Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Using participatory action research for heart self care amongst indigenous patients

This paper describes the initial phases of the Fluid Watchers Pacific Rim project: a participatory action research project that involves developing and trialling an iPad app to provide monitoring and self-care for Indigenous Australians with heart failure. The development phase involved working with health experts, an IT team and Indigenous heart-failure patients through three cycles of development and critical reflection. This was followed by a small pilot study to examine the app’s effectiveness. In this paper, the researchers explain why IT-supported health education can be successful in decreasing re-hospitalisation and improving self-management skills. They describe the steps they took to ensure community participation and ownership of the project and present the findings of their pilot study. This pilot project suggests that an iPad app may be a practical and successful way to provide health-care support for Indigenous Australian heart-failure patients.

Implementation and removal of an affirmative-action quota : the impact on task assignment and workers’ skill acquisition

Both the United States and Canada have federal legislation that attempts to address employment inequities across specific target groups. The US has a long tradition of affirmative action, dating back to President Kennedy’s 1961 Executive Order; Canada enacted its Employment Equity Act in 1986. Employment Equity/Affirmative Action policy has attracted significant controversy, with high profile court cases and the repeal of state/provincial legislation. Coate and Loury (1993) examine the theoretical impact of introducing affirmative action. Unfortunately the theoretical impact of affirmative action is ambiguous. The current paper employs a laboratory experiment to shed empirical light on this theoretical ambiguity.

Shortfalls in malnutrition coding : a mandate for action

The International Classification of Diseases, Version 10, Australian modification (ICD-10- AM) is commonly used to classify diseases in hospital patients. ICD-10-AM defines malnutrition as “BMI < 18.5 kg/m2 or unintentional weight loss of ≥ 5% with evidence of suboptimal intake resulting in subcutaneous fat loss and/or muscle wasting”. The Australasian Nutrition Care Day Survey (ANCDS) is the most comprehensive survey to evaluate malnutrition prevalence in acute care patients from Australian and New Zealand hospitals1. This study determined if malnourished participants were assigned malnutritionrelated codes as per ICD-10-AM. The ANCDS recruited acute care patients from 56 hospitals. Hospital-based dietitians evaluated participants’ nutritional status using BMI and Subjective Global Assessment (SGA). In keeping with the ICD-10-AM definition, malnutrition was defined as BMI <18.5kg/m2, SGA-B (moderately malnourished) or SGA-C (severely malnourished). After three months, in this prospective cohort study, hospitals’ health information/medical records department provided coding results for malnourished participants. Although malnutrition was prevalent in 32% (n= 993) of the cohort (N= 3122), a significantly small number were coded for malnutrition (n= 162, 16%, p<0.001). In 21 hospitals, none of the malnourished participants were coded. This is the largest study to provide a snapshot of malnutrition-coding in Australian and New Zealand hospitals. Findings highlight gaps in malnutrition documentation and/or subsequent coding, which could potentially result in significant loss of casemix-related revenue for hospitals. Dietitians must lead the way in developing structured processes for malnutrition identification, documentation and coding.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

