New Statistical Algorithms for the Analysis of Mass Spectrometry Time-Of-Flight Mass Data with Applications in Clinical Diagnostics

Mass spectrometry (MS) based techniques have emerged as a standard forlarge-scale protein analysis. The ongoing progress in terms of more sensitive machines and improved data analysis algorithms led to a constant expansion of its fields of applications. Recently, MS was introduced into clinical proteomics with the prospect of early disease detection using proteomic pattern matching. Analyzing biological samples (e.g. blood) by mass spectrometry generates mass spectra that represent the components (molecules) contained in a sample as masses and their respective relative concentrations. In this work, we are interested in those components that are constant within a group of individuals but differ much between individuals of two distinct groups. These distinguishing components that dependent on a particular medical condition are generally called biomarkers. Since not all biomarkers found by the algorithms are of equal (discriminating) quality we are only interested in a small biomarker subset that - as a combination - can be used as a fingerprint for a disease. Once a fingerprint for a particular disease (or medical condition) is identified, it can be used in clinical diagnostics to classify unknown spectra. In this thesis we have developed new algorithms for automatic extraction of disease specific fingerprints from mass spectrometry data. Special emphasis has been put on designing highly sensitive methods with respect to signal detection. Thanks to our statistically based approach our methods are able to detect signals even below the noise level inherent in data acquired by common MS machines, such as hormones. To provide access to these new classes of algorithms to collaborating groups we have created a web-based analysis platform that provides all necessary interfaces for data transfer, data analysis and result inspection. To prove the platform's practical relevance it has been utilized in several clinical studies two of which are presented in this thesis. In these studies it could be shown that our platform is superior to commercial systems with respect to fingerprint identification. As an outcome of these studies several fingerprints for different cancer types (bladder, kidney, testicle, pancreas, colon and thyroid) have been detected and validated. The clinical partners in fact emphasize that these results would be impossible with a less sensitive analysis tool (such as the currently available systems). In addition to the issue of reliably finding and handling signals in noise we faced the problem to handle very large amounts of data, since an average dataset of an individual is about 2.5 Gigabytes in size and we have data of hundreds to thousands of persons. To cope with these large datasets, we developed a new framework for a heterogeneous (quasi) ad-hoc Grid - an infrastructure that allows to integrate thousands of computing resources (e.g. Desktop Computers, Computing Clusters or specialized hardware, such as IBM's Cell Processor in a Playstation 3)

The VPS ReplaySuite: development and evaluation of a novel, Internet based telepathology tool

The ReplaySuite is a web-based telepathology tool that replicates the doubleheaded microscope environment online, enabling a reviewing pathologist to ‘replay’ an archived virtual slide examination. Examination-tracking data obtained by the Virtual Pathology Slide (VPS) virtual slide viewer is exploited, allowing a remote pathologist to review an examination conducted at a different time and location. This removes temporal and spatial issues associated with double-headed microscopy. In order to conduct a preliminary evaluation of the technology, 9 pathologists used the ReplaySuite to review examination replays and diagnostic data from archived examinations of 10 needlecore breast biopsies. Diagnostically difficult cases were most frequently evaluated, either via diagnostic concordance graphs or examination replays, and all 3 participants who replayed more than 10 examinations stated the ReplaySuite to be of some or great benefit in pathology training and quality assurance. Of those who replayed an examination by another pathologist, 83% (5/6) agreed that replays provided an insight into the examining pathologists diagnosis, and 33% (2/6) reconsidered their own diagnosis for at least one case. Of those who reconsidered their original diagnosis, all reclassified either concordant with group consensus or original glass slide diagnosis. This study demonstrated that the ReplaySuite was of potential benefit in pathology education, however the technology required evaluation in a setting that would facilitate its impact on diagnostic performance. Accordingly, a redeveloped VPS and ReplaySuite were incorporated into the EQUALIS External Quality Assurance (EQA) study in chronic hepatitis staging and grading. During the study, 9 Swedish pathology departments examined and scored digital representations of liver needlecore biopsies during two sessions, with 10 cases per session and two digital slides per case. Between scoring sessions, participants were provided with access to two supplementary electronic resources: the ReplaySuite, and a library of pre-selected reference images. Comparison of concordance with gold standard (KVAST group) scoring before and after electronic resource use facilitated the elucidation of impact on diagnostic performance. Between scoring sessions, participant concordance with KVAST staging increased by 18% (49%-67%), while concordance with KVAST grading increased by 20% (34%-54%). Mean staging un-weighted kappa improved from 0.347 to 0.554 (+0.207), or from ‘fair’ to ‘moderate’ exact agreement with KVAST staging. Linear weighted staging kappa improved from 0.603 to 0.688 (+0.085), indicating close agreement in both sessions. Mean grading unweighted kappa increased from 0.132 to 0.412 (+0.280), or from a ‘poor’ to ‘moderate’ level o f exact agreement with KVAST, while linear weighted kappa improved from 0.328 to 0.624 (+0.295), or from ‘fair’ to ‘good’ level of approximate agreement with KVAST. Subsequent to the EQA scheme, an expert liver pathologist used the ReplaySuite to evaluate study examinations, assessing examination technique and identifying sources of error. Examinations scoring concordant with KVAST were observed to exhibit acceptable examination technique more frequently than discordantly scoring examinations. When grading, 28% (46% - 18%) more concordant than discordant examinations were considered to have viewed sufficient tissue, and at the appropriate magnification. A similar disparity of 24% (59% - 35%) was observed in staging, suggesting that examination technique was important both when determining the degree of necroinflammation within a biopsy, and when ascertaining the extent of fibrosis. In assessing sources of error, the expert pathologist identified a potential source in 50% of grading examinations, with misinterpretation of observed pathology cited in 19%, and missed pathology (oversight) cited in 31% of grading examinations. Of the 41% of staging examinations in which a source was identified, misinterpretation of observed pathology was cited in 20% of examinations, and missed pathology (oversight) in 21% of examinations. This study demonstrated that the use of supplementary electronic resources could result in improvements in diagnostic performance. It also illustrated the significant ‘add on’ value that could be provided by the ReplaySuite in EQA, by providing means to assess not only diagnostic concordance, but also diagnostic technique and identify sources of error. In order to assess Irish trainee pathologist’s perceptions of computer-assisted learning (CAL), a number of commercial systems were utilised to incorporate digital slides into a postgraduate seminar series, and provide subsequent access to seminar digital slides, diagnoses and expert annotations online. All surveyed trainees considered the use of digital slides and expert annotations of benefit in pathology training, and considered the potential implementation of expert examination replays, online self-assessment and the capability to search online for material by organ, diagnosis or pathological feature of benefit. The work described herein illustrates that both expert and trainee pathologists alike consider the use of supplementary electronic resources of benefit in pathology education, and demonstrates that their use can improve diagnostic performance. The ability to evaluate participation in EQA studies via the ReplaySuite provides significant additional value to education schemes, providing a depth of assessment not possible with conventional microscopy

