A deep look into radiomics.

Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into radiomics, from the basis, deeply discussed from a technical point of view, through the main applications, to the challenges that have to be addressed to translate this process in clinical practice. A detailed description of the main techniques used in the various steps of radiomics workflow, which includes image acquisition, reconstruction, pre-processing, segmentation, features extraction and analysis, is here proposed, as well as an overview of the main promising results achieved in various applications, focusing on the limitations and possible solutions for clinical implementation. Only an in-depth and comprehensive description of current methods and applications can suggest the potential power of radiomics in fostering precision medicine and thus the care of patients, especially in cancer detection, diagnosis, prognosis and treatment evaluation.

Centralized Clinical Trial Imaging Data Management: Practical Guidance from a Comprehensive Cancer Center's Experience.

Medical imaging is an integral part of clinical trial research and it must be managed properly to provide accurate data to the sponsor in a timely manner (Clune in Cancer Inform 4:33-56, 2007; Wang et al. in Proc SPIE Int Soc Opt Eng 7967, 2011). Standardized workflows for site qualification, protocol preparation, data storage, retrieval, de-identification, submission, and query resolution are paramount to achieve quality clinical trial data management such as reducing the number of imaging protocol deviations and avoiding delays in data transfer. Centralization of data management and implementation of relational databases and electronic workflows can help maintain consistency and accuracy of imaging data. This technical note aims at sharing the practical implementation of our centralized clinical trial imaging data management processes to avoid the fragmentation of tasks among various disease centers and research staff, and enable us to provide quality, accurate, and timely imaging data to clinical trial sponsors.

Avaliação da implantação do Sistema de Controle, Acompanhamento e Avaliação de Resultados (Sistema e-Car) na Secretaria de Vigilância em Saúde do Ministério da Saúde do Brasil, no período de 2012 - 2015 / Evaluación de la implantación del Sistema de Control, Monitoreo y Evaluación de Resultados (Sistema e-Car) en la Secretaría de Vigilancia en Salud del Ministerio de Salud de Brasil, en el período de 2012 - 2015 / Evaluation of the Results Control, Monitoring and Evaluation System (e-Car system) Implementation at the Health Surveillance Secretariat, Brazilian Ministry of Health, 2012-2015

Objetivo: avaliar a implantação do Sistema de Controle, Acompanhamento e Avaliação de Resultados (e-Car) na Secretaria de Vigilância em Saúde (SVS) do Ministério da Saúde, no período de 2012 a 2015. Métodos: estudo de avaliação utilizando métodos mistos para a coleta de dados primários e secundários, seguido da definição do grau de implantação do sistema e da análise da influência do contexto político-organizacional. Resultados: o sistema e-Car foi considerado implantado na SVS, alcançando o percentual de 75,4%; as piores performances da dimensão de estrutura foram relacionadas ao serviço de manutenção dos computadores e do sistema operacional, bem como ao baixo conhecimento sobre o manual do sistema; na dimensão de processo, a existência de instâncias colegiadas foi considerada benéfica para o monitoramento. Conclusão: o sistema e-Car foi implantado na SVS; entretanto, sua sustentabilidade mostrou-se frágil, sendo recomendados a institucionalização e o fortalecimento das práticas de monitoramento e avaliação pela SVS.

Objetivo: evaluar la implantación del Sistema de Control, Monitoreo y Evaluación de Resultados (e-Car) en la Secretaría de Vigilancia en Salud (SVS) del Ministerio de Salud de Brasil, en el período de 2012 a 2015. Métodos: estudio de evaluación de métodos mixtos para la recolección de datos primarios y secundarios, seguido de la definición del grado de implantación del sistema y análisis de la influencia del contexto político-organizacional. Resultados: el sistema e-Car fue considerado implantado en la SVS, alcanzando un 75,4%; las peores actuaciones de la dimensión de estructura fueron el servicio de mantenimiento de las computadoras y del sistema operacional, así como el bajo conocimiento del manual del sistema; en la dimensión de proceso, la existencia de instancias colegiadas fue considerada benéfica para el monitoreo. Conclusión: el sistema e-Car fue implantado en la SVS; todavía, su sostenibilidad se mostró frágil, recomendándose la institucionalización y el fortalecimiento de las prácticas de monitoreo y evaluación por la SVS.

