Unlocking the PACS DICOM Domain for its Use in Clinical Research Data Warehouses.
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ABSTRACT:
SUBMITTER: Kaspar M
PROVIDER: S-EPMC7522145 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Providing surrogate endpoints in clinical trials, medical imaging has become increasingly important in human-centered research. Nowadays, electronic data capture systems (EDCS) are used but binary image data is integrated insufficiently. There exists no structured way, neither to manage digital imaging and communications in medicine (DICOM) data in EDCS nor to interconnect EDCS with picture archiving and communication systems (PACS). Manual detours in the trial workflow yield errors, delays, and costs. In this paper, requirements for a DICOM-based system interconnection of EDCS and research PACS are analysed. Several workflow architectures are compared. Optimized for multi-center trials, we propose an entirely web-based solution integrating EDCS, PACS, and DICOM viewer, which has been implemented using the open source projects OpenClinica, DCM4CHEE, and Weasis, respectively. The EDCS forms the primary access point. EDCS to PACS interchange is integrated seamlessly on the data and the context levels. DICOM data is viewed directly from the electronic case report form (eCRF), while PACS-based management is hidden from the user. Data privacy is ensured by automatic de-identification and re-labelling with study identifiers. Our concept is evaluated on a variety of 13 DICOM modalities and transfer syntaxes. We have implemented the system in an ongoing investigator-initiated trial (IIT), where five centers have recruited 24 patients so far, performing decentralized computed tomography (CT) screening. Using our system, the chief radiologist is reading DICOM data directly from the eCRF. Errors and workflow processing time are reduced. Furthermore, an imaging database is built that may support future research.
| S-EPMC4570903 | biostudies-literature
Project description:ObjectiveAmong National Institutes of Health Clinical and Translational Science Award (CTSA) hubs, adoption of electronic data warehouses for research (EDW4R) containing data from electronic health record systems is nearly ubiquitous. Although benefits of EDW4R include more effective, efficient support of scientists, little is known about how CTSA hubs have implemented EDW4R services. The goal of this qualitative study was to understand the ways in which CTSA hubs have operationalized EDW4R to support clinical and translational researchers.Materials and methodsAfter conducting semistructured interviews with informatics leaders from 20 CTSA hubs, we performed a directed content analysis of interview notes informed by naturalistic inquiry.ResultsWe identified 12 themes: organization and data; oversight and governance; data access request process; data access modalities; data access for users with different skill sets; engagement, communication, and literacy; service management coordinated with enterprise information technology; service management coordinated within a CTSA hub; service management coordinated between informatics and biostatistics; funding approaches; performance metrics; and future trends and current technology challenges.DiscussionThis study is a step in developing an improved understanding and creating a common vocabulary about EDW4R operations across institutions. Findings indicate an opportunity for establishing best practices for EDW4R operations in academic medicine. Such guidance could reduce the costs associated with developing an EDW4R by establishing a clear roadmap and maturity path for institutions to follow.ConclusionsCTSA hubs described varying approaches to EDW4R operations that may assist other institutions in better serving investigators with electronic patient data.
| S-EPMC7647350 | biostudies-literature
Project description:ObjectiveAmong National Institutes of Health Clinical and Translational Science Award (CTSA) hubs, effective approaches for enterprise data warehouses for research (EDW4R) development, maintenance, and sustainability remain unclear. The goal of this qualitative study was to understand CTSA EDW4R operations within the broader contexts of academic medical centers and technology.Materials and methodsWe performed a directed content analysis of transcripts generated from semistructured interviews with informatics leaders from 20 CTSA hubs.ResultsRespondents referred to services provided by health system, university, and medical school information technology (IT) organizations as "enterprise information technology (IT)." Seventy-five percent of respondents stated that the team providing EDW4R service at their hub was separate from enterprise IT; strong relationships between EDW4R teams and enterprise IT were critical for success. Managing challenges of EDW4R staffing was made easier by executive leadership support. Data governance appeared to be a work in progress, as most hubs reported complex and incomplete processes, especially for commercial data sharing. Although nearly all hubs (n = 16) described use of cloud computing for specific projects, only 2 hubs reported using a cloud-based EDW4R. Respondents described EDW4R cloud migration facilitators, barriers, and opportunities.DiscussionDescriptions of approaches to how EDW4R teams at CTSA hubs work with enterprise IT organizations, manage workforces, make decisions about data, and approach cloud computing provide insights for institutions seeking to leverage patient data for research.ConclusionIdentification of EDW4R best practices is challenging, and this study helps identify a breadth of viable options for CTSA hubs to consider when implementing EDW4R services.
