Effect of picture archiving and communication system on diagnosis accuracy in CT and radiography examinations in emergency departments.

INTRODUCTION: Picture archiving and communication system (PACS) affects the radiologists' and physicians' performance. We aimed to evaluate the effect of implementing PACS on the emergency department (ED) physicians' accuracy compared to a radiologist's diagnosis in Iran. METHODS: We retrospectively collected data for three six-month periods before and after the implementation of PACS on CT scan and radiography examinations. We compared ED physicians' diagnoses of CT scan and radiography images with a radiologist's interpretations for the same images. We compared 374 CT scans and 346 radiography examinations before implementing PACS (July 2015 to December 2015); 507 CT scans and 480 radiography examinations immediately after PACS (July 2016 to December 2016); and 870 CT scans and 1137 radiography examinations one year after PACS (July 2017 to December 2017). RESULTS: We found that diagnosis accuracy of ED physicians on CT scans increased from 75.9 % before implementing PACS to 84.4 % immediately after PACS and 94.9 % one year after PACS (p-value < 0.0001). Diagnosis accuracy for radiography images increased from 63.0 % before implementing PACS to 80.2 % immediately after PACS and 93.1 % one year after PACS (p-value < 0.0001). CONCLUSION: Implementation of PACS technology increases ED physicians' diagnosis accuracy.

How is the use of digital dental radiology in a developing country? An overview of Brazil / ¿Cómo es el uso de la radiología dental digital en un país en vías de desarrollo? Una visión general de Brasil

Abstract The aim of this study was to assess the use of digital dental radiology in Brazil, by focusing on the use of image receptors, imaging exams and digital image enhancement tools, also assessing the methods of professional image transfer. Questionnaires were distributed in person on dental meetings and digitally via messaging (WhatsApp®) and mailings list. The sample of this cross-sectional study consisted of 478 questionnaires. Most participants were woman (n=315, 65.9%), with average age of 33.8±9.2 years. Descriptive and frequency analysis was performed. Chi-square and Fisher's exact tests were used (α=0.05). Most dentists worked at shared dental clinics (34.7%) and use digital image receptors (51.1%), but a representative percentage (48.9%) still exclusively use radiographic films. Photostimulable phosphor plate is the most used digital image receptor. Among extraoral exams, panoramic radiography (PAN) is the most used. Regarding dental specialties, oral radiologists and oral and maxillofacial surgeons mostly use cone-beam computed tomography (p<0.001). Most dentists who use digital systems make use of digital image enhancement tools (87.8%), mainly contrast, zoom, brightness and measurements. The most common method of professional image transfer (professional-professional and professional-patiens) is by email, with few dentists using online app and social media (26%). Therefore, while most Brazilian dentists use digital imaging systems, a significant percentage still exclusively use radiographic films. The most extraoral imaging exams used is PAN. Regarding image enhancement tools, brightness and contrast adjustments, zoom and measurements are the most applied. Finally, dentists generally use email for professional image transfer.