Objective: to evaluate the implementation of the Results Control, Monitoring and Evaluation System (e-Car) at the Health Surveillance Secretariat (SVS), Brazilian Ministry of Health, in the period 2012-2015. Methods: this was an evaluation study using mixed methods for collection of primary and secondary data, followed by definition of the system's degree of implementation and analysis of the influence of the political-organizational context. Results: the e-Car System was considered to have been implemented (75.4%) at SVS; the worst scores for its structure dimension related to the computer and operating system maintenance service, as well as little knowledge of the system manual; as for the system's process dimension, the existence of collegiate bodies was considered beneficial for monitoring. Conclusion: the e-Car System had been implemented at SVS; however, its sustainability was fragile, and SVS was recommended to institutionalize and strengthen its monitoring and evaluation practices.

An Architecture for Translational Cancer Research As Exemplified by the German Cancer Consortium.

Networking of medical institutions by means of a capable data infrastructure has the potential to open up vast amounts of routine data to translational cancer research. However, the secondary use of information collected independently in several institutions is a challenging task of data integration. In this review, we discuss the requirements and common challenges involved in the establishment of such a platform. We present methods and tools from the field of medical informatics as solutions to semantic and technical heterogeneity, questions of data protection and record linkage, as well as issues of trust and data ownership. We also describe the architecture of an existing cancer research network as an exemplary application of these methods.

Development of multi-disciplinary breast cancer care in Southern Malawi.

The Edinburgh Malawi Breast Cancer Project, a collaborative partnership project between the Queen Elizabeth Central Hospital (QECH) Oncology Unit, Blantyre, Malawi and the Edinburgh Cancer Centre, UK, was established in 2015. The principal objective of the project is to help to develop high quality multi-disciplinary breast cancer care in Malawi. A needs assessment identified three priority areas for further improvement of breast cancer services: multi-disciplinary working, development of oestrogen receptor (ER) testing and management of clinical data. A 3-year project plan was implemented which has been conducted through a series of reciprocal training visits. Key achievements to date have been: (1) Development of a new specialist breast care nursing role; (2) Development of multi-disciplinary meetings; (3) Completion of a programme of oncology nursing education; (4) Development of a clinical database that enables prospective collection of data of all new patients with breast cancer; (5) Training of local staff in molecular and conventional approaches to ER testing. The Edinburgh Malawi Breast Cancer Project is supporting nursing education, data use and cross-specialty collaboration that we are confident will improve cancer care in Malawi. Future work will include the development of a breast cancer diagnostic clinic and a breast cancer registry.

Unified Database for Rejected Image Analysis Across Multiple Vendors in Radiography.

Reject rate analysis has been part of radiography departments' quality control since the days of screen-film radiography. In the era of digital radiography, one might expect that reject rate analysis is easily facilitated because of readily available information produced by the modality during the examination procedure. Unfortunately, this is not always the case. The lack of an industry standard and the wide variety of system log entries and formats have made it difficult to implement a robust multivendor reject analysis program, and logs do not always include all relevant information. The increased use of digital detectors exacerbates this problem because of higher reject rates associated with digital radiography compared with computed radiography. In this article, the authors report on the development of a unified database for vendor-neutral reject analysis across multiple sites within an academic institution and share their experience from a team-based approach to reduce reject rates.

Metadata Repository for Improved Data Sharing and Reuse Based on HL7 FHIR.