The function and mechanisms of action of ghrelin and obestatin in ovarian cancer

In this study, we have demonstrated that the preproghrelin derived hormones, ghrelin and obestatin, may play a role in ovarian cancer. Ghrelin and obestatin stimulated an increase in cell migration in ovarian cancer cell lines and may play a role in cancer progression. Ovarian cancer is the leading cause of death among gynaecological cancers and is the sixth most common cause of cancer-related deaths in women in developed countries. As ovarian cancer is difficult to diagnose at a low tumour grade, two thirds of ovarian cancers are not diagnosed until the late stages of cancer development resulting in a poor prognosis for the patient. As a result, current treatment methods are limited and not ideal. There is an urgent need for improved diagnostic markers, as well better therapeutic approaches and adjunctive therapies for this disease. Ghrelin has a number of important physiological effects, including roles in appetite regulation and the stimulation of growth hormone release. It is also involved in regulating the immune, cardiovascular and reproductive systems and regulates sleep, memory and anxiety, and energy metabolism. Over the last decade, the ghrelin axis, (which includes the hormones ghrelin and obestatin and their receptors), has been implicated in the pathogenesis of many human diseases and it may t may also play an important role in the development of cancer. Ghrelin is a 28 amino acid peptide hormone that exists in two forms. Acyl ghrelin (usually referred to as ghrelin), has a unique n-octanoic acid post-translational modification (which is catalysed by ghrelin O-acyltransferase, GOAT), and desacyl ghrelin, which is a non-octanoylated form. Octanoylated ghrelin acts through the growth hormone secretagogue receptor type 1a (GHSR1a). GHSR1b, an alternatively spliced isoform of GHSR, is C-terminally truncated and does not bind ghrelin. Ghrelin has been implicated in the pathophysiology of a number of diseases Obestatin is a 23 amino acid, C-terminally amidated peptide which is derived from preproghrelin. Although GPR39 was originally thought to be the obestatin receptor this has been disproven, and its receptor remains unknown. Obestatin may have as diverse range of roles as ghrelin. Obestatin improves memory, inhibits thirst and anxiety, increases pancreatic juice secretion and has cardioprotective effects. Obestatin also has been shown to regulate cell proliferation, differentiation and apoptosis in some cell types. Prior to this study, little was known regarding the functions and mechanisms of action ghrelin and obestatin in ovarian cancer. In this study it was demonstrated that the full length ghrelin, GHSR1b and GOAT mRNA transcripts were expressed in all of the ovarian-derived cell lines examined (SKOV3, OV-MZ-6 and hOSE 17.1), however, these cell lines did not express GHSR1a. Ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for ghrelin, obestatin, and GOAT, but not GHSR1a, or GHSR1b. No correlations between cancer grade and the level of expression of these transcripts were observed. This study demonstrated for the first time that both ghrelin and obestatin increase cell migration in ovarian cancer cell lines. Treatment with ghrelin (for 72 hours) significantly increased cell migration in the SKOV3 and OV-MZ-6 ovarian cancer cell lines. Ghrelin (100 nM) stimulated cell migration in the SKOV3 (2.64 +/- 1.08 fold, p <0.05) and OV-MZ-6 (1.65 +/- 0.31 fold, p <0.05) ovarian cancer cell lines, but not in the representative normal cell line hOSE 17.1. This increase in migration was not accompanied by an increase in cell invasion through Matrigel. In contrast to other cancer types, ghrelin had no effect on proliferation. Ghrelin treatment (10nM) significantly decreased attachment of the SKOV3 ovarian cancer cell line to collagen IV (24.7 +/- 10.0 %, p <0.05), however, there were no changes in attachment to the other extracellular matrix molecules (ECM) tested (fibronectin, vitronectin and collagen I), and there were no changes in attachment to any of the ECM molecules in the OV-MZ-6 or hOSE 17.1 cell lines. It is, therefore, unclear if ghrelin plays a role in cell attachment in ovarian cancer. As ghrelin has previously been demonstrated to signal through the ERK1/2 pathway in cancer, we investigated ERK1/2 signalling in ovarian cancer cell lines. In the SKOV3 ovarian cancer cell line, a reduction in ERK1/2 phosphorylation (0.58 fold +/- 0.23, p <0.05) in response to 100 nM ghrelin treatment was observed, while no significant change in ERK1/2 signalling was seen in the OV-MZ-6 cell line with treatment. This suggests that this pathway is unlikely to be involved in mediating the increased migration seen in the ovarian cancer cell lines with ghrelin treatment. In this study ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for obestatin, however, no correlation between cancer grade and level of obestatin transcript expression was observed. In the ovarian-derived cell lines studied (SKOV3, OV-MZ-6 and hOSE 17.1) it was demonstrated that the full length preproghrelin mRNA transcripts were expressed in all cell lines, suggesting they have the ability to produce mature obestatin. This is the first study to demonstrate that obestatin stimulates cell migration and cell invasion. Obestatin induced a significant increase in migration in the SKOV3 ovarian cancer cell line with 10 nM (2.80 +/- 0.52 fold, p <0.05) and 100 nM treatments (3.12 +/- 0.68 fold, p <0.05) and in the OV-MZ-6 cancer cell line with 10 nM (2.04 +/- 0.10 fold, p <0.01) and 100 nM treatments (2.00 +/- 0.37 fold, p <0.05). Obestatin treatment did no affect cell migration in the hOSE 17.1normal ovarian epithelial cell line. Obestatin treatment (100 nM) also stimulated a significant increase in cell invasion in the OV-MZ-6 ovarian cancer cell line (1.45 fold +/- 0.13, p <0.05) and in the hOSE17.1 normal ovarian cell line cells (1.40 fold +/- 0.04 and 1.55 fold +/- 0.05 respectively, p <0.01) with 10 nM and 100 nM treatments. Obestatin treatment did not stimulate cell invasion in the SKOV3 ovarian cancer cell line. This lack of obestatin-stimulated invasion in the SKOV3 cell line may be a cell line specific result. In this study, obestatin did not stimulate cell proliferation in the ovarian cell lines and it has previously been shown to have no effect on cell proliferation in the BON-1 pancreatic neuroendocrine and GC rat somatotroph tumour cell lines. In contrast, obestatin has been shown to affect cell proliferation in gastric and thyroid cancer cell lines, and in some normal cell lines. Obestatin also had no effect on attachment of any of the cell lines to any of the ECM components tested (fibronectin, vitronectin, collagen I and collagen IV). The mechanism of action of obestatin was investigated further using a two dimensional-difference in gel electrophoresis (2D-DIGE) proteomic approach. After treatment with obestating (0, 10 and 100 nM), SKOV3 ovarian cancer and hOSE 17.1 normal ovarian cell lines were collected and 2D-DIGE analysis and mass spectrometry were performed to identify proteins that were differentially expressed in response to treatment. Twenty-six differentially expressed proteins were identified and analysed using Ingenuity Pathway Analysis (IPA). This linked 16 of these proteins in a network. The analysis suggested that the ERK1/2 MAPK pathway was a major mediator of obestatin action. ERK1/2 has previously been shown to be associated with obestatin-stimulated cell proliferation and with the anti-apoptotic effects of obestatin. Activation of the ERK1/2 signalling pathway by obestatin was, therefore, investigated in the SKOV3 and OV-MZ-6 ovarian cancer cell lines using anti-active antibodies and Western immunoblots. Obestatin treatment significantly decreased ERK1/2 phosphorylation at higher obestatin concentrations in both the SKOV3 (100 nM and 1000 nM) and OV-MZ-6 (1000 nM) cell lines compared to the untreated controls. Currently, very little is known about obestatin signalling in cancer. This thesis has demonstrated for the first time that the ghrelin axis may play a role in ovarian cancer migration. Ghrelin and obestatin increased cell migration in ovarian cancer cell lines, indicating that they may be a useful target for therapies that reduce ovarian cancer progression. Further studies investigating the role of the ghrelin axis using in vivo ovarian cancer metastasis models are warranted.