Management of Cloud systems applied to eHealth

This thesis explores techniques, models and algorithms for an efficient management of Cloud systems and how to apply them to the healthcare sector in order to improve current treatments. It presents two Cloud-based eHealth applications to telemonitor and control smoke-quitting and hypertensive patients. Different Cloud-based models were obtained and used to develop a Cloudbased infrastructure where these applications are deployed. The results show that these applications improve current treatments and that can be scaled as computing requirements grow. Multiple Cloud architectures and models were analyzed and then implemented using different techniques and scenarios. The Smoking Patient Control (S-PC) tool was deployed and tested in a real environment, showing a 28.4% increase in long-term abstinence. The Hypertension Patient Control (H-PC) tool, was successfully designed and implemented, and the computing boundaries were measuredAquesta tesi explora tèniques, models i algorismes per una gestió eficient en sistemes al Núvol i com aplicar-ho en el sector de la salut per tal de millorar els tractaments actuals. Presenta dues aplicacions de salut electrònica basades en el Núvol per telemonitoritzar i controlar pacients fumadors i hipertensos. S'ha obtingut diferents models basats en el Núvol i s'han utilitzat per a desenvolupar una infraestructura on desplegar aquestes aplicacions. Els resultats mostren que aquestes aplicacions milloren els tractaments actuals així com escalen a mesura que els requeriments computacionals augmenten. Múltiples arquitectures i models han estat analitzats i implementats utilitzant diferents tècniques i escenaris. L'aplicació Smoking Patient Control (S-PC) ha estat desplegada i provada en un entorn real, aconseguint un augment del 28,4% en l'absistinència a llarg termini de pacients fumadors. L'aplicació Hypertension Patient Control (H-PC) ha estat dissenyada i implementada amb èxit, i els seus límits computacionals han estat mesurats.Esta tesis explora ténicas, modelos y algoritmos para una gestión eficiente de sistemas en la Nube y como aplicarlo en el sector de la salud con el fin de mejorar los tratamientos actuales. Presenta dos aplicaciones de salud electrónica basadas en la Nube para telemonitorizar y controlar pacientes fumadores e hipertensos. Se han obtenido diferentes modelos basados en la Nube y se han utilizado para desarrollar una infraestructura donde desplegar estas aplicaciones. Los resultados muestran que estas aplicaciones mejoran los tratamientos actuales así como escalan a medida que los requerimientos computacionales aumentan. Múltiples arquitecturas y modelos han sido analizados e implementados utilizando diferentes técnicas y escenarios. La aplicación Smoking Patient Control (S-PC) se ha desplegado y provado en un entorno real, consiguiendo un aumento del 28,4% en la abstinencia a largo plazo de pacientes fumadores. La aplicación Hypertension Patient Control (H-PC) ha sido diseñada e implementada con éxito, y sus límites computacionales han sido medidos

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Proceedings of the First Karlsruhe Service Summit Workshop - Advances in Service Research, Karlsruhe, Germany, February 2015 (KIT Scientific Reports ; 7692)

Since April 2008 KSRI fosters interdisciplinary research in order to support and advance the progress in the service domain. KSRI brings together academia and industry while serving as a European research hub with respect to service science. For KSS2015 Research Workshop, we invited submissions of theoretical and empirical research dealing with the relevant topics in the context of services including energy, mobility, health care, social collaboration, and web technologies