Medical Imaging Resource Center Research Articles

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons.

The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary MIDRC dataset compared to the United States general population (US Census) and COVID-19 positive case counts from the Centers for Disease Control and Prevention (CDC). The Jensen-Shannon distance (JSD), a measure of similarity of two distributions, was used to longitudinally measure the representativeness of the distribution of (1)all unique patients in the MIDRC data to the 2020 US Census and (2)all unique COVID-19 positive patients in the MIDRC data to the case counts reported by the CDC. The distributions were evaluated in the demographic categories of age at index, sex, race, ethnicity, and the combination of race and ethnicity. Representativeness of the MIDRC data by ethnicity and the combination of race and ethnicity was impacted by the percentage of CDC case counts for which this was not reported. The distributions by sex and race have retained their level of representativeness over time. The representativeness of the open medical imaging datasets in the curated public data commons at MIDRC has evolved over time as the number of contributing institutions and overall number of subjects have grown. The use of metrics, such as the JSD support measurement of representativeness, is one step needed for fair and generalizable AI algorithm development.

Lessons learned in transitioning to AI in the medical imaging of COVID-19.

.The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc across the world. It also created a need for the urgent development of efficacious predictive diagnostics, specifically, artificial intelligence (AI) methods applied to medical imaging. This has led to the convergence of experts from multiple disciplines to solve this global pandemic including clinicians, medical physicists, imaging scientists, computer scientists, and informatics experts to bring to bear the best of these fields for solving the challenges of the COVID-19 pandemic. However, such a convergence over a very brief period of time has had unintended consequences and created its own challenges. As part of Medical Imaging Data and Resource Center initiative, we discuss the lessons learned from career transitions across the three involved disciplines (radiology, medical imaging physics, and computer science) and draw recommendations based on these experiences by analyzing the challenges associated with each of the three associated transition types: (1) AI of non-imaging data to AI of medical imaging data, (2) medical imaging clinician to AI of medical imaging, and (3) AI of medical imaging to AI of COVID-19 imaging. The lessons learned from these career transitions and the diffusion of knowledge among them could be accomplished more effectively by recognizing their associated intricacies. These lessons learned in the transitioning to AI in the medical imaging of COVID-19 can inform and enhance future AI applications, making the whole of the transitions more than the sum of each discipline, for confronting an emergency like the COVID-19 pandemic or solving emerging problems in biomedicine.

Adaptation of an internet‐based DICOM viewer for use with the Medical Imaging Resource Center – Teaching File System (MIRC‐TFS)

DICOM is the standard file format for medical imaging; however, storage, transmission and viewing of these images over the internet for teaching and learning purposes outside of the clinical setting presents a challenge as they do not lend themselves well to rapid display and interrogation due to their atypical file format. The aim of this project was to utilize the web technology standard HTML 5 offers to deploy a DICOM viewer that functions well, directly in the user's browser, without the need for complex client side‐applications, application switching, or user login requirements. To achieve this we have adapted the open source HTML 5 DICOM viewer, Oviyam, for integration with the Radiological Society of North America's Medical Imaging Resource Center – Teaching File System (MIRC‐TFS) on a virtual server to facilitate access to DICOM objects for teaching and learning. For learners a plugin was developed to transform the DICOM images in MIRC‐TFS into JPEG format resulting in a reduction in file size allowing users to view the images more rapidly while supporting higher user traffic for viewing images concurrently, as frequently occurs with large class sizes. In addition, a second plugin was developed for BlackBoard Learn that allows instructors to browse the MIRC‐TFS teaching cases and insert them alongside their other course materials. The tool set and image viewing capabilities of Oviyam were enhanced to include annotation tools allowing students to create marked up versions of the images for evaluation of their knowledge. The deployment of this solution has significantly facilitated the interaction of teachers and learners with DICOM based images for use in their academic environment.

University of Saskatchewan Radiology Courseware (USRC): An Assessment of Its Utility for Teaching Diagnostic Imaging in the Medical School Curriculum

Problem: We have found it very challenging to integrate images from our radiology digital imaging repository into the curriculum of our local medical school. Thus, it has been difficult to convey important knowledge related to viewing and interpreting diagnostic radiology images. We sought to determine if we could create a solution for this problem and evaluate whether students exposed to this solution were able to learn imaging concepts pertinent to medical practice. Intervention: We developed University of Saskatchewan Radiology Courseware (USRC), a novel interactive web application that enables preclinical medical students to acquire image interpretation skills fundamental to clinical practice. This web application reformats content stored in Medical Imaging Resource Center teaching cases for BlackBoard Learn™, a popular learning management system. We have deployed this solution for 2 successive years in a 1st-year basic sciences medical school course at the College of Medicine, University of Saskatchewan. The “courseware” content covers both normal anatomy and common clinical pathologies in five distinct modules. We created two cohorts of learners consisting of an intervention cohort of students who had used USRC for their 1st academic year, whereas the nonintervention cohort was students who had not been exposed to this learning opportunity. Context: To assess the learning experience of the users we designed an online questionnaire and image review quiz delivered to both of the student groups. Outcome: Comparisons between the groups revealed statistically significant differences in both confidence with image interpretation and the ability to answer knowledge-based questions. Students were satisfied with the overall usability, functions, and capabilities of USRC. Lessons Learned: USRC is an innovative technology that provides integration between Medical Imaging Resource Center, a teaching solution used in radiology, and a Learning Management System.