Motivation during videogame play : analysing player experience in terms of cognitive action

This paper describes a method for analysing videogames based on game activities. It examines the impact of these activities on the player experience. The research approach applies heuristic checklists that deconstruct games in terms of cognitive processes that players engage in during gameplay (e.g., addressing goals, interpreting feedback). For this study we examined three puzzle games, Portal 2, I-Fluid and Braid. The Player Experience of Need Satisfaction (PENS) survey is used to measure player experience following gameplay. Cognitive action provided within games is examined in light of reported player experiences to determine the extent to which these activities influence players’ feelings of competence, autonomy, intuitive control and presence. Findings indicate that the positive experiences are directly influenced by game activity design. Our study also demonstrates the value of expert review in deconstructing gameplay activity as a means of providing direction for game design that enhances the player experience.

A simplified approach for calculating the moments of action for linear reaction-diffusion equations

The mean action time is the mean of a probability density function that can be interpreted as a critical time, which is a finite estimate of the time taken for the transient solution of a reaction-diffusion equation to effectively reach steady state. For high-variance distributions, the mean action time under-approximates the critical time since it neglects to account for the spread about the mean. We can improve our estimate of the critical time by calculating the higher moments of the probability density function, called the moments of action, which provide additional information regarding the spread about the mean. Existing methods for calculating the nth moment of action require the solution of n nonhomogeneous boundary value problems which can be difficult and tedious to solve exactly. Here we present a simplified approach using Laplace transforms which allows us to calculate the nth moment of action without solving this family of boundary value problems and also without solving for the transient solution of the underlying reaction-diffusion problem. We demonstrate the generality of our method by calculating exact expressions for the moments of action for three problems from the biophysics literature. While the first problem we consider can be solved using existing methods, the second problem, which is readily solved using our approach, is intractable using previous techniques. The third problem illustrates how the Laplace transform approach can be used to study coupled linear reaction-diffusion equations.

Automatic segmentation of choroidal thickness in optical coherence tomography

The assessment of choroidal thickness from optical coherence tomography (OCT) images of the human choroid is an important clinical and research task, since it provides valuable information regarding the eye’s normal anatomy and physiology, and changes associated with various eye diseases and the development of refractive error. Due to the time consuming and subjective nature of manual image analysis, there is a need for the development of reliable objective automated methods of image segmentation to derive choroidal thickness measures. However, the detection of the two boundaries which delineate the choroid is a complicated and challenging task, in particular the detection of the outer choroidal boundary, due to a number of issues including: (i) the vascular ocular tissue is non-uniform and rich in non-homogeneous features, and (ii) the boundary can have a low contrast. In this paper, an automatic segmentation technique based on graph-search theory is presented to segment the inner choroidal boundary (ICB) and the outer choroidal boundary (OCB) to obtain the choroid thickness profile from OCT images. Before the segmentation, the B-scan is pre-processed to enhance the two boundaries of interest and to minimize the artifacts produced by surrounding features. The algorithm to detect the ICB is based on a simple edge filter and a directional weighted map penalty, while the algorithm to detect the OCB is based on OCT image enhancement and a dual brightness probability gradient. The method was tested on a large data set of images from a pediatric (1083 B-scans) and an adult (90 B-scans) population, which were previously manually segmented by an experienced observer. The results demonstrate the proposed method provides robust detection of the boundaries of interest and is a useful tool to extract clinical data.

