Stem cells as tools in regenerative therapy for retinal degeneration

OBJECTIVE: To describe the use of stem cells (SCs) for regeneration of retinal degenerations. Regenerative medicine intends to provide therapies for severe injuries or chronic diseases where endogenous repair does not sufficiently restore the tissue. Pluripotent SCs, with their capacity to give rise to specialized cells, are the most promising candidates for clinical application. Despite encouraging results, a combination with up-to-date tissue engineering might be critical for ultimate success. DESIGN: The focus is on the use of SCs for regeneration of retinal degenerations. Cell populations include embryonic, neural, and bone marrow-derived SCs, and engineered grafts will also be described. RESULTS: Experimental approaches have successfully replaced damaged photoreceptors and retinal pigment epithelium using endogenous and exogenous SCs. CONCLUSIONS: Stem cells have the potential to significantly impact retinal regeneration. A combination with bioengineering may bear even greater promise. However, ethical and scientific issues have yet to be solved.

ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms.

THERMAL CHARACTERIZATION OF A GASOLINE TURBOCHARGED DIRECT INJECTION (GTDI) ENGINE UTILIZING LEAN OPERATION AND EXHAUST GAS RECIRCULATION (EGR)

The push for improved fuel economy and reduced emissions has led to great achievements in engine performance and control. These achievements have increased the efficiency and power density of gasoline engines dramatically in the last two decades. With the added power density, thermal management of the engine has become increasingly important. Therefore it is critical to have accurate temperature and heat transfer models as well as data to validate them. With the recent adoption of the 2025 Corporate Average Fuel Economy(CAFE) standard, there has been a push to improve the thermal efficiency of internal combustion engines even further. Lean and dilute combustion regimes along with waste heat recovery systems are being explored as options for improving efficiency. In order to understand how these technologies will impact engine performance and each other, this research sought to analyze the engine from both a 1st law energy balance perspective, as well as from a 2nd law exergy analysis. This research also provided insights into the effects of various parameters on in-cylinder temperatures and heat transfer as well as provides data for validation of other models. It was found that the engine load was the dominant factor for the energy distribution, with higher loads resulting in lower coolant heat transfer and higher brake work and exhaust energy. From an exergy perspective, the exhaust system provided the best waste heat recovery potential due to its significantly higher temperatures compared to the cooling circuit. EGR and lean combustion both resulted in lower combustion chamber and exhaust temperatures; however, in most cases the increased flow rates resulted in a net increase in the energy in the exhaust. The exhaust exergy, on the other hand, was either increased or decreased depending on the location in the exhaust system and the other operating conditions. The effects of dilution from lean operation and EGR were compared using a dilution ratio, and the results showed that lean operation resulted in a larger increase in efficiency than the same amount of dilution with EGR. Finally, a method for identifying fuel spray impingement from piston surface temperature measurements was found. Note: The material contained in this section is planned for submission as part of a journal article and/or conference paper in the future.

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.

