3D documentation and visualization of external injury findings by integration of simple photography in CT/MRI data sets (IprojeCT).

This study evaluated the feasibility of documenting patterned injury using three dimensions and true colour photography without complex 3D surface documentation methods. This method is based on a generated 3D surface model using radiologic slice images (CT) while the colour information is derived from photographs taken with commercially available cameras. The external patterned injuries were documented in 16 cases using digital photography as well as highly precise photogrammetry-supported 3D structured light scanning. The internal findings of these deceased were recorded using CT and MRI. For registration of the internal with the external data, two different types of radiographic markers were used and compared. The 3D surface model generated from CT slice images was linked with the photographs, and thereby digital true-colour 3D models of the patterned injuries could be created (Image projection onto CT/IprojeCT). In addition, these external models were merged with the models of the somatic interior. We demonstrated that 3D documentation and visualization of external injury findings by integration of digital photography in CT/MRI data sets is suitable for the 3D documentation of individual patterned injuries to a body. Nevertheless, this documentation method is not a substitution for photogrammetry and surface scanning, especially when the entire bodily surface is to be recorded in three dimensions including all external findings, and when precise data is required for comparing highly detailed injury features with the injury-inflicting tool.

Pulmonary lymphangioleiomyomatosis: analysis of disease manifestation by region-based quantification of lung parenchyma

PURPOSE Lymphangioleiomyomatosis (LAM) is characterized by proliferation of smooth muscle tissue that causes bronchial obstruction and secondary cystic destruction of lung parenchyma. The aim of this study was to evaluate the typical distribution of cystic defects in LAM with quantitative volumetric chest computed tomography (CT). MATERIALS AND METHODS CT examinations of 20 patients with confirmed LAM were evaluated with region-based quantification of lung parenchyma. Additionally, 10 consecutive patients were identified who had recently undergone CT imaging of the lung at our institution, in which no pathologies of the lung were found, to serve as a control group. Each lung was divided into three regions (upper, middle and lower thirds) with identical number of slices. In addition, we defined a "peel" and "core" of the lung comprising the 2 cm subpleural space and the remaining inner lung area. Computerized detection of lung volume and relative emphysema was performed with the PULMO 3D software (v3.42, Fraunhofer MEVIS, Bremen, Germany). This software package enables the quantification of emphysematous lung parenchyma by calculating the pixel index, which is defined as the ratio of lung voxels with a density <-950HU to the total number of voxels in the lung. RESULTS Cystic changes accounted for 0.1-39.1% of the total lung volume in patients with LAM. Disease manifestation in the central lung was significantly higher than in peripheral areas (peel median: 15.1%, core median: 20.5%; p=0.001). Lower thirds of lung parenchyma showed significantly less cystic changes than upper and middle lung areas combined (lower third: median 13.4, upper and middle thirds: median 19.0, p=0.001). CONCLUSION The distribution of cystic lesions in LAM is significantly more pronounced in the central lung compared to peripheral areas. There is a significant predominance of cystic changes in apical and intermediate lung zones compared to the lung bases.

Long-term data from the Swiss pulmonary hypertension registry.

BACKGROUND Registries are important for real-life epidemiology on different pulmonary hypertension (PH) groups. OBJECTIVE To provide long-term data of the Swiss PH registry of 1998-2012. METHODS PH patients have been classified into 5 groups and registered upon written informed consent at 5 university and 8 associated hospitals since 1998. New York Heart Association (NYHA) class, 6-min walk distance, hemodynamics and therapy were registered at baseline. Patients were regularly followed, and therapy and events (death, transplantation, endarterectomy or loss to follow-up) registered. The data were stratified according to the time of diagnosis into prevalent before 2000 and incident during 2000-2004, 2005-2008 and 2009-2012. RESULTS From 996 (53% female) PH patients, 549 had pulmonary arterial hypertension (PAH), 36 PH due to left heart disease, 127 due to lung disease, 249 to chronic thromboembolic PH (CTEPH) and 35 to miscellaneous PH. Age and BMI significantly increased over time, whereas hemodynamic severity decreased. Overall, event-free survival was 84, 72, 64 and 58% for the years 1-4 and similar for time periods since 2000, but better during the more recent periods for PAH and CTEPH. Of all PAH cases, 89% had target medical therapy and 43% combination therapy. Of CTEPH patients, 14 and 2% underwent pulmonary endarterectomy or transplantation, respectively; 87% were treated with PAH target therapy. CONCLUSION Since 2000, the incident Swiss PH patients registered were older, hemodynamically better and mostly treated with PAH target therapies. Survival has been better for PAH and CTEPH diagnosed since 2008 compared with earlier diagnosis or other classifications.

