A Comparison of Neuroelectrophysiology Databases

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. These archives provide researchers with tools to store, share, and reanalyze neurophysiology data though the means of accomplishing these objectives differ. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. While many tools are available to reanalyze data on and off the archives' platforms, this article features Reproducible Analysis and Visualization of Intracranial EEG (RAVE) toolkit, developed specifically for the analysis of intracranial signal data and integrated with the discussed standards and archives. Neuroelectrophysiology data archives improve how researchers can aggregate, analyze, distribute, and parse these data, which can lead to more significant findings in neuroscience research.Comment: 25 pages, 8 figures, 1 tabl

Visuelles Studienmanagement mit dem Trial Outline Builder in ObTiMA

Die heutige klinische Landschaft ist ein Spannungsfeld aus Kosteneffizienz, umfangreichen Dokumentationspflichten, Personalmangel und vieler weiterer Herausforderungen in der Behandlung von Patienten. Mithilfe der heutigen Computertechnologie und ihren Möglichkeiten wird trotz des eingeschränkten Zeitpensums der behandelnden Ärzte versucht, eine möglichst auf den einzelnen Patienten abgestimmte Behandlung zu ermöglichen. Damit in der personalisierten Medizin auf die für den jeweiligen Patienten am besten passende Therapie zur Bekämpfung seiner Erkrankung zurückgegriffen werden kann, sind im Vorfeld klinische Studien über neue Medikamente und Therapieformen notwendig. Diese klinischen Studien benötigen viel Vorbereitungszeit, da zunächst ein Studienprotokoll inklusive eines Behandlungsplans mit entsprechenden Fragestellungen entwickelt werden muss. In größeren Studien erfordert dies den Austausch zwischen Medizinern aus verschiedenen Fachbereichen. Um diesen Planungsmitgliedern schon zu Beginn eine gemeinsame Diskussionsgrundlage auf Basis eines grafischen Behandlungsplans zu ermöglichen, kann der in dieser Arbeit vorgestellte Trial Outline Builder (TOB) dienen. Damit die Anwendbar- und Nützlichkeit dieser Technologie nicht schon in der Anfangsphase einer Studie endet, wurde sie auf das Studienmanagementsystem Ontology-based Trial Management Application (ObTiMA) angepasst und in diese integriert. Für die vorliegende Arbeit wurde im ersten Schritt ObTiMA und der Trial Outline Builder auf den gleichen technischen Stand gebracht. Somit wurde die in ObTiMA vorhandene Struktur von Study Events und ihren Case Report Form (CRF) Fragebögen im TOB nutzbar gemacht. Dies war notwendig geworden, da sich die beiden Anwendungen über die Jahre auseinanderentwickelt hatten. Im zweiten Schritt wurden Kommunikationsschnittstellen zwischen ObTiMA und dem TOB geschaffen, um erstellte Behandlungspläne speichern und erneut laden zu können. Dafür wurde die Patientenansicht des TOBs mit der Möglichkeit erweitert, medizinische Events über einen Representational State Transfer (REST) Service in ObTiMA zu aktivieren. Dies hatte weitreichende Änderungen am ObTiMA Quellcode zur Folge, da dieser bislang ausschließlich für Benutzersessions ausgelegt war und nun auch über das statuslose REST ausführbar sein musste. Während dieser Entwicklung war es immer wieder erforderlich neu entdeckte Bugs im TOB zu korrigieren, die zu einer nicht geladenen TOB Seite oder zu defekten Behandlungsplänen nach der Speicherung in der Datenbank führte. Im letzten Arbeitsteil wurde eine durch Anwender leicht ausführbare Randomisierung von Patienten nach der Minimisationsmethode realisiert, die die jeweiligen Stärken der beiden Anwendungen nutzt. Mit dem Ergebnis dieser Arbeit können nun die in der Studiendesignphase in ObTiMA erstellten Study Events mit einzelnen medizinischen Events zu einem zeitbasierten Behandlungsplan verknüpft werden. Nach Studienstart werden für die Patienten zusätzlich neben