Evaluation of Free,Open-source,Web-based DICOM Viewers for the Indian National Telemedicine Service (eSanjeevani)

The Digital Image and Communications in Medicine (DICOM) viewer is a very useful component in telemedicine applications. Owing to increased demand, adoption, and prospects of browser-based software in the recent past, web-based DICOM viewers have gained significant ground. There are myriad web-based DICOM viewers which are open source and are available free of cost as stand-alone applications. These freely available tools have rich functionality like the commercial ones. To find an optimal DICOM viewer for integration with a web-based telemedicine solution is quite a challenge, and no research has gone into assessing these freely available DICOM viewers. This research assessed a range of web-based, open-source, and freely available DICOM viewers from the perspective of their integration with the Indian National Telemedicine Solution (eSanjeevani). To introduce teleradiology module in eSanjeevani, a study is carried out to enable viewing of radiological images through DICOM viewer. eSanjeevani is being prepared for a national roll-out at 155,000 health and wellness centers across rural India by the Ministry of Health and Family Welfare (Government of India) under the Ayushman Bharat Scheme (the world’s largest health insurance scheme). In total, 13 free, open-source, and web-based DICOM viewers were identified for evaluation; however, only six were shortlisted as assessed. This study can serve as a one-stop source for researchers looking for a suitable DICOM viewer for their healthcare IT applications.     

A Cloud-Ready Architecture for Shared Medical Imaging Repository

Nowadays usage paradigms of medical imaging resources are requesting vendor-neutral archives, accessible through standard interfaces, with multi-repository support. Regional repositories shared by distinct institutions, tele-radiology as a service at cloud, teaching, and research archives are illustrative examples of this new reality. However, traditional production environments have a server archive instance per functional domain where every registered client application has access to all studies. This paper proposes an innovator ownership concept and access control mechanisms that provide a multi-repository environment and integrates well with standard protocols. A secure accounting mechanism for medical imaging repositories was designed and instantiated as an extension of a well-known open-source archive. A new web service layer was implemented to provide a vendor-neutral solution compliant with modern DICOM Web protocols for storage, search, and retrieval of medical imaging data. The concept validation was done through the integration of proposed architecture in an open-source solution. A quantitative assessment was performed for evaluating the impact of the mechanism in the usual DICOM Web operations. This article proposes a secure accounting architecture able to easily convert a standard medical imaging archive server in a multi-repository solution. The proposal validation was done through a set of tests that demonstrated its robustness and usage feasibility in a production environment. The proposed system offers new services, fundamental in a new era of cloud-based operations, with acceptable temporal costs.     

Open-Source,Web-Based Dashboard Components for DICOM Connectivity

The administration of a DICOM network within an imaging healthcare institution requires tools that allow for monitoring of connectivity and availability for adequate uptime measurements and help guide technology management strategies. We present the implementation of an open-source widget for the Dashing framework that provides basic dashboard functionality allowing for monitoring of a DICOM network using network “ping” and DICOM “C-ECHO” operations.     

Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology

Machine learning (ML) is revolutionizing image-based diagnostics in pathology and radiology. ML models have shown promising results in research settings, but the lack of interoperability between ML systems and enterprise medical imaging systems has been a major barrier for clinical integration and evaluation. The DICOM^® standard specifies information object definitions (IODs) and services for the representation and communication of digital images and related information, including image-derived annotations and analysis results. However, the complexity of the standard represents an obstacle for its adoption in the ML community and creates a need for software libraries and tools that simplify working with datasets in DICOM format. Here we present the highdicom library, which provides a high-level application programming interface (API) for the Python programming language that abstracts low-level details of the standard and enables encoding and decoding of image-derived information in DICOM format in a few lines of Python code. The highdicom library leverages NumPy arrays for efficient data representation and ties into the extensive Python ecosystem for image processing and machine learning. Simultaneously, by simplifying creation and parsing of DICOM-compliant files, highdicom achieves interoperability with the medical imaging systems that hold the data used to train and run ML models, and ultimately communicate and store model outputs for clinical use. We demonstrate through experiments with slide microscopy and computed tomography imaging, that, by bridging these two ecosystems, highdicom enables developers and researchers to train and evaluate state-of-the-art ML models in pathology and radiology while remaining compliant with the DICOM standard and interoperable with clinical systems at all stages. To promote standardization of ML research and streamline the ML model development and deployment process, we made the library available free and open-source at https://github.com/herrmannlab/highdicom.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10278-022-00683-y.     

Anatomy of an Extensible Open Source PACS

The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries’ healthcare institutions. Financial constraints and the specificity of these scenarios contribute to a low adoption rate of PACS in those environments. Furthermore, with the advent of ubiquitous computing and new initiatives to improve healthcare information technologies and data sharing, such as IHE and XDS-i, a PACS must adapt quickly to changes. This paper describes Dicoogle, a software framework that enables developers and researchers to quickly prototype and deploy new functionality taking advantage of the embedded Digital Imaging and Communications in Medicine (DICOM) services. This full-fledged implementation of a PACS archive is very amenable to extension due to its plugin-based architecture and out-of-the-box functionality, which enables the exploration of large DICOM datasets and associated metadata. These characteristics make the proposed solution very interesting for prototyping, experimentation, and bridging functionality with deployed applications. Besides being an advanced mechanism for data discovery and retrieval based on DICOM object indexing, it enables the detection of inconsistencies in an institution’s data and processes. Several use cases have benefited from this approach such as radiation dosage monitoring, Content-Based Image Retrieval (CBIR), and the use of the framework as support for classes targeting software engineering for clinical contexts.     

The Orthanc Ecosystem for Medical Imaging

This paper reviews the components of Orthanc, a free and open-source, highly versatile ecosystem for medical imaging. At the core of the Orthanc ecosystem, the Orthanc server is a lightweight vendor neutral archive that provides PACS managers with a powerful environment to automate and optimize the imaging flows that are very specific to each hospital. The Orthanc server can be extended with plugins that provide solutions for teleradiology, digital pathology, or enterprise-ready databases. It is shown how software developers and research engineers can easily develop external software or Web portals dealing with medical images, with minimal knowledge of the DICOM standard, thanks to the advanced programming interface of the Orthanc server. The paper concludes by introducing the Stone of Orthanc, an innovative toolkit for the cross-platform rendering of medical images.     

Linking Whole-Slide Microscope Images with DICOM by Using JPEG2000 Interactive Protocol

The use of digitized histopathologic specimens (also known as whole-slide images (WSIs)) in clinical medicine requires compatibility with the Digital Imaging and Communications in Medicine (DICOM) standard. Unfortunately, WSIs usually exceed DICOM image object size limit, making it impossible to store and exchange them in a straightforward way. Moreover, transmitting the entire DICOM image for viewing is ineffective for WSIs. With the JPEG2000 Interactive Protocol (JPIP), WSIs can be linked with DICOM by transmitting image data over an auxiliary connection, apart from patient data. In this study, we explored the feasibility of using JPIP to link JPEG2000 WSIs with a DICOM-based Picture Archiving and Communications System (PACS). We first modified an open-source DICOM library by adding support for JPIP as described in the existing DICOM Supplement 106. Second, the modified library was used as a basis for a software package (JVSdicom), which provides a proof-of-concept for a DICOM client–server system that can transmit patient data, conventional DICOM imagery (e.g., radiological), and JPIP-linked JPEG2000 WSIs. The software package consists of a compression application (JVSdicom Compressor) for producing DICOM-compatible JPEG2000 WSIs, a DICOM PACS server application (JVSdicom Server), and a DICOM PACS client application (JVSdicom Workstation). JVSdicom is available for free from our Web site (), which also features a public JVSdicom Server, containing example X-ray images and histopathology WSIs of breast cancer cases. The software developed indicates that JPEG2000 and JPIP provide a well-working solution for linking WSIs with DICOM, requiring only minor modifications to current DICOM standard specification.     

A conceptual framework for patient-directed knowledge tools to support patient-centred care: Results from an evidence-informed consensus meeting

ObjectivePatient-directed knowledge tools are designed to engage patients in dialogue or deliberation, to support patient decision-making or self-care of chronic conditions. However, an abundance of these exists. The tools themselves and their purposes are not always clearly defined; creating challenges for developers and users (professionals, patients). The study’s aim was to develop a conceptual framework of patient-directed knowledge tool types.MethodsA face-to-face evidence-informed consensus meeting with 15 international experts. After the meeting, the framework went through two rounds of feedback before informal consensus was reached.ResultsA conceptual framework containing five patient-directed knowledge tool types was developed. The first part of the framework describes the tools’ purposes and the second focuses on the tools’ core elements.ConclusionThe framework provides clarity on which types of patient-directed tools exist, the purposes they serve, and which core elements they prototypically include. It is a working framework and will require further refinement as the area develops, alongside validation with a broader group of stakeholders.Practice implicationsThe framework assists developers and users to know which type a tool belongs, its purpose and core elements, helping them to develop and use the right tool for the right job.     

Protégé: A Tool for Managing and Using Terminology in Radiology Applications

The development of standard terminologies such as RadLex is becoming important in radiology applications, such as structured reporting, teaching file authoring, report indexing, and text mining. The development and maintenance of these terminologies are challenging, however, because there are few specialized tools to help developers to browse, visualize, and edit large taxonomies. Protégé (http://protege.stanford.edu) is an open-source tool that allows developers to create and to manage terminologies and ontologies. It is more than a terminology-editing tool, as it also provides a platform for developers to use the terminologies in end-user applications. There are more than 70,000 registered users of Protégé who are using the system to manage terminologies and ontologies in many different domains. The RadLex project has recently adopted Protégé for managing its radiology terminology. Protégé provides several features particularly useful to managing radiology terminologies: an intuitive graphical user interface for navigating large taxonomies, visualization components for viewing complex term relationships, and a programming interface so developers can create terminology-driven radiology applications. In addition, Protégé has an extensible plug-in architecture, and its large user community has contributed a rich library of components and extensions that provide much additional useful functionalities. In this report, we describe Protégé’s features and its particular advantages in the radiology domain in the creation, maintenance, and use of radiology terminology.     

The department of veterans affairs integration of imaging into the healthcare enterprise using the VistA hospital information system and Digital Imaging and Communications in Medicine

The United States Department of Veterans Affairs is integrating imaging into the healthcare enterprise by using the Digital Imaging and Communication in Medicine (DICOM) standard protocols. Image management is directly integrated into the VistA Hospital Information System (HIS) software and clinical database. Radiology images are acquired with DICOM and are stored directly in the HIS database. Images can be displayed on low-cost clinician’s workstations throughout the medical center. High-resolution diagnostic quality multimonitor VistA workstations with specialized viewing software can be used for reading radiology images. Two approaches are used to acquire and handle images within the radiology department. Some sites have a commercial Picture Archiving and Communications System (PACS) interfaced to the VistA HIS, whereas other sites use the direct image acquisition and integrated diagnostic display capabilities of VistA itself. A small set of DICOM services has been implemented by VistA to allow patient and study text data to be transmitted to image producing modalities and the commercial PACS, and to enable images and study data to be transferred back. DICOM has been the cornerstone in the ability to integrate imaging functionality into the healthcare enterprise. Because of its openness, it allows the integration of system components from commercial and noncommercial sources to work together to provide functional cost-effective solutions.     

A Workflow for Ensuring DICOM Compatibility During Radiography Device Software Development

In medical devices, nonconformance with Digital Imaging and Communications in Medicine (DICOM) standard is a serious risk. DICOM nonconformance radiology devices could cause undetected image loss, increasing examination time, and costs in health centers and could even result in the wrong patient treatment. However, there is a rich literature on medical standards that identify the best practices for producing safe and effective medical software. However, these standards do not expressly provide tools to deal with all the relevant DICOM compatibility issues in a specific case. This study aims to introduce a systematic software development workflow that complies with medical standards and ensures DICOM conformance of a new or upgraded radiology software project. In this approach, DICOM conformance gets the highest priority, and the whole software project is organized around it. Software requirement analysis, risk evaluation, and test management tasks are arranged systematically to make the final device DICOM conformant. This conceptual framework was developed during the R&D work towards a novel radiography device, and it could be employed as a roadmap in other medical imaging software projects. The proposed methodology controls the DICOM compatibility risk of the final software, and its systematic evaluation complied with medical standards.

     

Learning HL7 FHIR Using the HAPI FHIR Server and Its Use in Medical Imaging with the SIIM Dataset

Health Level 7’s (HL7’s) new standard, FHIR (Fast Health Interoperability Resources), is setting healthcare information technology and medical imaging specifically ablaze with excitement. This paper aims to describe the protocol’s advantages in some detail and explore an easy path for those unfamiliar with FHIR to begin learning the standard using free, open-source tools, namely the HL7 application programming interface (HAPI) FHIR server and the SIIM Hackathon Dataset.     

Integration of the Image-Guided Surgery Toolkit (IGSTK) into the Medical Imaging Interaction Toolkit (MITK)

The development cycle of an image-guided surgery navigation system is too long to meet current clinical needs. This paper presents an integrated system developed by the integration of two open-source software (IGSTK and MITK) to shorten the development cycle of the image-guided surgery navigation system and save human resources simultaneously. An image-guided surgery navigation system was established by connecting the two aforementioned open-source software libraries. It used the Medical Imaging Interaction Toolkit (MITK) as a framework providing image processing tools for the image-guided surgery navigation system of medical imaging software with a high degree of interaction and used the Image-Guided Surgery Toolkit (IGSTK) as a library that provided the basic components of the system for location, tracking, and registration. The electromagnetic tracking device was used to measure the real-time position of surgical tools and fiducials attached to the patient’s anatomy. IGSTK was integrated into MITK; at the same time, the compatibility and the stability of this system were emphasized. Experiments showed that an integrated system of the image-guided surgery navigation system could be developed in 2 months. The integration of IGSTK into MITK is feasible. Several techniques for 3D reconstruction, geometric analysis, mesh generation, and surface data analysis for medical image analysis of MITK can connect with the techniques for location, tracking, and registration of IGSTK. This integration of advanced modalities can decrease software development time and emphasize the precision, safety, and robustness of the image-guided surgery navigation system.     

A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System

Open-source development can provide a platform for innovation by seeking feedback from community members as well as providing tools and infrastructure to test new standards. Vendors of proprietary systems may delay adoption of new standards until there are sufficient incentives such as legal mandates or financial incentives to encourage/mandate adoption. Moreover, open-source systems in healthcare have been widely adopted in low- and middle-income countries and can be used to bridge gaps that exist in global health radiology. Since 2011, the authors, along with a community of open-source contributors, have worked on developing an open-source radiology information system (RIS) across two communities—OpenMRS and LibreHealth. The main purpose of the RIS is to implement core radiology workflows, on which others can build and test new radiology standards. This work has resulted in three major releases of the system, with current architectural changes driven by changing technology, development of new standards in health and imaging informatics, and changing user needs. At their core, both these communities are focused on building general-purpose EHR systems, but based on user contributions from the fringes, we have been able to create an innovative system that has been used by hospitals and clinics in four different countries. We provide an overview of the history of the LibreHealth RIS, the architecture of the system, overview of standards integration, describe challenges of developing an open-source product, and future directions. Our goal is to attract more participation and involvement to further develop the LibreHealth RIS into an Enterprise Imaging System that can be used in other clinical imaging including pathology and dermatology.     

Image Data Sharing for Biomedical Research—Meeting HIPAA Requirements for De-identification

Data sharing is increasingly recognized as critical to cross-disciplinary research and to assuring scientific validity. Despite National Institutes of Health and National Science Foundation policies encouraging data sharing by grantees, little data sharing of clinical data has in fact occurred. A principal reason often given is the potential of inadvertent violation of the Health Insurance Portability and Accountability Act privacy regulations. While regulations specify the components of private health information that should be protected, there are no commonly accepted methods to de-identify clinical data objects such as images. This leads institutions to take conservative risk-averse positions on data sharing. In imaging trials, where images are coded according to the Digital Imaging and Communications in Medicine (DICOM) standard, the complexity of the data objects and the flexibility of the DICOM standard have made it especially difficult to meet privacy protection objectives. The recent release of DICOM Supplement 142 on image de-identification has removed much of this impediment. This article describes the development of an open-source software suite that implements DICOM Supplement 142 as part of the National Biomedical Imaging Archive (NBIA). It also describes the lessons learned by the authors as NBIA has acquired more than 20 image collections encompassing over 30 million images.     

Development of a Next-Generation Automated DICOM Processing System in a PACS-Less Research Environment

The use of clinical imaging modalities within the pharmaceutical research space provides value and challenges. Typical clinical settings will utilize a Picture Archive and Communication System (PACS) to transmit and manage Digital Imaging and Communications in Medicine (DICOM) images generated by clinical imaging systems. However, a PACS is complex and provides many features that are not required within a research setting, making it difficult to generate a business case and determine the return on investment. We have developed a next-generation DICOM processing system using open-source software, commodity server hardware such as Apple Xserve®, high-performance network-attached storage (NAS), and in-house-developed preprocessing programs. DICOM-transmitted files are arranged in a flat file folder hierarchy easily accessible via our downstream analysis tools and a standard file browser. This next-generation system had a minimal construction cost due to the reuse of all the components from our first-generation system with the addition of a second server for a few thousand dollars. Performance metrics were gathered and the system was found to be highly scalable, performed significantly better than the first-generation system, is modular, has satisfactory image integrity, and is easier to maintain than the first-generation system. The resulting system is also portable across platforms and utilizes minimal hardware resources, allowing for easier upgrades and migration to smaller form factors at the hardware end-of-life. This system has been in production successfully for 8 months and services five clinical instruments and three pre-clinical instruments. This system has provided us with the necessary DICOM C-Store functionality, eliminating the need for a clinical PACS for day-to-day image processing.