Pulmonary Artery-Vein Segmentation in Real and Synthetic CT Images = Segmentaci��n Arteria-Vena Pulmonares en Im��genes de CT Reales y Sint��ticas

La tomograf��a axial computerizada (TAC) es la modalidad de imagen m��dica preferente para el estudio de enfermedades pulmonares y el an��lisis de su vasculatura. La segmentaci��n general de vasos en pulm��n ha sido abordada en profundidad a lo largo de los ��ltimos a��os por la comunidad cient��fica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciaci��n entre irrigaciones arterial y venosa es a��n un problema abierto. De hecho, la separaci��n autom��tica de arterias y venas est�� considerado como uno de los grandes retos futuros del procesamiento de im��genes biom��dicas. La segmentaci��n arteria-vena (AV) permitir��a el estudio de ambas irrigaciones por separado, lo cual tendr��a importantes consecuencias en diferentes escenarios m��dicos y m��ltiples enfermedades pulmonares o estados patol��gicos. Caracter��sticas como la densidad, geometr��a, topolog��a y tama��o de los vasos sangu��neos podr��an ser analizados en enfermedades que conllevan remodelaci��n de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores espec��ficos que a��n hoy en d��permanecen ocultos. Esta diferenciaci��n entre arterias y venas tambi��n podr��a ayudar a la mejora y el desarrollo de m��todos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los ��rboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los ��rboles vasculares del pulm��n hace inabordable una separaci��n manual de ambas estructuras en un tiempo realista, fomentando a��n m��s la necesidad de dise��ar herramientas autom��ticas o semiautom��ticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva m��ltiples limitaciones en el desarrollo de sistemas de separaci��n AV, en los cuales son necesarias im��genes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el dise��o de im��genes sint��ticas de TAC pulmonar podr��a 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) est�� un��vocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales est��n fuertemente interrelacionados. Primero se describe el dise��o de una estrategia para generar, autom��ticamente, fantomas computacionales de TAC de pulm��n en humanos. Partiendo de conocimientos a priori, tanto biol��gicos como de caracter��sticas de imagen de CT, acerca de la topolog��a y relaci��n entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar v��as a��reas, arterias y venas pulmonares sint��ticas usando m��todos de crecimiento iterativo, que posteriormente se unen para formar un pulm��n simulado con caracter��sticas realistas. Estos casos sint��ticos, junto a im��genes reales de TAC sin contraste, han sido usados en el desarrollo de un m��todo completamente autom��tico de segmentaci��n/separaci��n AV. La estrategia comprende una primera extracci��n gen��rica de vasos pulmonares usando part��culas espacio-escala, y una posterior clasificaci��n AV de tales part��culas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje autom��tico) y la inclusi��n de informaci��n de conectividad entre part��culas. La validaci��n de los fantomas pulmonares se ha llevado a cabo mediante inspecci��n visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersi��n de estructuras y relaci��n entre arterias y v��as a��reas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sint��ticamente. La evaluaci��n del algoritmo de segmentaci��n AV est�� basada en distintas estrategias de comprobaci��n de la exactitud en la clasificaci��n de vasos, las cuales revelan una adecuada diferenciaci��n entre arterias y venas tanto en los casos reales como en los sint��ticos, abriendo as�� un amplio abanico de posibilidades en el estudio cl��nico de enfermedades cardiopulmonares y en el desarrollo de metodolog��as y nuevos algoritmos para el an��lisis de im��genes 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.

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.