Resumen El objetivo de este estudio fue evaluar uso de la radiología dental digital en Brasil, centrándose en uso de receptores de imagen, exámenes de imágenes y herramientas de mejora de imagen digital, evaluando también los métodos de transferencia de imagen profesional. Cuestionarios se distribuyeron de forma presencial en reuniones odontológicas y de forma digital a través de mensajería (WhatsApp®) y lista de correo. Muestra de este estudio transversal estuvo compuesta por 478 cuestionarios. Mayoría de los participantes eran mujeres (n=315, 65,9%), con edad promedio de 33,8±9,2 años. Se realizó un análisis descriptivo y de frecuencias. Se utilizaron las pruebas Chi-cuadrado y exacta de Fisher (α=0,05). La mayoría de los odontólogos trabajaban en clínicas dentales compartidas (34,7%) y utilizan receptores de imágenes digitales (51,1%), pero un porcentaje representativo (48,9%) todavía utiliza exclusivamente películas radiográficas. Placa de fósforo fotoestimulable es el receptor de imagen digital más utilizado. Entre los exámenes extraorales, la radiografía panorámica (PAN) es la más utilizada. En cuanto a las especialidades odontológicas, los radiólogos orales y los cirujanos orales y maxilofaciales utilizan mayoritariamente la tomografía computarizada de haz cónico (p<0,001). Mayoría de los odontólogos que utilizan sistemas digitales utilizan herramientas de mejora de imagen digital (87,8%), principalmente contraste, zoom, brillo y medidas. Método más común de transferencia de imágenes profesionales (profesional-profesional y profesional-pacientes) es por correo electrónico, con pocos dentistas que utilizan aplicaciones en línea y redes sociales (26%). Por lo tanto, mientras que la mayoría de dentistas brasileños utilizan sistemas de imágenes digitales, un porcentaje significativo aún utiliza exclusivamente películas radiográficas. Examen de imagen extraoral más utilizado es el PAN. En cuanto a las herramientas de mejora de imagen, los ajustes de brillo y contraste, el zoom y las medidas son las más aplicadas. Finalmente, los dentistas generalmente usan el correo electrónico para la transferencia de imágenes profesionales.

Design and Implementation of a Cloud PACS Architecture.

The limitations of the classic PACS (picture archiving and communication system), such as the backward-compatible DICOM network architecture and poor security and maintenance, are well-known. They are challenged by various existing solutions employing cloud-related patterns and services. However, a full-scale cloud-native PACS has not yet been demonstrated. The paper introduces a vendor-neutral cloud PACS architecture. It is divided into two main components: a cloud platform and an access device. The cloud platform is responsible for nearline (long-term) image archive, data flow, and backend management. It operates in multi-tenant mode. The access device is responsible for the local DICOM (Digital Imaging and Communications in Medicine) interface and serves as a gateway to cloud services. The cloud PACS was first implemented in an Amazon Web Services environment. It employs a number of general-purpose services designed or adapted for a cloud environment, including Kafka, OpenSearch, and Memcached. Custom services, such as a central PACS node, queue manager, or flow worker, also developed as cloud microservices, bring DICOM support, external integration, and a management layer. The PACS was verified using image traffic from, among others, computed tomography (CT), magnetic resonance (MR), and computed radiography (CR) modalities. During the test, the system was reliably storing and accessing image data. In following tests, scaling behavior differences between the monolithic Dcm4chee server and the proposed solution are shown. The growing number of parallel connections did not influence the monolithic server's overall throughput, whereas the performance of cloud PACS noticeably increased. In the final test, different retrieval patterns were evaluated to assess performance under different scenarios. The current production environment stores over 450 TB of image data and handles over 4000 DICOM nodes.

Dicoogle Open Source: The Establishment of a New Paradigm in Medical Imaging.

The rapid and continuous growth of data volume and its heterogeneity has become one of the most noticeable trends in healthcare, namely in medical imaging. This evolution led to the deployment of specialized information systems supported by the DICOM standard that enables the interoperability of distinct components, including imaging modalities, repositories, and visualization workstations. However, the complexity of these ecosystems leads to challenging learning curves and makes it time-consuming to mock and apply new ideas. Dicoogle is an extensible medical imaging archive server that emerges as a tool to overcome those challenges. Its extensible architecture allows the fast development of new advanced features or extends existent ones. It is currently a fundamental enabling technology in collaborative and telehealthcare environments, including research projects, screening programs, and teleradiology services. The framework is supported by a Learning Pack that includes a description of the web programmatic interface, a software development kit, documentation, and implementation samples. This article gives an in-depth view of the Dicoogle ecosystem, state-of-the-art contributions, and community impact. It starts by presenting an overview of its architectural concept, highlights some of the most representative research backed up by Dicoogle, some remarks obtained from its use in teaching, and worldwide usage statistics of the software. Finally, the positioning of Dicoogle in the medical imaging software field is discussed through comparison with other well-known solutions.