Cold-Start Emissions testing of Snowmobiles Using Ethanol and Gasoline

Increasing prices for fuel with depletion and instability in foreign oil imports has driven the importance for using alternative and renewable fuels. The alternative fuels such as ethanol, methanol, butyl alcohol, and natural gas are of interest to be used to relieve some of the dependence on oil for transportation. The renewable fuel, ethanol which is made from the sugars of corn, has been used widely in fuel for vehicles in the United States because of its unique qualities. As with any renewable fuel, ethanol has many advantages but also has disadvantages. Cold startability of engines is one area of concern when using ethanol blended fuel. This research was focused on the cold startability of snowmobiles at ambient temperatures of 20 °F, 0 °F, and -20 °F. The tests were performed in a modified 48 foot refrigerated trailer which was retrofitted for the purpose of cold-start tests. Pure gasoline (E0) was used as a baseline test. A splash blended ethanol and gasoline mixture (E15, 15% ethanol and 85% gasoline by volume) was then tested and compared to the E0 fuel. Four different types of snowmobiles were used for the testing including a Yamaha FX Nytro RTX four-stroke, Ski-doo MX Z TNT 600 E-TEC direct injected two stroke, Polaris 800 Rush semi-direct injected two-stroke, and an Arctic Cat F570 carbureted two-stroke. All of the snowmobiles operate on open loop systems which means there was no compensation for the change in fuel properties. Emissions were sampled using a Sensors Inc. Semtech DS five gas emissions analyzer and engine data was recoded using AIM Racing Data Power EVO3 Pro and EVO4 systems. The recorded raw exhaust emissions included carbon monoxide (CO), carbon dioxide (CO2), total hydrocarbons (THC), and oxygen (O2). To help explain the trends in the emissions data, engine parameters were also recorded. The EVO equipment was installed on each vehicle to record the following parameters: engine speed, exhaust gas temperature, head temperature, coolant temperature, and test cell air temperature. At least three consistent tests to ensure repeatability were taken at each fuel and temperature combination so a total of 18 valid tests were taken on each snowmobile. The snowmobiles were run at operating temperature to clear any excess fuel in the engine crankcase before each cold-start test. The trends from switching from E0 to E15 were different for each snowmobile as they all employ different engine technologies. The Yamaha snowmobile (four-stroke EFI) achieved higher levels of CO2 with lower CO and THC emissions on E15. Engine speeds were fairly consistent between fuels but the average engine speeds were increased as the temperatures decreased. The average exhaust gas temperature increased from 1.3-1.8% for the E15 compared to E0 due to enleanment. For the Ski-doo snowmobile (direct injected two-stroke) only slight differences were noted when switching from E0 to E15. This could possibly be due to the lean of stoichiometric operation of the engine at idle. The CO2 emissions decreased slightly at 20 °F and 0 °F for E15 fuel with a small difference at -20 °F. Almost no change in CO or THC emissions was noted for all temperatures. The only significant difference in the engine data observed was the exhaust gas temperature which decreased with E15. The Polaris snowmobile (semi-direct injected two-stroke) had similar raw exhaust emissions for each of the two fuels. This was probably due to changing a resistor when using E15 which changed the fuel map for an ethanol mixture (E10 vs. E0). This snowmobile operates at a rich condition which caused the engine to emit higher values of CO than CO2 along with exceeding the THC analyzer range at idle. The engine parameters and emissions did not increase or decrease significantly with decreasing temperature. The average idle engine speed did increase as the ambient temperature decreased. The Arctic Cat snowmobile (carbureted two-stroke) was equipped with a choke lever to assist cold-starts. The choke was operated in the same manor for both fuels. Lower levels of CO emissions with E15 fuel were observed yet the THC emissions exceeded the analyzer range. The engine had a slightly lower speed with E15.

Novel screening tools for latent tuberculosis: time to leave an old friend?

PURPOSE OF REVIEW: Therapeutic inhibition of tumour necrosis factor-alpha strongly increases the risk of reactivation in latent tuberculosis infection. Recent blood tests based on antigen-specific T cell response and measuring production of interferon-gamma, so called interferon-gamma release assays (IGRAs), are promising novel tools to identify infected patients. The performance of diagnostic testing for latent tuberculosis infection in patients with rheumatic diseases will be discussed. RECENT FINDINGS: In patients with rheumatoid arthritis, IGRAs are more sensitive and more specific than traditional tuberculin skin testing. They are unaffected by Bacillus-Calmette-Guérin vaccination and most nontuberculous mycobacteria. Most comparative studies show a better performance of the IGRAs than tuberculin skin testing in terms of a higher specificity. The rate of indeterminate results may be affected by glucocorticoids and the underlying disease but appears independent of disease-modifying antirheumatic drugs. Despite using identical Mycobacterium tuberculosis antigens, the two commercially available tests show differences in clinical performance. SUMMARY: The current information about the performance of the tuberculin skin testing and the IGRAs in the detection of latent tuberculosis infection in patients with rheumatic diseases strongly suggest a clinically relevant advantage of the IGRAs. Their use will help to reduce overuse and underuse of preventive treatment in tumour necrosis factor inhibition.

Virtopsy: forensic traumatology of the subcutaneous fatty tissue; multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) as diagnostic tools

Traumatic lesions of the subcutaneous fatty tissue provide important clues for forensic reconstruction. The interpretation of these patterns requires a precise description and recording of the position and extent of each lesion. During conventional autopsy, this evaluation is performed by dissecting the skin and subcutaneous tissues in successive layers. In this way, depending on the force and type of impact (right angle or tangent), several morphologically distinct stages of fatty tissue damage can be differentiated: perilobular hemorrhage (I), contusion (II), or disintegration (III) of the fat lobuli, and disintegration with development of a subcutaneous cavity (IV). In examples of virtopsy cases showing blunt trauma to the skin and fatty tissue, we analyzed whether these lesions can also be recorded and classified using multislice computed tomography (MSCT) and magnetic resonance imaging (MRI). MSCT has proven to be a valuable screening method to detect the lesions, but MRI is necessary in order to properly differentiate and classify the grade of damage. These noninvasive radiological diagnostic tools can be further developed to play an important role in forensic examinations, in particular when it comes to evaluating living trauma victims.