der geplanten Behandlung auch eine persönliche Timeline mit allen medizinischen Events angezeigt. Dadurch erhält das Studienpersonal auf einen Blick eine grafische Übersicht über den realen Behandlungsverlauf des jeweiligen Patienten inklusive unerwünschter Ereignisse wie Serious Adverse Events (SAEs), Suspected Unexpected Serious Adverse Reactions (SUSARs), Notoperationen, etc. Im klinischen Alltag kann der behandelnde Arzt damit leichter und effizienter die erfasste Studiendaten auffinden. Diese Verbesserungen dürften in der zukünftigen Anwendung des Trial Outline Builders sowohl dem medizinischen Personal als auch den Patienten zu Gute kommen.Today's clinical landscape is an area of conflict between cost efficiency, extensive documentation requirements, lack of personnel and many other challenges in the treatment of patients. With the help of today's computer technology and its possibilities, an attempt is being made to enable treatment to be tailored as closely as possible to the individual patient, especially, in times when time is very limited for the physicians. Clinical studies on new drugs and forms of therapy have to be performed in advance so that personalised medicine can use the therapy best suited to the patient's illness. These clinical studies require a lot of preparation time, since a Trial Master Protocol must first be developed, including the corresponding research questions and a treatment plan. In larger studies this requires the exchange of information between many physicians from different departments. In order to provide these planning members with a common basis for discussion based on a visual treatment plan right from the start, the Trial Outline Builder presented in this thesis can be used. To ensure that the applicability and usefulness of this technology does not end in the initial phase of a study, it was adapted to and integrated into the Ontology-based Trial Management Application (ObTiMA). In the first step, ObTiMA and the Trial Outline Builder (TOB) were brought to the same level by unifying the structure of study events and Case Report Form (CRF) questionnaires. This had become necessary since the two applications developed into kind of different direction over the past years. In the second step, communication interfaces between ObTiMA and the Trial Outline Builder were implemented for saving and loading treatment plans. Later, the pa-tient view of the TOB was extended with the possibility to activate medical events via a Rep-resentational State Transfer (REST) service in ObTiMA. This resulted in extensive changes in the ObTiMA source code, since it previously was only supposed to work with user sessions. Now this code works with stateless REST services as well. During this whole transformation process, it was often necessary to correct several breaking bugs in the original TOB code, which led to unloaded pages or broken treatment plans after saving. In the last step of this work, an easy user-executable randomization of patients (minimization method) was implemented, which combined the strengths of both applications. With the result of this work, the CRF questionnaires created in the study design phase in ObTiMA can now be linked with individual medical events to form a time-based treatment plan. After the start of the study, patients have a personal timeline with all medical events in addi-tion to the planned treatment. This provides the study staff with a visual overview of the actual treatment process of the respective patient at a glance, including unwanted events such as Serious Adverse Events (SAEs), Suspected Unexpected Serious Adverse Reactions (SUSARs), emergency operations, etc. This allows physicians in charge to find the recorded study data easier and more efficiently in the clinical routine. These improvements should benefit both, clinicians and patients, in the future use of the Trial Outline Builder

Modern Information Systems

The development of modern information systems is a demanding task. New technologies and tools are designed, implemented and presented in the market on a daily bases. User needs change dramatically fast and the IT industry copes to reach the level of efficiency and adaptability for its systems in order to be competitive and up-to-date. Thus, the realization of modern information systems with great characteristics and functionalities implemented for specific areas of interest is a fact of our modern and demanding digital society and this is the main scope of this book. Therefore, this book aims to present a number of innovative and recently developed information systems. It is titled "Modern Information Systems" and includes 8 chapters. This book may assist researchers on studying the innovative functions of modern systems in various areas like health, telematics, knowledge management, etc. It can also assist young students in capturing the new research tendencies of the information systems' development

Supporting formal expression of eligibility criteria in clinical trials. The implementation and evaluation of the eligibility criteria builder

A clinical trial is a study that assesses the effectiveness and safety of a new drug or treatment. To be able to generalize from the findings of the study, the clinical trial requires a representative sample of the target patient population. The target population is defined in terms of eligibility criteria that clearly describe the characteristics of patients enrolled in the study. The eligibility criteria are stated in natural language in its own section in a protocol document, which serves as the plan and detailed description of any prospective clinical trial. Having the eligibility criteria expressed as natural language has several drawbacks. First, it can lead to ambiguities and different interpretations among clinicians responsible for enrolment of patients into the study, which consequently may affect the safety of patients. Second, it provides no means of automatic eligibility checking against patient databases and electronic patient journals. The process of determining the eligibility of each patient therefore becomes a resource demanding and time consuming task. Formally defined computer interpretable eligibility criteria could potentially improve safety of involved patients and efficiency in patient enrolment. This thesis presents the Eligibility Criteria Builder that aims to provide a simple and pragmatic way of defining these rules using a user-friendly graphical user interface. The evaluation of the prototype indicated that the target users in general were positive to, and clearly saw the need for, a tool like this. The evaluation also pointed out weak spots and areas of improvements for the proposed prototype

Engineering Agile Big-Data Systems

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems

Exploring data quality monitoring procedures in the clinical research setting: Insights from clinical studies

To learn about human health, clinical research studies are conducted. A substantial concern for all clinical research studies is the failure to collect, process and present good quality data. Poor data quality may stem from error. International guidelines have identified that it is an essential need to monitor study activity to ensure that the rights, safety and wellbeing of participants are protected. However, the guidelines provide limited insight on how to perform monitoring procedures including the nature and extent of monitoring needed to ensure quality. Without clear guidance, this leaves clinical researchers confused about the most appropriate quality assurance and control procedures. The central hypothesis of this thesis is that despite the wide variations, exploration and evaluation of appropriate data quality monitoring procedures in clinical research studies will provide guidance toward developing a “fit-for-use” data quality monitoring framework (DQMF). This hypothesis was tested in five key studies using an explanatory sequential design guided by the Data- Information-Knowledge-Wisdom (DIKW) model as the theoretical framework

Engineering Agile Big-Data Systems

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems

Partial ablation versus radical prostatectomy in intermediate-risk prostate cancer:the PART feasibility RCT

Background Prostate cancer (PCa) is the most common cancer in men in the UK. Patients with intermediate-risk, clinically localised disease are offered radical treatments such as surgery or radiotherapy, which can result in severe side effects. A number of alternative partial ablation (PA) technologies that may reduce treatment burden are available; however the comparative effectiveness of these techniques has never been evaluated in a randomised controlled trial (RCT). Objectives To assess the feasibility of a RCT of PA using high-intensity focused ultrasound (HIFU) versus radical prostatectomy (RP) for intermediate-risk PCa and to test and optimise methods of data capture. Design We carried out a prospective, multicentre, open-label feasibility study to inform the design and conduct of a future RCT, involving a QuinteT Recruitment Intervention (QRI) to understand barriers to participation. Setting Five NHS hospitals in England. Participants Men with unilateral, intermediate-risk, clinically localised PCa. Interventions Radical prostatectomy compared with HIFU. Primary outcome measure The randomisation of 80 men. Secondary outcome measures Findings of the QRI and assessment of data capture methods. Results Eighty-seven patients consented to participate by 31 March 2017 and 82 men were randomised by 4 May 2017 (41 men to the RP arm and 41 to the HIFU arm). The QRI was conducted in two iterative phases: phase I identified a number of barriers to recruitment, including organisational challenges, lack of recruiter equipoise and difficulties communicating with patients about the study, and phase II comprised the development and delivery of tailored strategies to optimise recruitment, including group training, individual feedback and ‘tips’ documents. At the time of data extraction, on 10 October 2017, treatment data were available for 71 patients. Patient characteristics were similar at baseline and the rate of return of all clinical case report forms (CRFs) was 95%; the return rate of the patient-reported outcome measures (PROMs) questionnaire pack was 90.5%. Centres with specific long-standing expertise in offering HIFU as a routine NHS treatment option had lower recruitment rates (Basingstoke and Southampton) – with University College Hospital failing to enrol any participants – than centres offering HIFU in the trial context only. Conclusions Randomisation of men to a RCT comparing PA with radical treatments of the prostate is feasible. The QRI provided insights into the complexities of recruiting to this surgical trial and has highlighted a number of key lessons that are likely to be important if the study progresses to a main trial. A full RCT comparing clinical effectiveness, cost-effectiveness and quality-of-life outcomes between radical treatments and PA is now warranted