Unreconciled data structures and formats are a common obstacle to the urgently required sharing and reuse of data within healthcare and medical research. Within the North German Tumor Bank of Colorectal Cancer, clinical and sample data, based on a harmonized data set, is collected and can be pooled by using a hospital-integrated Research Data Management System supporting biobank and study management. Adding further partners who are not using the core data set requires manual adaptations and mapping of data elements. Facing this manual intervention and focusing the reuse of heterogeneous healthcare instance data (value level) and data elements (metadata level), a metadata repository has been developed. The metadata repository is an ISO 11179-3 conformant server application built for annotating and mediating data elements. The implemented architecture includes the translation of metadata information about data elements into the FHIR standard using the FHIR Data Element resource with the ISO 11179 Data Element Extensions. The FHIR-based processing allows exchange of data elements with clinical and research IT systems as well as with other metadata systems. With increasingly annotated and harmonized data elements, data quality and integration can be improved for successfully enabling data analytics and decision support.

Genetics, lifestyle and environment. UK Biobank is an open access resource following the lives of 500,000 participants to improve the health of future generations.

UK Biobank is a long-term prospective epidemiology study having recruited and now following the lives of 500,000 people in England, Scotland and Wales, aged 40-69 years when they joined the study (Sudlow et al., PLoS Med 12(3):e1001779, 2015). Participants were recruited by letter and asked to attend one of 22 assessment centres in towns and cities across Britain, where they provided consent, answered detailed questions about their health and lifestyle, had body measures taken and donated blood, urine and saliva. Participants provided consent for the long-term follow-up of their health via medical records, such as general practice and hospital records, cancer and death records. Samples are being stored long term for a wide range of analyses, including genetic. The resource is open to all bona fide scientists from the UK and overseas, academic and industry who register via its access management system. Summary of UK Biobank data can be viewed via its Data Showcase and the resource will be strengthened over time as the results of new analyses and studies are returned, health links and participants provide additional information about themselves. Some will attend full repeat assessment visits. UK Biobank is open for business, and it hopes researchers will find it a valuable tool to improve the health of future generations.

Implementing an Electronic Event-Reporting System in a Radiation Oncology Department: The Effect on Safety Culture and Near-Miss Prevention.

PURPOSE: We implemented an electronic event-reporting system to investigate its effect on quality improvement in our department. METHODS: We developed an event-reporting program that launched in October 2012; data analysis was performed in January 2014. Events were logged by the radiation oncology staff and reviewed by our quality and safety committee on a biweekly basis. To measure the efficacy of the new program, and change in safety culture, a Likert-scale survey was administered before, and three months after, implementation of the event-reporting system. RESULTS: A total of 194 events were logged into the new system during a 15-month period (approximately 13 events per month), compared with 93 events in an 18-month period (approximately five events per month) before the program was launched. The average number of events reported by radiation therapists increased from 0.9 per month to 8.6 per month. The survey results showed a shift toward stronger agreement by staff members, in postimplementation versus preimplementation responses, when they were asked if they knew how to report an event in the department (P = .042), and if the current event-reporting system would reduce the incidence of future events (P = .032). Results showed a trend toward stronger agreement by staff members when they were asked if they felt more comfortable reporting events that they had observed (P = .093). Multiple safety action plans were implemented as a result of analysis of these events. CONCLUSIONS: An electronic event-reporting system streamlines quality and safety in a radiation oncology department by increasing reported events and promoting a safety culture. A program that is widely accessible, easy to use, and can analyze data meaningfully will be the most successful.

A Generic Data Harmonization Process for Cross-linked Research and Network Interaction. Construction and Application for the Lung Cancer Phenotype Database of the German Center for Lung Research.

OBJECTIVE: Joint data analysis is a key requirement in medical research networks. Data are available in heterogeneous formats at each network partner and their harmonization is often rather complex. The objective of our paper is to provide a generic approach for the harmonization process in research networks. We applied the process when harmonizing data from three sites for the Lung Cancer Phenotype Database within the German Center for Lung Research. METHODS: We developed a spreadsheet-based solution as tool to support the harmonization process for lung cancer data and a data integration procedure based on Talend Open Studio. RESULTS: The harmonization process consists of eight steps describing a systematic approach for defining and reviewing source data elements and standardizing common data elements. The steps for defining common data elements and harmonizing them with local data definitions are repeated until consensus is reached. Application of this process for building the phenotype database led to a common basic data set on lung cancer with 285 structured parameters. The Lung Cancer Phenotype Database was realized as an i2b2 research data warehouse. CONCLUSION: Data harmonization is a challenging task requiring informatics skills as well as domain knowledge. Our approach facilitates data harmonization by providing guidance through a uniform process that can be applied in a wide range of projects.

