Overweight and obesity in Australia: The 1999-2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab)

Objective: To measure the prevalence of obesity in Australian adults and to examine the associations of obesity with socioeconomic and lifestyle factors. Design: AusDiab, a cross-sectional study conducted between May 1999 and December 2000, involved participants from 42 randomly selected districts throughout Australia. Participants: Of 20 347 eligible people aged greater than or equal to 25 years who completed a household interview, 11247 attended the physical examination at local survey sites (response rate, 55%). Main outcome measures: Overweight and obesity defined by body mass index (BMI; kg/m(2)) and waist circumference (cm); sociodemographic factors (including smoking, physical activity and television viewing time). Results: The prevalence of overweight and obesity (BMI greater than or equal to 25.0 kg/m(2); waist circumference greater than or equal to 80.0 cm [women] or greater than or equal to 94.0 cm [men]) in both sexes was almost 60%, defined by either BMI or waist circumference. The prevalence of obesity was 2.5 times higher than in 1980. Using waist circumference, the prevalence of obesity was higher in women than men (34.1% v 26.8%; P < 0.01). Lower educational status, higher television viewing time and lower physical activity time were each strongly associated with obesity, with television viewing time showing a stronger relationship than physical activity time. Conclusions: The prevalence of obesity in Australia has more than doubled in the past 20 years. Strong positive associations between obesity and each of television viewing time and lower physical activity time confirm the influence of sedentary lifestyles on obesity, and underline the potential benefits of reducing sedentary behaviour, as well as increasing physical activity, to curb the obesity epidemic.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Lifestyle factors influence in the frequency in buccal micronucleus

Genomic damage is probably the most important fundamental cause of development and degenerative disease. It is also well established that genomic damage is produced by environmental exposure to genotoxins, medical procedures (e.g. radiation and chemicals), micronutrient deficiency (e.g. folate), lifestyle factors (e.g. alcohol, smoking, drugs and stress), and genetic factors such as inherited defects in DNA metabolism and/or repair. Tobacco smoke has been associated to a higher risk of development of cancer, especially in the oral cavity, larynx and lungs, as these are places of direct contact with many carcinogenic tobacco’s compounds. Alcohol is definitely a recognized agent that influence cells in a genotoxic form, been citied as a strong agent with potential in the development of carcinogenic lesions. Epidemiological evidence points to a strong synergistic effect between cigarette smoking and alcohol consumption in the induction of cancers in the oral cavity. Approximately 90% of human cancers originate from epithelial cells. Therefore, it could be argued that oral epithelial cells represent a preferred target site for early genotoxic events induced by carcinogenic agents entering the body via inhalation and ingestion. The MN assay in buccal cells was also used to study cancerous and precancerous lesions and to monitor the effects of a number of chemopreventive agents.

Modelling and segmentation of the vocal tract during speech production by using deformable models in magnetic resonance images

The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.

Lifestyle factors, direct and indirect costs for a Brazilian airline company

OBJECTIVE To analyze lifestyle risk factors related to direct healthcare costs and the indirect costs due to sick leave among workers of an airline company in Brazil. METHODS In this longitudinal 12-month study of 2,201 employees of a Brazilian airline company, the costs of sick leave and healthcare were the primary outcomes of interest. Information on the independent variables, such as gender, age, educational level, type of work, stress, and lifestyle-related factors (body mass index, physical activity, and smoking), was collected using a questionnaire on enrolment in the study. Data on sick leave days were available from the company register, and data on healthcare costs were obtained from insurance records. Multivariate linear regression analysis was used to investigate the association between direct and indirect healthcare costs with sociodemographic, work, and lifestyle-related factors. RESULTS Over the 12-month study period, the average direct healthcare expenditure per worker was US$505.00 and the average indirect cost because of sick leave was US$249.00 per worker. Direct costs were more than twice the indirect costs and both were higher in women. Body mass index was a determinant of direct costs and smoking was a determinant of indirect costs. CONCLUSIONS Obesity and smoking among workers in a Brazilian airline company were associated with increased health costs. Therefore, promoting a healthy diet, physical activity, and anti-tobacco campaigns are important targets for health promotion in this study population.

Risk of dependence associated with health, social support, and lifestyle

OBJECTIVE To analyze the prevalence of individuals at risk of dependence and its associated factors.METHODS The study was based on data from the Catalan Health Survey, Spain conducted in 2010 and 2011. Logistic regression models from a random sample of 3,842 individuals aged ≥ 15 years were used to classify individuals according to the state of their personal autonomy. Predictive models were proposed to identify indicators that helped distinguish dependent individuals from those at risk of dependence. Variables on health status, social support, and lifestyles were considered.RESULTS We found that 18.6% of the population presented a risk of dependence, especially after age 65. Compared with this group, individuals who reported dependence (11.0%) had difficulties performing activities of daily living and had to receive support to perform them. Habits such as smoking, excessive alcohol consumption, and being sedentary were associated with a higher probability of dependence, particularly for women.CONCLUSIONS Difficulties in carrying out activities of daily living precede the onset of dependence. Preserving personal autonomy and function without receiving support appear to be a preventive factor. Adopting an active and healthy lifestyle helps reduce the risk of dependence.

Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

Influence of cardiorespiratory fitness and parental lifestyle on adolescents' abdominal obesity

The aims of this study were (1) to analyse the influence of cardiorespiratory fitness (CRF) and parental overweight status (POS) and socioeconomic status (SES) on abdominal obesity. This study was comprised of 779 adolescents (12-18 years). Waist-height ratio (WHtR), 20 m shuttle-run test to ascertain CRF, POS according to World Health Organization recommendations and SES of parents using level of education were analysed. Using WHtR, the prevalence of abdominal obesity was 21.3% (23.5% girls and 17.9% boys; p = 0.062). Regardless of gender, participants who belonged to the WHtR risk group had significantly (p ≤ 0.05) lower CRF scores than the WHtR non-risk group; 84.4% of girls who belonged to the WHtR risk group had one or two overweight parents (p ≤ 0.05). Boys with low CRF (OR: 6.43; CI: 3.33-12.39) were more likely to belong to the WHtR risk group compared with their lean peers. Girls with low CRF (OR: 1.78; CI: 1.14-2.78) and with at least one overweight parent (OR: 2.50; CI: 1.07-5.85) or two overweight parents (OR: 4.90; CI: 2.08-11.54) were associated with the risk of abdominal obesity. This study highlights the influence of adolescents' family on abdominal obesity, especially in girls. Further, the data suggested that low CRF was a strong predictor of risk values of abdominal obesity in adolescence.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Unsupervised classification of remote sensing images combining Self Organizing Maps and segmentation techniques

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Cluster analysis and segmentation of Global M&A transactions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics