Classification, categorization and essential items for digital ulcer evaluation in systemic sclerosis: a DeSScipher/European Scleroderma Trials and Research group (EUSTAR) survey

Background A consensus on digital ulcer (DU) definition in systemic sclerosis (SSc) has been recently reached (Suliman et al., J Scleroderma Relat Disord 2:115-20, 2017), while for their evaluation, classification and categorisation, it is still missing. The aims of this study were to identify a set of essential items for digital ulcer (DU) evaluation, to assess if the existing DU classification was useful and feasible in clinical practice and to investigate if the new categorisation was preferred to the simple distinction of DU in recurrent and not recurrent, in patients with systemic sclerosis (SSc). Methods DeSScipher is the largest European multicentre study on SSc. It consists of five observational trials (OTs), and one of them, OT1, is focused on DU management. The DeSScipher OT1 items on DU that reached ≥ 60% of completion rate were administered to EUSTAR (European Scleroderma Trials and Research group) centres via online survey. Questions about feasibility and usefulness of the existing DU classification (DU due to digital pitting scars, to loss of tissue, derived from calcinosis and gangrene) and newly proposed categorisation (episodic, recurrent and chronic) were also asked. Results A total of 84/148 (56.8%) EUSTAR centres completed the questionnaire. DeSScipher items scored by ≥ 70% of the participants as essential and feasible for DU evaluation were the number of DU defined as a loss of tissue (level of agreement 92%), recurrent DU (84%) and number of new DU (74%). For 65% of the centres, the proposed classification of DU was considered useful and feasible in clinical practice. Moreover, 80% of the centres preferred the categorisation of DU in episodic, recurrent and chronic to simple distinction in recurrent/not recurrent DU. Conclusions For clinical practice, EUSTAR centres identified only three essential items for DU evaluation and considered the proposed classification and categorisation as useful and feasible. The set of items needs to be validated while further implementation of DU classification and categorisation is warranted. Trial registration Observational trial on DU (OT1) is one of the five trials of the DeSScipher project (ClinicalTrials.gov; OT1 Identifier: NCT01836263, posted on April 19, 2013)

Visual analytics methods for retinal layers in optical coherence tomography data

Optical coherence tomography is an important imaging technology for the early detection of ocular diseases. Yet, identifying substructural defects in the 3D retinal images is challenging. We therefore present novel visual analytics methods for the exploration of small and localized retinal alterations. Our methods reduce the data complexity and ensure the visibility of relevant information. The results of two cross-sectional studies show that our methods improve the detection of retinal defects, contributing to a deeper understanding of the retinal condition at an early stage of disease.Die optische Kohärenztomographie ist ein wichtiges Bildgebungsverfahren zur Früherkennung von Augenerkrankungen. Die Identifizierung von substrukturellen Defekten in den 3D-Netzhautbildern ist jedoch eine Herausforderung. Wir stellen daher neue Visual-Analytics-Methoden zur Exploration von kleinen und lokalen Netzhautveränderungen vor. Unsere Methoden reduzieren die Datenkomplexität und gewährleisten die Sichtbarkeit relevanter Informationen. Die Ergebnisse zweier Querschnittsstudien zeigen, dass unsere Methoden die Erkennung von Netzhautdefekten in frühen Krankheitsstadien verbessern

Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches

Classification, categorization and essential items for digital ulcer evaluation in systemic sclerosis: a DeSScipher/European Scleroderma Trials and Research group (EUSTAR) survey

BACKGROUND: A consensus on digital ulcer (DU) definition in systemic sclerosis (SSc) has been recently reached (Suliman et al., J Scleroderma Relat Disord 2:115-20, 2017), while for their evaluation, classification and categorisation, it is still missing. The aims of this study were to identify a set of essential items for digital ulcer (DU) evaluation, to assess if the existing DU classification was useful and feasible in clinical practice and to investigate if the new categorisation was preferred to the simple distinction of DU in recurrent and not recurrent, in patients with systemic sclerosis (SSc). METHODS: DeSScipher is the largest European multicentre study on SSc. It consists of five observational trials (OTs), and one of them, OT1, is focused on DU management. The DeSScipher OT1 items on DU that reached ≥ 60% of completion rate were administered to EUSTAR (European Scleroderma Trials and Research group) centres via online survey. Questions about feasibility and usefulness of the existing DU classification (DU due to digital pitting scars, to loss of tissue, derived from calcinosis and gangrene) and newly proposed categorisation (episodic, recurrent and chronic) were also asked. RESULTS: A total of 84/148 (56.8%) EUSTAR centres completed the questionnaire. DeSScipher items scored by ≥ 70% of the participants as essential and feasible for DU evaluation were the number of DU defined as a loss of tissue (level of agreement 92%), recurrent DU (84%) and number of new DU (74%). For 65% of the centres, the proposed classification of DU was considered useful and feasible in clinical practice. Moreover, 80% of the centres preferred the categorisation of DU in episodic, recurrent and chronic to simple distinction in recurrent/not recurrent DU. CONCLUSIONS: For clinical practice, EUSTAR centres identified only three essential items for DU evaluation and considered the proposed classification and categorisation as useful and feasible. The set of items needs to be validated while further implementation of DU classification and categorisation is warranted. TRIAL REGISTRATION: Observational trial on DU (OT1) is one of the five trials of the DeSScipher project (ClinicalTrials.gov; OT1 Identifier: NCT01836263, posted on April 19, 2013)