Assessment of feasibility of running RSNA's MIRC on a Raspberry Pi: a cost-effective solution for teaching files in radiology.

The value of a teaching case repository in radiology training programs is immense. The allocation of resources for putting one together is a complex issue, given the factors that have to be coordinated: hardware, software, infrastructure, administration, and ethics. Costs may be significant and cost-effective solutions are desirable. We chose Medical Imaging Resource Center (MIRC) to build our teaching file. It is offered by RSNA for free. For the hardware, we chose the Raspberry Pi, developed by the Raspberry Foundation: a small control board developed as a low cost computer for schools also used in alternative projects such as robotics and environmental data collection. Its performance and reliability as a file server were unknown to us. For the operational system, we chose Raspbian, a variant of Debian Linux, along with Apache (web server), MySql (database server) and PHP, which enhance the functionality of the server. A USB hub and an external hard drive completed the setup. Installation of software was smooth. The Raspberry Pi was able to handle very well the task of hosting the teaching file repository for our division. Uptime was logged at 100 %, and loading times were similar to other MIRC sites available online. We setup two servers (one for backup), each costing just below $200.00 including external storage and USB hub. It is feasible to run RSNA's MIRC off a low-cost control board (Raspberry Pi). Performance and reliability are comparable to full-size servers for the intended purpose of hosting a teaching file within an intranet environment.

Application of medical imaging resource center software in imaging teaching practice

Base on the development of picture archiving and communication system (PACS) of teaching hospital and imaging database,medical imaging resource center (MIRC) software of Siemens was used in medical imaging teaching.It is beneficial to increasing the effectiveness of teaching system,stimulating enthusiasm of students,reforming the traditional exam model and improving the standard of teaching. Key words: Picture archiving and communication system; Medical imaging

USRC: A New Strategy for Adding Digital Images to the Medical School Curriculum

Many medical schools use learning management systems (LMSs) to give students access to online lecture notes, assignments, quizzes, and other learning resources. LMSs can also be used to provide access to digital radiology images, potentially improving preclinical teaching in anatomy, physiology, and pathology while also allowing students to develop interpretation skills that are important in clinical practice. However, it is unclear how radiology images can best be stored, imported, and displayed in an LMS. We developed University of Saskatchewan Radiology Courseware (USRC), a new web application that allows course designers to import images into pages linked to BlackBoard Learn, a popular LMS. Page content, including images, annotations, captions, and supporting text, are stored as teaching cases on a MIRC (Medical Imaging Resource Center) server. Course designers create cases in MIRC, and then create a corresponding page in BlackBoard by modifying an HTML template so that it holds the URL of a MIRC case. When a user visits the page in BlackBoard, the page requests content from the MIRC case, reformats the text for display in BlackBoard, and loads an image viewer plug-in that allows students to view and interact with the images stored in the case. The USRC technology can be used to reformat MIRC cases for presentation in any website or in any learning management system that supports custom pages written in HTML with embedded JavaScript.

Structured reporting using a shared indexed multilingual radiology lexicon

A system for creating structured reports (SRs) using a standardized radiology lexicon was developed and tested to facilitate automated translation of content and multidisciplinary international communications. A database of radiology terms, RadLex developed by the Radiological Society of North America, was used to create a shared indexed multilingual radiology lexicon. A diagnostic workstation for generating structured reports (OpenEye) was implemented with a "RadLex manager" function for adding new words to the lexicon in both English and Italian. Sample reports of examinations included in the Medical Imaging Resource Center (MIRC) radiology imaging database of clinical cases were prepared using this system. The system was evaluated for teaching purposes and scientific dissemination. The OpenEye system was able to manage the glossary to create new SRs and manually translate existing reports containing freely worded descriptions. The OpenEye system provides instant translation from Italian into English and enables clinical cases to be published in the MIRC, while making them accessible for consultation on an international scale. The SR is advantageous compared with a freely worded report in terms of clarity and completeness of the content. Creating SRs for each clinical case enables rapid and focused analysis at multidisciplinary meetings. All our cases have been included in the MIRC database as part of a broader-based European Project for research on soft tissues sarcomas (CONTICANET).