Image Exchange in the Middle East: a Survey.

Developing an enterprise approach to imaging technology rather than a radiology focus has recently increased. The communicator needs to be aware of this shift.The Middle East countries participated in the survey have confirmed the following major benefits of Medical Image Exchange: ✔ Fast access to both image and report ✔ Enable tele-services for second opinion, consulting and reporting ✔ Improve patient journey, workflow and diagnosis ✔ Allowed more patient engagement to be in place The Middle East countries that participated in this survey have agreed on the following shared challenges regarding Medical Imaging Exchange: ✔ Lack of enterprise imaging governance at the early stage of implementation. It will organize the who, when, and how. In addition, any fees and or payment involved for physicians ✔ Infrastructure availability to handle such large volume of data. Growing from mega-byte to petabyte per year is challenge for infrastructure. Cloud against On Premises-Installation implementation model ✔ Interoperability and integration to connect multi specialties from different systems. In addition, how far existing systems are ready for that. A standard-based framework is mature for image exchange, but what follows for other domains? There is a need to move beyond radiology images so as to include images from pathology, ophthalmology, and dermatology There are other countries in the region requiring guidance, support, and funding to move forward from the compact disc into internet-based interoperable image exchange. This should be considered part of the World Health Organization and the United Nation development to the region in the healthcare sector.

Securing Your Radiology Practice: Evidence-Based Strategies for Radiologists Compiled From 10 Years of Cyberattacks and HIPAA Breaches Involving Medical Imaging.

While there is significant literature discussing physical and cybersecurity risks around health information technology in general, the number of publications that specifically address medical imaging is much smaller, and many of these focus on the technical security requirements for the exchange of medical images over public networks rather than practical guidelines for radiologists and technicians. This study examines the US Department of Health and Human Services database of reported breaches involving medical imaging from 2010-2020, identifies the most common contributing factors to those breaches, and offers recommendations for radiology practices to prevent each, based on the National Institute of Standards and Technology (NIST) guidelines as well as measures proposed in the literature on health information technology.

THE IMPORTANCE OF FEEDBACK IN MONITORING PATIENTS' RADIATION DOSES IN MAMMOGRAPHY.

The majority of medical facilities in the Slovak Republic archive diagnostic images of their patients in a picture archiving and communicating system (PACS). Data from the PACS system can be used to analyse patient radiation dose and perform internal and external quality control through dose monitoring software systems. However, appropriate use of such systems requires the provision of feedback and the ability of staff to identify causes of diagnostic reference level exceedances. The present pilot study evaluated the use of a Dose quality control system (DQC) for monitoring the radiation dose of the patients in the ongoing mammography screening, with subsequent identification of alerts triggered by the system.

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 .

The RSNA ImageShare - Enabling Secure, Transparent, and Easy Image Exchange.

In the early 2000s, the radiology community was awakened to the limitations of electronic media (CDs, DVDs) for exchanging imaging exams. Clinicians frustrated by the time-consuming task of opening discs, while Internet-based exchange of music, photos, and videos were becoming more widespread. The RSNA, which had extensive experience working on interoperability issues in medical imaging, began to look for opportunities to address the issue. In 2007, in the wake of the financial crisis, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) issued an RFP to address Internet-based exchange of medical images. The RFP defined requirements for the network, including that it needed to be patient controlled and standards based. The RSNA was awarded funding for what came to be known as RSNA ImageShare. Over the next 8 years, the RSNA worked in partnership with several vendors and academic institutions to create a network for sharing image-enabled personal health records (PHR). The foundation of interoperability standards used in ImageShare was provided by Integrating the Healthcare Enterprise (IHE), a standards-development organization with which RSNA has had a long association. In 2018 and 2019, the RSNA looked at what had been accomplished and asked if we could take that next step at a national level and promote a solution by which any standards-compliant party could exchange imaging exams through an HIE mechanism.