| S-EPMC8922193 | biostudies-literature
Project description:BackgroundThe promises of improved health care and health research through data-intensive applications rely on a growing amount of health data. At the core of large-scale data integration efforts, clinical data warehouses (CDW) are also responsible for data governance, managing data access and (re)use. As the complexity of the data flow increases, greater transparency and standardization of criteria and procedures are required in order to maintain objective oversight and control. Therefore, the development of practice oriented and evidence-based policies is crucial. This study assessed the spectrum of data access and use criteria and procedures in clinical data warehouses governance internationally.MethodsWe performed a systematic review of (a) the published scientific literature on CDW and (b) publicly available information on CDW data access, e.g., data access policies. A qualitative thematic analysis was applied to all included literature and policies.ResultsTwenty-three scientific publications and one policy document were included in the final analysis. The qualitative analysis led to a final set of three main thematic categories: (1) requirements, including recipient requirements, reuse requirements, and formal requirements; (2) structures and processes, including review bodies and review values; and (3) access, including access limitations.ConclusionsThe description of data access and use governance in the scientific literature is characterized by a high level of heterogeneity and ambiguity. In practice, this might limit the effective data sharing needed to fulfil the high expectations of data-intensive approaches in medical research and health care. The lack of publicly available information on access policies conflicts with ethical requirements linked to principles of transparency and accountability. CDW should publicly disclose by whom and under which conditions data can be accessed, and provide designated governance structures and policies to increase transparency on data access. The results of this review may contribute to the development of practice-oriented minimal standards for the governance of data access, which could also result in a stronger harmonization, efficiency, and effectiveness of CDW.
| S-EPMC7353743 | biostudies-literature
Project description:Our study recalculated the use factor of linear accelerators (LINACs) by using an in-house program based on Digital Imaging and Communications in Medicine radiation therapy (DICOM-RT). We considered the impact of advancements and changes in treatment trends, including modality, technology, and radiation dose, on the use factor, which is one of the shielding parameters. In accordance with the methodology described in the NCRP 151 report, we computed the use factor for four linear accelerators (LINACs) across three hospitals. We analyzed the results based on the treatment techniques and treatment sites for three-dimensional conformal radiation therapy (3D-CRT) and intensity modulated radiation therapy or volumetric modulated arc therapy. Our findings revealed that the use factors obtained at 45° and 90° were 14.8% and 13.5% higher than those of the NCRP 151 report. In treatment rooms with a high 3D-CRT ratio, the use factor at a specific angle differed by up to 14.6% relative to the NCRP 151 report value. Our results showed a large difference in the use factor for specific sites such as the breast and spine, so it is recommended that each institution recalculate the use factor using patient's data.
| S-EPMC10480328 | biostudies-literature
Project description:ObjectiveHealthcare organizations use research data models supported by projects and tools that interest them, which often means organizations must support the same data in multiple models. The healthcare research ecosystem would benefit if tools and projects could be adopted independently from the underlying data model. Here, we introduce the concept of a reusable application programming interface (API) for healthcare and show that the i2b2 API can be adapted to support diverse patient-centric data models.Materials and methodsWe develop methodology for extending i2b2's pre-existing API to query additional data models, using i2b2's recent "multi-fact-table querying" feature. Our method involves developing data-model-specific i2b2 ontologies and mapping these to query non-standard table structure.ResultsWe implement this methodology to query OMOP and PCORnet models, which we validate with the i2b2 query tool. We implement the entire PCORnet data model and a five-domain subset of the OMOP model. We also demonstrate that additional, ancillary data model columns can be modeled and queried as i2b2 "modifiers."Discussioni2b2's REST API can be used to query multiple healthcare data models, enabling shared tooling to have a choice of backend data stores. This enables separation between data model and software tooling for some of the more popular open analytic data models in healthcare.ConclusionThis methodology immediately allows querying OMOP and PCORnet using the i2b2 API. It is released as an open-source set of Docker images, and also on the i2b2 community wiki.
| S-EPMC6188504 | biostudies-literature
Project description:Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.
| S-EPMC4888317 | biostudies-literature
Project description:Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant additional data. The Grayscale Softcopy Presentation State extension of the Digital Imaging and Communications in Medicine (DICOM) standard resolves this issue for two-dimensional (2D) data by introducing an extensive set of parameters, namely 2D Presentation States (2DPR), that describe how an image should be displayed. 2DPR allows storing these parameters instead of storing parameter applied images, which cause unnecessary duplication of the image data. Since there is currently no corresponding extension for 3D data, in this study, a DICOM-compliant object called 3D presentation states (3DPR) is proposed for the parameterization and storage of 3D medical volumes. To accomplish this, the 3D medical visualization process is divided into four tasks, namely pre-processing, segmentation, post-processing, and rendering. The important parameters of each task are determined. Special focus is given to the compression of segmented data, parameterization of the rendering process, and DICOM-compliant implementation of the 3DPR object. The use of 3DPR was tested in a radiology department on three clinical cases, which require multiple segmentations and visualizations during the workflow of radiologists. The results show that 3DPR can effectively simplify the workload of physicians by directly regenerating 3D renderings without repeating intermediate tasks, increase efficiency by preserving all user interactions, and provide efficient storage as well as transfer of visualized data.
| S-EPMC4666236 | biostudies-literature
Project description:BackgroundImplementation of patient preferences for use of electronic health records for research has been traditionally limited to identifiable data. Tiered e-consent for use of de-identified data has traditionally been deemed unnecessary or impractical for implementation in clinical settings.MethodsWe developed a web-based tiered informed consent tool called informed consent for clinical data and bio-sample use for research (iCONCUR) that honors granular patient preferences for use of electronic health record data in research. We piloted this tool in 4 outpatient clinics of an academic medical center.ResultsOf patients offered access to iCONCUR, 394 agreed to participate in this study, among whom 126 patients accessed the website to modify their records according to data category and data recipient. The majority consented to share most of their data and specimens with researchers. Willingness to share was greater among participants from an Human Immunodeficiency Virus (HIV) clinic than those from internal medicine clinics. The number of items declined was higher for for-profit institution recipients. Overall, participants were most willing to share demographics and body measurements and least willing to share family history and financial data. Participants indicated that having granular choices for data sharing was appropriate, and that they liked being informed about who was using their data for what purposes, as well as about outcomes of the research.ConclusionThis study suggests that a tiered electronic informed consent system is a workable solution that respects patient preferences, increases satisfaction, and does not significantly affect participation in research.
| S-EPMC5391727 | biostudies-literature
Project description:Background/aimsCoronavirus Disease 2019 (COVID-19) has presented an unprecedented challenge for delivering clinical research. The use of technology-assisted data collection for clinical research is desirable for many practitioners, but the acceptability of use in the general population has not been assessed. The aim of the study was to assess attitudes towards using technology-assisted remote methods in the delivery of clinical research in the UK and to understand the barriers to taking part in research with respect to both remote assessments and traditional research methods across different age ranges.MethodsThe study was conducted as an online anonymous survey with a 4-part questionnaire, between August 2020 and December 2020. Participants living in the UK aged 18 years and above were eligible to take part.ResultsA total 351 completed the survey and are included in the data analysis. In all age groups, participants identified that use of online assignments, video calls and telephone calls would make them more likely to take part in clinical research. Overall, the largest barrier to taking part in research was time commitments and timing of the appointment. COVID-19 has had a small, positive influence on the confidence of using technology in the general population.ConclusionsThe study found that there is a large interest in taking part in research using online, telephone and video call appointments, which could facilitate research delivery in light of ongoing COVID-19-related restrictions and also improve the accessibility and inclusivity of research.
| S-EPMC8511885 | biostudies-literature