An Analytical Workflow for Metagenomic Data and its Application to the Study of Chronic Obstructive Pulmonary Disease (COPD)

Metagenomics is the culture-independent study of genetic material obtained directly from environmental samples. It has become a realistic approach to understanding microbial communities thanks to advances in high-throughput DNA sequencing technologies over the past decade. Current research has shown that different sites of the human body house varied bacterial communities. There is a strong correlation between an individual���s microbial community profile at a given site and disease. Metagenomics is being applied more often as a means of comparing microbial profiles in biomedical studies. The analysis of the data collected using metagenomics can be quite challenging and there exist a plethora of tools for interpreting the results. An automatic analytical workflow for metagenomic analyses has been implemented and tested using synthetic datasets of varying quality. It is able to accurately classify bacteria by taxa and correctly estimate the richness and diversity of each set. The workflow was then applied to the study of the airways microbiome in Chronic Obstructive Pulmonary Disease (COPD). COPD is a progressive lung disease resulting in narrowing of the airways and restricted airflow. Despite being the third leading cause of death in the United States, little is known about the differences in the lung microbial community profiles of healthy individuals and COPD patients. Bronchoalveolar lavage (BAL) samples were collected from COPD patients, active or ex-smokers, and never smokers and sequenced by 454 pyrosequencing. A total of 56 individuals were recruited for the study. Substantial colonization of the lungs was found in all subjects and differentially abundant genera in each group were identified. These discoveries are promising and may further our understanding of how the structure of the lung microbiome is modified as COPD progresses. It is also anticipated that the results will eventually lead to improved treatments for COPD.

STRUCTURAL AND FUNCTIONAL CORRELATES OF EXERCISE VENTILATORY INEFFICIENCY IN CHRONIC OBSTRUCTIVE PULMONARY DISEASE PATIENTS WITH MILD-TO-MODERATE SPIROMETRIC ABNORMALITIES

Background: Individuals with chronic obstructive pulmonary disease (COPD) have higher than normal ventilatory equivalents for carbon dioxide (VE/VCO2) during exercise. There is growing evidence that emphysema on thoracic computed tomography (CT) scans is associated with poor exercise capacity in COPD patients with only mild-to-moderate airflow obstruction. We hypothesized that emphysema is an underlying cause of microvascular dysfunction and ventilatory inefficiency, which in turn contributes to reduced exercise capacity. We expected ventilatory inefficiency to be associated with a) the extent of emphysema; b) lower diffusing capacity for carbon monoxide; c) a reduced pulmonary blood flow response to exercise; and d) reduced exercise capacity. Methods: In a cross-sectional study, 19 subjects with mild-to-moderate COPD (mean �� SD FEV1= 82 �� 13% predicted, 12 GOLD grade 1) and 26 age-, sex-, and activity-matched controls underwent a ramp-incremental symptom-limited exercise test on a cycle ergometer. Ventilatory inefficiency was assessed by the minimum VE/VCO2 value (nadir). A subset of subjects also completed repeated constant work rate exercise bouts with non-invasive measurements of pulmonary blood flow. Emphysema was quantified as the percentage of attenuation areas below -950 Housefield Units on CT scans. An electronic scoresheet was used to keep track of emphysema sub-types. Results: COPD subjects typically had centrilobular emphysema (76.8 �� 10.1% of total emphysema) in the upper lobes (upper/lower lobe ratio= 0.82 �� 0.04). They had lower peak oxygen uptake (VO2), higher VE/VCO2 nadir and greater dyspnea scores than controls (p<0.05). Lower peak O2 and worse dyspnea were found in COPD subjects with VE/VCO2 nadirs ��� 30. COPD subjects had blunted increases in pulmonary blood flow from rest to iso-VO2 exercise (p<0.05). Higher VE/VCO2 nadir in COPD subjects correlated with emphysema severity (r= 0.63), which in turn correlated with reduced lung diffusing capacity (r= -0.72) and blunted changes in pulmonary blood flow from rest to exercise (r= -0.69) (p<0.01). Conclusions: Ventilation ���wasted��� in emphysematous areas is associated with reduced exercise ventilatory efficiency in mild-to-moderate COPD. Exercise ventilatory inefficiency links structure (emphysema) and function (gas transfer) to a key clinical outcome (reduced exercise capacity) in COPD patients with modest spirometric abnormalities.