Creation of a Multi-vendor Image-Sharing Solution.

Transferring medical imaging studies from one institution to another is a common occurrence in today's medical practice. For the past two decades, radiology departments have relied on physical media (compact discs and digital video disks) and human couriers to accomplish image transfer. This mode of transfer is slow, prone to failure, and reliant on outdated technology. To address these shortcomings, multiple image-sharing vendors have created electronic, cloud-based solutions. While these solutions solve multiple problems, a new problem has been introduced: it is difficult to send or receive images across image-sharing platforms. In this work, we describe how we have developed a solution to share images across multiple vendor platforms.

Interactive Multimedia Reporting Technical Considerations: HIMSS-SIIM Collaborative White Paper.

Despite technological advances in the analysis of digital images for medical consultations, many health information systems lack the ability to correlate textual descriptions of image findings linked to the actual images. Images and reports often reside in separate silos in the medical record throughout the process of image viewing, report authoring, and report consumption. Forward-thinking centers and early adopters have created interactive reports with multimedia elements and embedded hyperlinks in reports that connect the narrative text with the related source images and measurements. Most of these solutions rely on proprietary single-vendor systems for viewing and reporting in the absence of any encompassing industry standards to facilitate interoperability with the electronic health record (EHR) and other systems. International standards have enabled the digitization of image acquisition, storage, viewing, and structured reporting. These provide the foundation to discuss enhanced reporting. Lessons learned in the digital transformation of radiology and pathology can serve as a basis for interactive multimedia reporting (IMR) across image-centric medical specialties. This paper describes the standard-based infrastructure and communications to fulfill recently defined clinical requirements through a consensus from an international workgroup of multidisciplinary medical specialists, informaticists, and industry participants. These efforts have led toward the development of an Integrating the Healthcare Enterprise (IHE) profile that will serve as a foundation for interoperable interactive multimedia reporting.

The patient-friendly radiology report: history, evolution, challenges and opportunities.

The past several decades have witnessed dramatic developments and improvements in the field of radiology, including technologic innovations and new imaging modalities, picture archiving and communication systems, and the rise of artificial intelligence. At the same time, an evolution has been occurring in a fundamental component of radiology practice - the radiologist's report. Initially, the radiology report was a private written communication between the radiologist and the referring physician 1,2. Today, the report is an electronic document, displayed on web portals, and visible to both physicians and the patients themselves.3 A provision in the 21st Century Cures Act, signed into law on December 13, 2016, ensures that radiology reports in the electronic health record are visible to patients without delay 4. To meet modern patient expectations and legal requirements, the structure and purpose of the radiologist report is changing. This article will provide an overview of the history of radiology reporting and the law, discuss the role of the radiologist report within the context of patient and family centered care, review current strategies and investigations in patient-friendly reporting, and summarize radiology reporting challenges and opportunities for the future.

[Development and Validation of Dose Management Software in IVR Utilizing Radiation Information System].

PURPOSE: In each clinical case, the equipment display dose is used for interventional radiology (IVR) dose management and conform to the Japan diagnostic reference levels 2020 (DRLs 2020). However, dose management software corresponding to the DRLs 2020 using radiation dose structured report (RDSR) is not sufficiently widespread. This study aimed to assess the usefulness of in-house developed dose management software in IVR utilizing radiology information system (RIS), which can record both procedures and lesions. METHODS: In this study, IVR from July to September 2020 was analyzed (cardiac regions: 141 cases and other regions: 149 cases). The evaluation items were air kerma-area product, air kerma at the patient entrance reference point, and patient information (height, weight, and BMI). Each subject of DRLs 2020 was analyzed by 12 radiological technologists in charge of IVR. The difference between results of the manual analysis and those of the in-house developed dose management software was calculated using paired t-test in terms of analysis time. RESULTS: The analysis time for the cardiac and other regions was 4180.25±1161.79 s and 4366.92±1393.19 s in the manual analysis, and 36.25±15.32 s and 38.08±17.34 s in the software. The use of software indicated a significant reduction in analysis time (p<0.05). The analysis accuracy of the cardiac and other regions was 96.30% and 98.89% in the software. CONCLUSION: These results show the usefulness of dose management software utilizing RIS.