TCGA4U: A Web-Based Genomic Analysis Platform To Explore And Mine TCGA Genomic Data For Translational Research.

Large-scale human cancer genomics projects, such as TCGA, generated large genomics data for further study. Exploring and mining these data to obtain meaningful analysis results can help researchers find potential genomics alterations that intervene the development and metastasis of tumors. We developed a web-based gene analysis platform, named TCGA4U, which used statistics methods and models to help translational investigators explore, mine and visualize human cancer genomic characteristic information from the TCGA datasets. Furthermore, through Gene Ontology (GO) annotation and clinical data integration, the genomic data were transformed into biological process, molecular function, cellular component and survival curves to help researchers identify potential driver genes. Clinical researchers without expertise in data analysis will benefit from such a user-friendly genomic analysis platform.

A systematic approach for using DICOM structured reports in clinical processes: focus on breast cancer.

This paper describes a methodology for redesigning the clinical processes to manage diagnosis, follow-up, and response to treatment episodes of breast cancer. This methodology includes three fundamental elements: (1) identification of similar and contrasting cases that may be of clinical relevance based upon a target study, (2) codification of reports with standard medical terminologies, and (3) linking and indexing the structured reports obtained with different techniques in a common system. The combination of these elements should lead to improvements in the clinical management of breast cancer patients. The motivation for this work is the adaptation of the clinical processes for breast cancer created by the Valencian Community health authorities to the new techniques available for data processing. To achieve this adaptation, it was necessary to design nine Digital Imaging and Communications in Medicine (DICOM) structured report templates: six diagnosis templates and three summary templates that combine reports from clinical episodes. A prototype system is also described that links the lesion to the reports. Preliminary tests of the prototype have shown that the interoperability among the report templates allows correlating parameters from different reports. Further work is in progress to improve the methodology in order that it can be applied to clinical practice.

The EuroNet paediatric hodgkin network - modern imaging data management for real time central review in multicentre trials.

Since 2007, children and adolescents with Hodgkin lymphomas are treated in the Europe-wide EuroNet-PHL trials. A real time central review process for stratification of the patients enhances quality control and efficient therapy management. This process includes reading of all cross-sectional-images. Since reference evaluation is time critical, a fast, easy to handle and safe data transfer is important. In addition, immediate and constant access to all the data has to be guaranteed in case of queries and for regulatory reasons. To meet the mentioned requirements the EuroNet Paediatric Hodgkin Data Network (funded by the European Union - Project Number: 2007108) was established between 2008 and 2011. A respective tailored data protection plan was formulated. The aim of this article is to describe the networks' mode of operation and the advantages for multi-centre trials that include centralized image review.

Organising and presenting information.

Information management can be a daunting process for clinicians, health care providers and policy makers within the health care industry. This chapter discusses the importance of information classification and information architecture in the information economy and specific challenges faced within the health care industry. The healthcare sector has industry specific requirements for information management, standards and specifications for information presentation. Classification of information based on information criticality and the value in the health care industry is discussed in this paper. Presentation of information with reference to eHealth standards and specifications for healthcare information systems and their key requirements are also discussed, as are information architecture for eHealth implementation in Australia. This chapter also touches on information management and clinical governance since the importance of information governance is discussed by various researchers and how this is becoming of value to healthcare information management.

Using the cancer registry to meet the Commission on Cancer clinical trials accrual standard.