Ginger - mechanism of action in chemotherapy-induced nausea and vomiting: A review

Despite advances in anti-emetic therapy, chemotherapy-induced nausea and vomiting (CINV) still poses a significant burden to patients undergoing chemotherapy. Nausea, in particular, is still highly prevalent in this population. Ginger has been traditionally used as a folk remedy for gastrointestinal complaints and has been suggested as a viable adjuvant treatment for nausea and vomiting in the cancer context. Substantial research has revealed ginger to possess properties that could exert multiple beneficial effects on chemotherapy patients who experience nausea and vomiting. Bioactive compounds within the rhizome of ginger, particularly the gingerol and shogaol class of compounds, interact with several pathways that are directly implicated in CINV in addition to pathways that could play secondary roles by exacerbating symptoms. These properties include 5-HT3, substance P and acetylcholine receptor antagonism; anti-inflammatory properties; and modulation of cellular redox signalling, vasopressin release, gastrointestinal motility, and gastric emptying rate. This review outlines these proposed mechanisms by discussing the results of clinical, in vitro and animal studies both within the chemotherapy context and in other relevant fields. The evidence presented in this review indicates that ginger possesses multiple properties that could be beneficial in reducing chemotherapy-induced nausea and vomiting.

INFORMAS (International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support) : overview and key principles

Non-communicable diseases (NCDs) dominate disease burdens globally and poor nutrition increasingly contributes to this global burden. Comprehensive monitoring of food environments, and evaluation of the impact of public and private sector policies on food environments is needed to strengthen accountability systems to reduce NCDs. The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) is a global network of public-interest organizations and researchers that aims to monitor, benchmark and support public and private sector actions to create healthy food environments and reduce obesity, NCDs and their related inequalities. The INFORMAS framework includes two ‘process’ modules, that monitor the policies and actions of the public and private sectors, seven ‘impact’ modules that monitor the key characteristics of food environments and three ‘outcome’ modules that monitor dietary quality, risk factors and NCD morbidity and mortality. Monitoring frameworks and indicators have been developed for 10 modules to provide consistency, but allowing for stepwise approaches (‘minimal’, ‘expanded’, ‘optimal’) to data collection and analysis. INFORMAS data will enable benchmarking of food environments between countries, and monitoring of progress over time within countries. Through monitoring and benchmarking, INFORMAS will strengthen the accountability systems needed to help reduce the burden of obesity, NCDs and their related inequalities.

Action and Adventure

This chapter discusses the history of action and adventure films in Australian cinema. It focuses on those films starring Australian actors who have gained international fame, and on those films featuring a female protagonist.

Image segmentation and pose estimation of humans in video

This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

Footprints to pathways : reconciliation action planning in industry to sustain Indigenous employment in Queensland

This paper provides an introductory discussion to a study focusing on industry Reconciliation Action Plans (RAP) and sustaining Indigenous employment in Queensland. Indigenous people continue to experience deep and persistent disadvantage in employment, which limits their life prospects (McLachlan, Gilgillan & Gordon, 2013). A major contributing factor to this detriment is irregular employment and or unemployment. A reasonable standard of living has been found to be determined by access to economic resources such as income and wealth. Denial of this access, denies access to income streams, social status, and engagement in meaningful activities. Hence, job loss and joblessness are triggers of disadvantage (McLachlan, et al., 2013). For young Indigenous people, lack of access has lasting effects particularly if they have multiple characteristics that place them at risk of disadvantage. The project aims to develop knowledge and understanding of Industry RAPs mediate employment opportunities for Indigenous people and how young Indigenous people conceive of their employment options and the processes by which employers can best support Indigenous people. It adopts two theoretical frameworks to investigate the aim of the study : (1) Lave and Wenger’s (1991) theory of communities of practice and, (2) Sen’s (1993) capability approach which provides a structure for examining individual well-being in the context of societal inequality. This paper discusses the first research question of the study: What are Industry Reconciliation Action Plans? What is included in RAPs? Why do Industries develop RAPs? How do RAPs attract, recruit, retain, and tenure Indigenous people? The project’s significance rests with its focus on Industry, employers, policies and practices that aid the attraction and retention of Indigenous people in employment.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.