Prior Knowledge Enhances Radiology Report Generation.

Radiology report generation aims to produce computer-aided diagnoses to alleviate the workload of radiologists and has drawn increasing attention recently. However, previous deep learning methods tend to neglect the mutual influences between medical findings, which can be the bottleneck that limits the quality of generated reports. In this work, we propose to mine and represent the associations among medical findings in an informative knowledge graph and incorporate this prior knowledge with radiology report generation to help improve the quality of generated reports. Experiment results demonstrate the superior performance of our proposed method on the IU X-ray dataset with a ROUGE-L of 0.384±0.007 and CIDEr of 0.340±0.011. Compared with previous works, our model achieves an average of 1.6% improvement (2.0% and 1.5% improvements in CIDEr and ROUGE-L, respectively). The experiments suggest that prior knowledge can bring performance gains to accurate radiology report generation. We will make the code publicly available at https://github.com/bionlplab/report_generation_amia2022.

Impact of Follow-Up Imaging Recommendation Specificity on Adherence.

Radiology reports often contain follow-up imaging recommendations, but failure to comply with them in a timely manner can lead to delayed treatment, poor patient outcomes, complications, and legal liability. Using a dataset containing 2,972,164 exams for over 7 years, in this study we explored the association between recommendation specificity on follow-up rates. Our results suggest that explicitly mentioning the follow-up interval as part of a follow-up imaging recommendation has a significant impact on adherence making these recommendations 3 times more likely (95% CI: 2.95 - 3.05) to be followed-up, while explicit mentioning of the follow-up modality did not have a significant impact. Our findings can be incorporated into routine dictation macros so that the follow-up duration is explicitly mentioned whenever clinically applicable, and/or used as the basis for a quality improvement project focussed on improving adherence to follow-up imaging recommendations.

Evaluation of Current and Former Teleradiology Systems in Africa: A Review.

Background: Teleradiology has grown tremendously across the globe, providing significant benefits to both patients and physicians. In the late 1990s, South Africa sought to lead teleradiology adoption efforts by creating a national telemedicine system through a structured and phased approach. Although initial reports of the system's effectiveness were encouraging, the present status of this project, as well as comparable efforts in surrounding developing countries, has remained uncertain. Objective: To explore the status of teleradiology adoption in Africa, identify existing barriers to adoption, and explore potential solutions to the most commonly identified barriers. Methods: A narrative literature review was conducted to find articles that discussed current and past teleradiology systems in Africa. Each item was evaluated for relevance separately based on specified inclusion and exclusion criteria and was used to field further articles if relevant to the topic, even if not found in the initial search. The search began with articles published after January 1995 and included articles through December 2021. Findings: Although teleradiology systems in Africa has shown to have a benefit in improving patient outcomes, current implementation remains limited due to feasibility projects with no singular picture archiving and communication system (PACS) being utilized at the time of writing. Conclusions: Although teleradiology has significant potential and can benefit the developing countries in Africa, further expansion, in terms of both complexity and adoption rates, remains hindered by infrastructure development, clinician and technologist support, and general sociopolitical factors.

How to Optimize Connection Between PACS and Clinical Data Warehouse: A Web Service Approach Based on Full Metadata Integration.