Developing a Radiology-Based Teaching Approach for Gross Anatomy in the Digital Era

The purpose of this study was to assess the implementation of a digital anatomy lecture series based largely on annotated, radiographic images and the utility of the Radiological Society of North America-developed Medical Imaging Resource Center (MIRC) for providing an online educational resource. A series of digital teaching images were collected and organized to correspond to lecture and dissection topics. MIRC was used to provide the images in a Web-based educational format for incorporation into anatomy lectures and as a review resource. A survey assessed the impressions of the medical students regarding this educational format. MIRC teaching files were successfully used in our teaching approach. The lectures were interactive with questions to and from the medical student audience regarding the labeled images used in the presentation. Eighty-five of 120 students completed the survey. The majority of students (87%) indicated that the MIRC teaching files were "somewhat useful" to "very useful" when incorporated into the lecture. The students who used the MIRC files were most likely to access the material from home (82%) on an occasional basis (76%). With regard to areas for improvement, 63% of the students reported that they would have benefited from more teaching files, and only 9% of the students indicated that the online files were not user friendly. The combination of electronic radiology resources available in lecture format and on the Internet can provide multiple opportunities for medical students to learn and revisit first-year anatomy. MIRC provides a user-friendly format for presenting radiology education files for medical students.

Integration of the Medical Imaging Resource Center into a Teaching Hospital Network to Allow Single Sign-on Access

The RSNA Medical Imaging Resource Center (MIRC) software is an open-source program that allows users to identify, index, and retrieve images, teaching files, and other radiologic data that share a common underlying structure. The software is being continually improved as new challenges and different needs become apparent. Although version T30 is easily installed on a stand-alone computer, its implementation at healthcare enterprises with complex network architecture may be challenging with respect to security because users cannot log on by using a standard enterprise-wide authentication protocol. Instead, authentication takes place through the local MIRC database, creating security concerns and potential organizational problems. In this setting, the Lightweight Directory Access Protocol (LDAP) can be used to provide a single sign-on environment and increase authentication security. A commercial directory service using LDAP has been successfully integrated with MIRC in a large multifacility enterprise to provide single sign-on capability compatible with the institutional networking policies for password security.

Use of the MIRC DICOM Service for Clinical Trials to Automatically Create Teaching File Cases from PACS

The Medical Imaging Resource Center (MIRC) software of the Radiological Society of North America is used to share teaching files and clinical trial data. By using the MIRC service for clinical trials, teaching file cases can be automatically generated directly from picture archiving and communication systems (PACS). The advantage of using the clinical trials service over the authoring service is the need for minimal user intervention, because data already present in the Digital Imaging and Communications in Medicine (DICOM) header can be automatically inserted into teaching file cases. When reading a case on the PACS workstation, the radiologist needs only to select the images for the teaching file case, write the diagnosis in the "Study Comments" box (usually used for "wet" readings), and send the case to the MIRC server directly from the workstation. The MIRC server automatically makes the images anonymous and fills in the modified teaching file template by using the data in the DICOM header (patient age, patient sex, clinical history, diagnosis, imaging modality, organ system), thus creating a simple teaching file. If desired, the teaching file case can be edited at a later time. By making minor modifications to the MIRC DICOM clinical trials service, it is possible to create teaching file cases with minimal effort. Supplemental material available at radiographics.rsnajnls.org/cgi/content/full/27/1/269/DC1.

Medical Imaging Resource Center (MIRC)

Das Medical Imaging Resource Center (MIRC) wurde von der Radiological Society of North America (RSNA) initiiert, die das Projekt auch finanziert. 2001 wurde das Projekt, was letztlich ein „Google für radiologische (Bild-) Daten“ darstellt, erstmals der Öffentlichkeit präsentiert. Seitdem erfolgte eine kontinuierliche Weiterentwicklung.

Medical Imaging Resource Center (MIRC) for Veterinary Medicine: A Digital Image Teaching File

Veterinary radiology has a need for software to facilitate the creation of digital image teaching files. The Medical Imaging Resource Center (MIRC) is widely used in medicine to create teaching cases and store data from clinical trials. This open-source software was identified as a solution for use in veterinary medicine. The additional fields needed to adapt the system for veterinary use were identified as sex, species, and breed. Breed and species codes from the Matthew J. Ryan Veterinary Hospital of the University of Pennsylvania and from the Standard Nomenclature of Veterinary Diseases and Operations (SNVDO) were gathered and correlated. The sex fields added were male, male neutered, female, and female neutered. The breed and species codes were combined into a single term. These were coded in eXtensible Markup Language (XML) and added to the software's veterinary document template and search capabilities. MIRC was successfully adapted for use in creating digital teaching files for veterinary medicine.