Clinical trials are an important tool for innovation in cancer treatments. Therefore, accrual into trials has been highlighted for Commission on Cancer (CoC)-accredited hospital programs. The current Standard 5.21 and Standard 1.92 which take effect in 2015 require a minimum percentage of patient enrollment for compliance, as well as an opportunity for commendation at a higher percentage. The standards do not define a role for the hospital cancer registry staff but, at C/NET Solutions, we believe that the data collection and management efforts of the registry can be leveraged to effectively screen patients for clinical trials accrual.

LAS: a software platform to support oncological data management.

The rapid technological evolution in the biomedical and molecular oncology fields is providing research laboratories with huge amounts of complex and heterogeneous data. Automated systems are needed to manage and analyze this knowledge, allowing the discovery of new information related to tumors and the improvement of medical treatments. This paper presents the Laboratory Assistant Suite (LAS), a software platform with a modular architecture designed to assist researchers throughout diverse laboratory activities. The LAS supports the management and the integration of heterogeneous biomedical data, and provides graphical tools to build complex analyses on integrated data. Furthermore, the LAS interfaces are designed to ease data collection and management even in hostile environments (e.g., in sterile conditions), so as to improve data quality.

[Database supported electronic retrospective analyses in radiation oncology: establishing a workflow using the example of pancreatic cancer]. / Datenbankbasierte digitale retrospektive Auswertung von Patientenkollektiven in der Radioonkologie: Etablierung eines Workflows am Beispiel des Pankreaskarzinoms.

PURPOSE: Especially in the field of radiation oncology, handling a large variety of voluminous datasets from various information systems in different documentation styles efficiently is crucial for patient care and research. To date, conducting retrospective clinical analyses is rather difficult and time consuming. With the example of patients with pancreatic cancer treated with radio-chemotherapy, we performed a therapy evaluation by using an analysis system connected with a documentation system. MATERIALS AND METHODS: A total number of 783 patients have been documented into a professional, database-based documentation system. Information about radiation therapy, diagnostic images and dose distributions have been imported into the web-based system. RESULTS: For 36 patients with disease progression after neoadjuvant chemoradiation, we designed and established an analysis workflow. After an automatic registration of the radiation plans with the follow-up images, the recurrence volumes are segmented manually. Based on these volumes the DVH (dose volume histogram) statistic is calculated, followed by the determination of the dose applied to the region of recurrence. All results are saved in the database and included in statistical calculations. CONCLUSION: The main goal of using an automatic analysis tool is to reduce time and effort conducting clinical analyses, especially with large patient groups. We showed a first approach and use of some existing tools, however manual interaction is still necessary. Further steps need to be taken to enhance automation. Already, it has become apparent that the benefits of digital data management and analysis lie in the central storage of data and reusability of the results. Therefore, we intend to adapt the analysis system to other types of tumors in radiation oncology.

Development and use of a web-based data management system for a randomized clinical trial of adolescents and young adults.

Recent advances in technology provide support for multisite, Web-based data-entry systems and the storage of data in a centralized location, resulting in immediate access to data for investigators, reduced participant burden and human entry error, and improved integrity of clinical trial data. The purpose of this article was to describe the development of a comprehensive, Web-based data management system for a multisite randomized behavioral intervention trial. Strategies used to create this study-specific data management system included interdisciplinary collaboration, design mapping, feasibility assessments, and input from an advisory board of former patients with characteristics similar to the targeted population. The resulting data management system and development strategies provide a template for other behavioral intervention studies.

Benchmarking biology research organizations using a new, dedicated tool.

International competition forces fundamental research organizations to assess their relative performance. We present a benchmark tool for scientific research organizations where, contrary to existing models, the group leader is placed in a central position within the organization. We used it in a pilot benchmark study involving six research institutions. Our study shows that data collection and data comparison based on this new tool can be achieved. It proved possible to compare relative performance and organizational characteristics and to generate suggestions for improvement for most participants. However, strict definitions of the parameters used for the benchmark and a thorough insight into the organization of each of the benchmark partners is required to produce comparable data and draw firm conclusions.