Clinical image data analysis is an active area of research. Integrating such data in a Clinical Data Warehouse (CDW) implies to unlock the PACS and RIS and to address interoperability and semantics issues. Based on specific functional and technical requirements, our goal was to propose a web service (I4DW) that allows users to query and access pixel data from a CDW by fully integrating and indexing imaging metadata. Here, we present the technical implementation of this workflow as well as the evaluation we carried out using a prostate cancer cohort use case. The query mechanism relies on a Dicom metadata hierarchy dynamically generated during the ETL Process. We evaluated the Dicom data transfer performance of I4DW, and found mean retrieval times of 5.94 seconds and 0.9 seconds to retrieve a complete DICOM series from the PACS and all metadata of a series. We could retrieve all patients and imaging tests of the prostate cancer cohort with a precision of 0.95 and a recall of 1. By leveraging the CMOVE method, our approach based on the Dicom protocol is scalable and domain-neutral. Future improvement will focus on performance optimization and de identification.

Web-Based Application for Biomedical Image Registry, Analysis, and Translation (BiRAT).

Imaging has become an invaluable tool in preclinical research for its capability to non-invasively detect and monitor disease and assess treatment response. With the increased use of preclinical imaging, large volumes of image data are being generated requiring critical data management tools. Due to proprietary issues and continuous technology development, preclinical images, unlike DICOM-based images, are often stored in an unstructured data file in company-specific proprietary formats. This limits the available DICOM-based image management database to be effectively used for preclinical applications. A centralized image registry and management tool is essential for advances in preclinical imaging research. Specifically, such tools may have a high impact in generating large image datasets for the evolving artificial intelligence applications and performing retrospective analyses of previously acquired images. In this study, a web-based server application is developed to address some of these issues. The application is designed to reflect the actual experimentation workflow maintaining detailed records of both individual images and experimental data relevant to specific studies and/or projects. The application also includes a web-based 3D/4D image viewer to easily and quickly view and evaluate images. This paper briefly describes the initial implementation of the web-based application.

Images indexing and matched assessment of semantics and visuals similarities applied to a medical learning X-ray image base.

BACKGROUND: Medical diagnostic support systems are important tools in the field of radiology. However, the precision obtained, during the exploitation of high homogeneity image datasets, needs to be improved. OBJECTIVE: To develop a new learning system dedicated to public health practitioners. This study presents an upgraded version dedicated to radiology experts for better clinical decision-making when diagnosing and treating the patient (CAD approach). METHODS: Our system is a hybrid approach based on a matching of semantic and visual attributes of images. It is a combination of two complementary subsystems to form the intermodal system. The first one named α based on semantic attributes. Indexing and image retrieval based on specific keywords. The second system named ß based on low-level attributes. Vectors characterizing the digital content of the image (color, texture and shape) represent images. Our image database consists of 930 X-ray images including 320 mammograms acquired from the mini-MIAS database of mammograms and 610 X-rays acquired from the Public Hospital Establishment (EPH-Rouiba Algeria). The combination of two subsystems gives rise to the intermodal system: α-subsystem offers an overall result (based on visual descriptors), then ß-subsystem (low level descriptors) refines the result and increases relevance. RESULTS: Our system can perform a specific image search (in a database of images with very high homogeneity) with an accuracy of around 90% for a recall of 25%. The average (overall) accuracy of the system exceeds 70%. CONCLUSION: The results obtained are very encouraging, and demonstrate efficiency of our approach, particularly for the intermodal system.

Intra-Query Parallelism for a Scalable and Responsive Web-Based Digital Pathology Viewer.

Computational systems are successfully used in distinct areas of health. However, the use of digital imaging in pathology is taking its first steps when compared with the radiology sector. For instance, inter-institutional web platforms interoperable with various scanners through standard communications are very rare. This is due to the fact that the technology is only now being mature enough to meet the major challenges of this sector in terms of data storage and data access for efficient visualization of images with several gigabytes. The remote access to those images proves to be a challenge in an open and heterogeneous environment. This paper proposes a scalable and efficient architecture for storing and dynamic data retrieval on distributed large-scale systems. The adopted methodology relies on intra-query parallelism to retrieve a large number of image segments in a scalable distributed environment.