Meta-Environment and Executable Meta-Language using Smalltalk: an Experience Report

Object-oriented modelling languages such as EMOF are often used to specify domain specific meta-models. However, these modelling languages lack the ability to describe behavior or operational semantics. Several approaches have used a subset of Java mixed with OCL as executable meta-languages. In this experience report we show how we use Smalltalk as an executable meta-language in the context of the Moose reengineering environment. We present how we implemented EMOF and its behavioral aspects. Over the last decade we validated this approach through incrementally building a meta-described reengineering environment. Such an approach bridges the gap between a code-oriented view and a meta-model driven one. It avoids the creation of yet another language and reuses the infrastructure and run-time of the underlying implementation language. It offers an uniform way of letting developers focus on their tasks while at the same time allowing them to meta-describe their domain model. The advantage of our approach is that developers use the same tools and environment they use for their regular tasks. Still the approach is not Smalltalk specific but can be applied to language offering an introspective API such as Ruby, Python, CLOS, Java and C#.

PyGirl: Generating Whole-System VMs from High-Level Prototypes Using PyPy

Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.

Semiotic Analysis in the Study of Social Work

Research and professional practices have the joint aim of re-structuring the preconceived notions of reality. They both want to gain the understanding about social reality. Social workers use their professional competence in order to grasp the reality of their clients, while researchers’ pursuit is to open the secrecies of the research material. Development and research are now so intertwined and inherent in almost all professional practices that making distinctions between practising, developing and researching has become difficult and in many aspects irrelevant. Moving towards research-based practices is possible and it is easily applied within the framework of the qualitative research approach (Dominelli 2005, 235; Humphries 2005, 280). Social work can be understood as acts and speech acts crisscrossing between social workers and clients. When trying to catch the verbal and non-verbal hints of each others’ behaviour, the actors have to do a lot of interpretations in a more or less uncertain mental landscape. Our point of departure is the idea that the study of social work practices requires tools which effectively reveal the internal complexity of social work (see, for example, Adams & Dominelli & Payne 2005, 294 – 295). The boom of qualitative research methodologies in recent decades is associated with much profound the rupture in humanities, which is called the linguistic turn (Rorty 1967). The idea that language is not transparently mediating our perceptions and thoughts about reality, but on the contrary it constitutes it was new and even confusing to many social scientists. Nowadays we have got used to read research reports which have applied different branches of discursive analyses or narratologic or semiotic approaches. Although differences are sophisticated between those orientations they share the idea of the predominance of language. Despite the lively research work of today’s social work and the research-minded atmosphere of social work practice, semiotics has rarely applied in social work research. However, social work as a communicative practice concerns symbols, metaphors and all kinds of the representative structures of language. Those items are at the core of semiotics, the science of signs, and the science which examines people using signs in their mutual interaction and their endeavours to make the sense of the world they live in, their semiosis. When thinking of the practice of social work and doing the research of it, a number of interpretational levels ought to be passed before reaching the research phase in social work. First of all, social workers have to interpret their clients’ situations, which will be recorded in the files. In some very rare cases those past situations will be reflected in discussions or perhaps interviews or put under the scrutiny of some researcher in the future. Each and every new observation adds its own flavour to the mixture of meanings. Social workers have combined their observations with previous experience and professional knowledge, furthermore, the situation on hand also influences the reactions. In addition, the interpretations made by social workers over the course of their daily working routines are never limited to being part of the personal process of the social worker, but are also always inherently cultural. The work aiming at social change is defined by the presence of an initial situation, a specific goal, and the means and ways of achieving it, which are – or which should be – agreed upon by the social worker and the client in situation which is unique and at the same time socially-driven. Because of the inherent plot-based nature of social work, the