Computed tomography evaluation of axial vertebral derotation in endoscopic anterior instrumentation for adolescent idiopathic scoliosis

Thoracoscopic instrumented anterior spinal fusion for adolescent idiopathic scoliosis (AIS) has clinical benefits that include reduced pulmonary morbidity, postoperative pain, and improved cosmesis. However, quantitative data on radiological improvement of vertebral rotation using this method is lacking. This study���s objectives were to measure preoperative and postoperative axial vertebral rotational deformity at the curve apex in endoscopically-treated anterior-instrumented scoliosis patients using CT, and assess the relevance of these findings to clinically measured chest wall rib hump deformity correction. This is the first quantitative CT study to confirm that endoscopic anterior instrumented fusion for AIS substantially improves axial vertebral body rotational deformity at the apex of the curve. The margin of correction of 43% compares favourably with historically published figures of 24% for patients with posterior all-hook-rod constructs. CT measurements correlated significantly to the clinical outcome of rib hump deformity correction.

When and how to treat pulmonary non-tuberculous mycobacterial diseases

Nontuberculous mycobacteria are ubiquitous environmental organisms that have been recognised as a cause of pulmonary infection for over 50 years. Traditionally patients have had underlying risk factors for development of disease; however the proportion of apparently immunocompetent patients involved appears to be rising. Not all patients culture-positive for mycobacteria will have progressive disease, making the diagnosis difficult, though criteria to aid in this process are available. The two main forms of disease are cavitary disease (usually involving the upper lobes) and fibronodular bronchiectasis (predominantly middle and lingular lobes). For patients with disease, combination antibiotic therapy for 12-24 months is generally required for successful treatment, and this may be accompanied by drug intolerances and side effects. Published success rates range from 30-82%. As the progression of disease is variable, for some patients, attention to pulmonary hygiene and underlying diseases without immediate antimycobacterial therapy may be more appropriate. Surgery can be a useful adjunct, though is associated with risks. Randomised controlled trials in well described patients would provide stronger evidence-based data to guide therapy of NTM lung diseases, and thus are much needed.

Typical accuracy and quality control of a process for creating CT-Based virtual bone models

A pragmatic method for assessing the accuracy and precision of a given processing pipeline required for converting computed tomography (CT) image data of bones into representative three dimensional (3D) models of bone shapes is proposed. The method is based on coprocessing a control object with known geometry which enables the assessment of the quality of resulting 3D models. At three stages of the conversion process, distance measurements were obtained and statistically evaluated. For this study, 31 CT datasets were processed. The final 3D model of the control object contained an average deviation from reference values of ���1.07��0.52 mm standard deviation (SD) for edge distances and ���0.647��0.43 mm SD for parallel side distances of the control object. Coprocessing a reference object enables the assessment of the accuracy and precision of a given processing pipeline for creating CTbased 3D bone models and is suitable for detecting most systematic or human errors when processing a CT-scan. Typical errors have about the same size as the scan resolution.

Image acquisition and manipulation protocols for CT-PET fusion to improve the accuracy of gross tumour volume localisation for 3D conformal radiotherapy for lung cancer

