with respect to the oxygen level also is clarified here. Theoretical extension of the experimental nonlinear indicial functions to arbitrary history of hypoxia is proposed. Application of the results to tissue remodeling and tissue engineering of blood vessels is discussed.

Streptavidin facilitates internalization and pulmonary targeting of an anti-endothelial cell antibody (platelet-endothelial cell adhesion molecule 1): A strategy for vascular immunotargeting of drugs

Conjugation of drugs with antibodies to surface endothelial antigens is a potential strategy for drug delivery to endothelium. We studied antibodies to platelet-endothelial adhesion molecule 1 (PECAM-1, a stably expressed endothelial antigen) as carriers for vascular immunotargeting. Although 125I-labeled anti-PECAM bound to endothelial cells in culture, the antibody was poorly internalized by the cells and accumulated poorly after intravenous administration in mice and rats. However, conjugation of biotinylated anti-PECAM (b-anti-PECAM) with streptavidin (SA) markedly stimulated uptake and internalization of anti-PECAM by endothelial cells and by cells expressing PECAM. In addition, conjugation with streptavidin markedly stimulated uptake of 125I-labeled b-anti-PECAM in perfused rat lungs and in the lungs of intact animals after either intravenous or intraarterial injection. The antioxidant enzyme catalase conjugated with b-anti-PECAM/SA bound to endothelial cells in culture, entered the cells, escaped intracellular degradation, and protected the cells against H2O2-induced injury. Anti-PECAM/SA/125I-catalase accumulated in the lungs after intravenous injection or in the perfused rat lungs and protected these lungs against H2O2-induced injury. Thus, modification of a poor carrier antibody with biotin and SA provides an approach for facilitation of antibody-mediated drug targeting. Anti-PECAM/SA is a promising candidate for vascular immunotargeting of bioactive drugs.

Identifying asthma and chronic obstructive pulmonary disease in patients with persistent cough presenting to general practitioners: descriptive study

Objective: To determine the prevalence of asthma and chronic obstructive pulmonary disease in patients not known to have these disorders, who present in general practice with persistent cough, and to ascertain criteria to help general practitioners in diagnosis.