practices related to it can be analysed as stories (see Dominelli 2005, 234), given, of course, that they are signifying and told by someone. The research of the practices is concentrating on impressions, perceptions, judgements, accounts, documents etc. All these multifarious elements can be scrutinized as textual corpora, but not whatever textual material. In semiotic analysis, the material studied is characterised as verbal or textual and loaded with meanings. We present a contribution of research methodology, semiotic analysis, which has to our mind at least implicitly references to the social work practices. Our examples of semiotic interpretation have been picked up from our dissertations (Laine 2005; Saurama 2002). The data are official documents from the archives of a child welfare agency and transcriptions of the interviews of shelter employees. These data can be defined as stories told by the social workers of what they have seen and felt. The official documents present only fragmentations and they are often written in passive form. (Saurama 2002, 70.) The interviews carried out in the shelters can be described as stories where the narrators are more familiar and known. The material is characterised by the interaction between the interviewer and interviewee. The levels of the story and the telling of the story become apparent when interviews or documents are examined with the use of semiotic tools. The roots of semiotic interpretation can be found in three different branches; the American pragmatism, Saussurean linguistics in Paris and the so called formalism in Moscow and Tartu; however in this paper we are engaged with the so called Parisian School of semiology which prominent figure was A. J. Greimas. The Finnish sociologists Pekka Sulkunen and Jukka Törrönen (1997a; 1997b) have further developed the ideas of Greimas in their studies on socio-semiotics, and we lean on their ideas. In semiotics social reality is conceived as a relationship between subjects, observations, and interpretations and it is seen mediated by natural language which is the most common sign system among human beings (Mounin 1985; de Saussure 2006; Sebeok 1986). Signification is an act of associating an abstract context (signified) to some physical instrument (signifier). These two elements together form the basic concept, the “sign”, which never constitutes any kind of meaning alone. The meaning will be comprised in a distinction process where signs are being related to other signs. In this chain of signs, the meaning becomes diverged from reality. (Greimas 1980, 28; Potter 1996, 70; de Saussure 2006, 46-48.) One interpretative tool is to think of speech as a surface under which deep structures – i.e. values and norms – exist (Greimas & Courtes 1982; Greimas 1987). To our mind semiotics is very much about playing with two different levels of text: the syntagmatic surface which is more or less faithful to the grammar, and the paradigmatic, semantic structure of values and norms hidden in the deeper meanings of interpretations. Semiotic analysis deals precisely with the level of meaning which exists under the surface, but the only way to reach those meanings is through the textual level, the written or spoken text. That is why the tools are needed. In our studies, we have used the semiotic square and the actant analysis. The former is based on the distinctions and the categorisations of meanings, and the latter on opening the plotting of narratives in order to reach the value structures.

The MIRELA framework: modeling and analyzing mixed reality applications using timed automata

Mixed Reality (MR) aims to link virtual entities with the real world and has many applications such as military and medical domains [JBL+00, NFB07]. In many MR systems and more precisely in augmented scenes, one needs the application to render the virtual part accurately at the right time. To achieve this, such systems acquire data related to the real world from a set of sensors before rendering virtual entities. A suitable system architecture should minimize the delays to keep the overall system delay (also called end-to-end latency) within the requirements for real-time performance. In this context, we propose a compositional modeling framework for MR software architectures in order to specify, simulate and validate formally the time constraints of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole system is then obtained as a composition of such defined components. To write specifications, a textual language named MIRELA (MIxed REality LAnguage) is proposed along with the corresponding compilation tools. The generated output contains timed automata in UPPAAL format for simulation and verification of time constraints. These automata may also be used to generate source code skeletons for an implementation on a MR platform. The approach is illustrated first on a small example. A realistic case study is also developed. It is modeled by several timed automata synchronizing through channels and including a large number of time constraints. Both systems have been simulated in UPPAAL and checked against the required behavioral properties.

NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

Sex identification and PIT-tagging: tools and prospects for studying intersexual differences in freshwater fishes

This study evaluated a technique to allow the long-term monitoring of individual fishes of known sex in the wild using sex confirmation in close proximity to the reproductive period combined with individual tagging. Hundreds of partially migratory roach Rutilus rutilus were tagged with passive integrated transponders (PIT) following sex determination in spring and various performance measures were compared with fish tagged outside the reproductive period in autumn. Short-term survival was > 95% for R. rutilus sexed and tagged under natural field conditions. Total length (LT) did not affect the probability of survival within the size range tagged (119–280mm), nor were there differences in timing of migration the following season between individuals sexed and tagged in spring and individuals tagged in autumn (i.e. outside the reproductive period). Also, a similar per cent of R. rutilus sexed and tagged in spring and tagged in autumn migrated the following season (34·5 and 34·7%). Moreover, long-term recapture data revealed no significant differences in body condition between R. rutilus individuals sexed and tagged in spring, individuals tagged in autumn and unmanipulated individuals. The observed sex ratio of recaptured fish did not differ from the expected values of equal recapture rates between males and females. Hence, there is no observable evidence for an adverse effect of tagging close to the reproductive period and therefore this method is suitable for studying intersexual differences and other phenotypic traits temporarily expressed during reproduction at the individual level in fishes.

The Dissociation of Location and Object Working Memory using fMRI and MEG

Visual working memory (VWM) involves maintaining and processing visual information, often for the purpose of making immediate decisions. Neuroimaging experiments of VWM provide evidence in support of a neural system mainly involving a fronto-parietal neuronal network, but the role of specific brain areas is less clear. A proposal that has recently generated considerable debate suggests that a dissociation of object and location VWM occurs within the prefrontal cortex, in dorsal and ventral regions, respectively. However, re-examination of the relevant literature presents a more robust distribution suggestive of a general caudal-rostral dissociation from occipital and parietal structures, caudally, to prefrontal regions, rostrally, corresponding to location and object memory, respectively. The purpose of the present study was to identify a dissociation of location and object VWM across two imaging methods (magnetoencephalography, MEG, and functional magnetic imaging, fMRI). These two techniques provide complimentary results due the high temporal resolution of MEG and the high spatial resolution of fMRI. The use of identical location and object change detection tasks was employed across techniques and reported for the first time. Moreover, this study is the first to use matched stimulus displays across location and object VWM conditions. The results from these two imaging methods provided convergent evidence of a location and object VWM dissociation favoring a general caudal-rostral rather than the more common prefrontal dorsal-ventral view. Moreover, neural activity across techniques was correlated with behavioral performance for the first time and provided convergent results. This novel approach of combining imaging tools to study memory resulted in robust evidence suggesting a novel interpretation of location and object memory. Accordingly, this study presents a novel context within which to explore the neural substrates of WM across imaging techniques and populations.

Development of automated image analysis tools for verification of radiotherapy field accuracy with an electronic portal imaging device

The successful management of cancer with radiation relies on the accurate deposition of a prescribed dose to a prescribed anatomical volume within the patient. Treatment set-up errors are inevitable because the alignment of field shaping devices with the patient must be repeated daily up to eighty times during the course of a fractionated radiotherapy treatment. With the invention of electronic portal imaging devices (EPIDs), patient's portal images can be visualized daily in real-time after only a small fraction of the radiation dose has been delivered to each treatment field. However, the accuracy of human visual evaluation of low-contrast portal images has been found to be inadequate. The goal of this research is to develop automated image analysis tools to detect both treatment field shape errors and patient anatomy placement errors with an EPID. A moments method has been developed to align treatment field images to compensate for lack of repositioning precision of the image detector. A figure of merit has also been established to verify the shape and rotation of the treatment fields. Following proper alignment of treatment field boundaries, a cross-correlation method has been developed to detect shifts of the patient's anatomy relative to the treatment field boundary. Phantom studies showed that the moments method aligned the radiation fields to within 0.5mm of translation and 0.5$\sp\circ$ of rotation and that the cross-correlation method aligned anatomical structures inside the radiation field to within 1 mm of translation and 1$\sp\circ$ of rotation. A new procedure of generating and using digitally reconstructed radiographs (DRRs) at megavoltage energies as reference images was also investigated. The procedure allowed a direct comparison between a designed treatment portal and the actual patient setup positions detected by an EPID. Phantom studies confirmed the feasibility of the methodology. Both the moments method and the cross-correlation technique were implemented within an experimental radiotherapy picture archival and communication system (RT-PACS) and were used clinically to evaluate the setup variability of two groups of cancer patients treated with and without an alpha-cradle immobilization aid. The tools developed in this project have proven to be very effective and have played an important role in detecting patient alignment errors and field-shape errors in treatment fields formed by a multileaf collimator (MLC). ^