Aims: To develop clinical protocols for acquiring PET images, performing CT-PET registration and tumour volume definition based on the PET image data, for radiotherapy for lung cancer patients and then to test these protocols with respect to levels of accuracy and reproducibility. Method: A phantom-based quality assurance study of the processes associated with using registered CT and PET scans for tumour volume definition was conducted to: (1) investigate image acquisition and manipulation techniques for registering and contouring CT and PET images in a radiotherapy treatment planning system, and (2) determine technology-based errors in the registration and contouring processes. The outcomes of the phantom image based quality assurance study were used to determine clinical protocols. Protocols were developed for (1) acquiring patient PET image data for incorporation into the 3DCRT process, particularly for ensuring that the patient is positioned in their treatment position; (2) CT-PET image registration techniques and (3) GTV definition using the PET image data. The developed clinical protocols were tested using retrospective clinical trials to assess levels of inter-user variability which may be attributed to the use of these protocols. A Siemens Somatom Open Sensation 20 slice CT scanner and a Philips Allegro stand-alone PET scanner were used to acquire the images for this research. The Philips Pinnacle3 treatment planning system was used to perform the image registration and contouring of the CT and PET images. Results: Both the attenuation-corrected and transmission images obtained from standard whole-body PET staging clinical scanning protocols were acquired and imported into the treatment planning system for the phantom-based quality assurance study. Protocols for manipulating the PET images in the treatment planning system, particularly for quantifying uptake in volumes of interest and window levels for accurate geometric visualisation were determined. The automatic registration algorithms were found to have sub-voxel levels of accuracy, with transmission scan-based CT-PET registration more accurate than emission scan-based registration of the phantom images. Respiration induced image artifacts were not found to influence registration accuracy while inadequate pre-registration over-lap of the CT and PET images was found to result in large registration errors. A threshold value based on a percentage of the maximum uptake within a volume of interest was found to accurately contour the different features of the phantom despite the lower spatial resolution of the PET images. Appropriate selection of the threshold value is dependant on target-to-background ratios and the presence of respiratory motion. The results from the phantom-based study were used to design, implement and test clinical CT-PET fusion protocols. The patient PET image acquisition protocols enabled patients to be successfully identified and positioned in their radiotherapy treatment position during the acquisition of their whole-body PET staging scan. While automatic registration techniques were found to reduce inter-user variation compared to manual techniques, there was no significant difference in the registration outcomes for transmission or emission scan-based registration of the patient images, using the protocol. Tumour volumes contoured on registered patient CT-PET images using the tested threshold values and viewing windows determined from the phantom study, demonstrated less inter-user variation for the primary tumour volume contours than those contoured using only the patient���s planning CT scans. Conclusions: The developed clinical protocols allow a patient���s whole-body PET staging scan to be incorporated, manipulated and quantified in the treatment planning process to improve the accuracy of gross tumour volume localisation in 3D conformal radiotherapy for lung cancer. Image registration protocols which factor in potential software-based errors combined with adequate user training are recommended to increase the accuracy and reproducibility of registration outcomes. A semi-automated adaptive threshold contouring technique incorporating a PET windowing protocol, accurately defines the geometric edge of a tumour volume using PET image data from a stand alone PET scanner, including 4D target volumes.

Application of micro CT and computation modeling in bone tissue engineering

Computer aided technologies, medical imaging, and rapid prototyping has created new possibilities in biomedical engineering. The systematic variation of scaffold architecture as well as the mineralization inside a scaffold/bone construct can be studied using computer imaging technology and CAD/CAM and micro computed tomography (CT). In this paper, the potential of combining these technologies has been exploited in the study of scaffolds and osteochondral repair. Porosity, surface area per unit volume and the degree of interconnectivity were evaluated through imaging and computer aided manipulation of the scaffold scan data. For the osteochondral model, the spatial distribution and the degree of bone regeneration were evaluated. In this study the versatility of two softwares Mimics (Materialize), CTan and 3D realistic visualization (Skyscan) were assessed, too.

Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models

Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15mm while the MRI-based models contained an average error of 0.23mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system���s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

The 'obesity paradox' in chronic obstructive pulmonary disease

Poor nutritional status in chronic obstructive pulmonary disease (COPD) is associated with increased mortality independently of disease-severity (Collins et al).1 Epidemiological studies have suggested a protective role of obesity against mortality in COPD (Vestbo et al)2 which is contrary to data from the general population where obesity is associated with decreased life expectancy. This relationship has been referred to as the ���obesity paradox��� and has been demonstrated in a number of chronic wasting conditions (Kalantar-Zadeh et al).3 This study investigated the existence of the obesity paradox in outpatients with COPD by examining the effect of body mass index (BMI) on 1-year healthcare use and clinical outcome in terms of hospital admission rates, length of hospital stay, outpatient appointments and mortality. BMI was assessed in 424 outpatients with COPD, with measurements performed by specialist respiratory nurses during outpatient clinics. 1-year healthcare use was retrospectively collected from the date of BMI measurement. Abstract S163 Table 1 Patients classified as overweight (25.0���29.9���kg/m2) or obese (>30���kg/m2) experienced significantly fewer emergency hospital admissions, as well as a reduced length of hospital stay, in comparison to normal weight (20.0���24.9���kg/m2) or underweight (<20���kg/m2) outpatients. There was a significant negative trend between BMI classification and mortality. This study supports the existence of the ���obesity paradox��� in COPD, not only in relation to reduced 1���year mortality rates but also in terms of reduced emergency hospital admissions and reduced length of hospital stay.