Electronic teaching files and continuing professional development in radiology

Education in diagnostic radiology employs medical images extensively, and case-based teaching files of actual patients are useful to illustrate pertinent teaching points. In the era of digital radiology, there is great potential to use the ready source of patient material from Picture Archive and Communication Systems (PACS) and initiatives such as Medical Imaging Resource Center (MIRC) on the World Wide Web for teaching and for Continuing Professional Development (CPD). As mandatory CPD becomes the reality in medical practice, computerised solutions that support the creation of electronic teaching files in the midst of busy clinical workflow would be very valuable. This paper will explore the features of image-based CPD, the various ways in which medical images can be used for self directed learning and the challenges that face the radiology profession.

Multimedia Extension of Medical Imaging Resource Center Teaching Files

A new method has been developed for multimedia enhancement of electronic teaching files created by using the standard protocols and formats offered by the Medical Imaging Resource Center (MIRC) project of the Radiological Society of North America. The typical MIRC electronic teaching file consists of static pages only; with the new method, audio and visual content may be added to the MIRC electronic teaching file so that the entire image interpretation process can be recorded for teaching purposes. With an efficient system for encoding the audiovisual record of on-screen manipulation of radiologic images, the multimedia teaching files generated are small enough to be transmitted via the Internet with acceptable resolution. Students may respond with the addition of new audio and visual content and thereby participate in a discussion about a particular case. MIRC electronic teaching files with multimedia enhancement have the potential to augment the effectiveness of diagnostic radiology teaching.

Conversion of a plain film teaching file to a digital database

In many academic institutions, there currently exist a large number of plain film teaching files. Unfortunately, plain film storage limits access. Therefore, a method for converting a plain film teaching file into a digital database, which can be easily searched by both database field and free text, would be of great value. These images and the accompanying text can then be used to rapidly generate presentations/lectures, to provide a tool for independent learning, or to rapidly access publication quality, pathology proven, images for use in papers and textbooks. The following article outlines a method for converting a plain film into a teaching file to a digital database utilizing the Radiological Society of North America Medical Imaging Resource Center (MIRC) program.

A Novel Application of the MIRC Repository in Medical Education

Medical students on the radiology elective in our institution create electronic presentations to present to each other as part of the requirements for the rotation. Access was given to previous students' presentations via the web-based system, Medical Imaging Resource Center (MIRC) project, created and supported by the Radiological Society of North America (RSNA). RadPix Power 2 MIRC (Weadock Software, LLC, Ann Arbor, MI) software converted the Microsoft PowerPoint (Redmond, WA) presentations to a MIRC-compatible format. The textual information on each slide is searchable across the entire MIRC database. Future students will be able to benefit from the work of their predecessors.

Casimage project: a digital teaching files authoring environment.

The goal of the Casimage project is to offer an authoring and editing environment integrated with the Picture Archiving and Communication Systems (PACS) for creating image-based electronic teaching files. This software is based on a client/server architecture allowing remote access of users to a central database. This authoring environment allows radiologists to create reference databases and collection of digital images for teaching and research directly from clinical cases being reviewed on PACS diagnostic workstations. The environment includes all tools to create teaching files, including textual description, annotations, and image manipulation. The software also allows users to generate stand-alone CD-ROMs and web-based teaching files to easily share their collections. The system includes a web server compatible with the Medical Imaging Resource Center standard (MIRC, http://mirc.rsna.org) to easily integrate collections in the RSNA web network dedicated to teaching files. This software could be installed on any PACS workstation to allow users to add new cases at any time and anywhere during clinical operations. Several images collections were created with this tool, including thoracic imaging that was subsequently made available on a CD-Rom and on our web site and through the MIRC network for public access.

Implementing a MIRC query interface for a database driven teaching file.

This paper describes the authors' experience with integrating an existing database-driven teaching file with the RSNA (Radiological Society of North America) Medical Imaging Resource Center (MIRC). MIRC is the product of an RSNA-sponsored initiative to enable medical institutions to share their electronic medical content (images, text, and multimedia) by creating a distributed repository accessible from the Internet. An existing database-driven teaching file, developed by the authors and used extensively by the University of California San Francisco (UCSF) Department of Radiology since 1998, was retrofitted to include an interface for handling broadcast queries initiated by a MIRC query service. These queries take place through the exchange of XML documents via HTTP. After all the storage services have responded, the results are collated by the query service and presented to the user. The teaching file and MIRC interface were developed using the 4th Dimension Relational Database Management System (RDBMS). The integration process primarily involved mapping the "MIRCdocument" schema to the teaching file's schema, translating the actual MIRC query into the internal query language of the database and extending the access control mechanisms of the teaching file to allow public access. A working implementation of the interface required only 3 days of development time, with refinements taking place over several months. Interface development was greatly aided by MIRC's use of well-established Internet standards. This project has demonstrated the feasibility of implementing a MIRC interface on an existing teaching file server.