Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipline-specific communication patterns often impairs shared understanding and the shared use of common medical terminology. Common terms are currently used in medicine to ensure interoperability and facilitate integration of biomedical information for clinical practice and emerging scientific and educational applications alike, from database integration to supporting basic clinical operations such as billing. Such common terminologies can be provided in ontologies, which are formalized representations of knowledge in a particular domain. Ontologies unambiguously specify common concepts and describe the relationships between those concepts by using a form that is mathematically precise and accessible to humans and machines alike. RadLex® is a key RSNA initiative that provides a shared domain model, or ontology, of radiology to facilitate integration of information in radiology education, clinical care, and research. As the contributions of the computational components of common radiologic workflows continue to increase with the ongoing development of big data, artificial intelligence, and novel image analysis and visualization tools, the use of common terminologies is becoming increasingly important for supporting seamless computational resource integration across medicine. This article introduces ontologies, outlines the fundamental semantic web technologies used to create and apply RadLex, and presents examples of RadLex applications in everyday radiology and research. It concludes with a discussion of emerging applications of RadLex, including artificial intelligence applications. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Imaging Informatics Fellowship Curriculum: Building Consensus on the Most Critical Topics and the Future of the Informatics Fellowship.

The existing fellowship imaging informatics curriculum, established in 2004, has not undergone formal revision since its inception and inaccurately reflects present-day radiology infrastructure. It insufficiently equips trainees for today's informatics challenges as current practices require an understanding of advanced informatics processes and more complex system integration. We sought to address this issue by surveying imaging informatics fellowship program directors across the country to determine the components and cutline for essential topics in a standardized imaging informatics curriculum, the consensus on essential versus supplementary knowledge, and the factors individual programs may use to determine if a newly developed topic is an essential topic. We further identified typical program structural elements and sought fellowship director consensus on offering official graduate trainee certification to imaging informatics fellows. Here, we aim to provide an imaging informatics fellowship director consensus on topics considered essential while still providing a framework for informatics fellowship programs to customize their individual curricula.

Machine vs. Radiologist-Based Translations of RadLex: Implications for Multi-language Report Interoperability.

The purpose of this study was to evaluate the feasibility of translation of RadLex lexicon from English to German performed by Google Translate, using the RadLex ontology as ground truth. The same comparison was also performed for German to English translations. We determined the concordance rate of the Google Translate-rendered translations (for both English to German and German to English translations) to the official German RadLex (translations provided by the German Radiological Society) and English RadLex terms via character-by-character concordance analysis (string matching). Specific term characteristics of term character count and word count were compared between concordant and discordant translations using t-tests. Google Translate-rendered translations originally considered incongruent (2482 English terms and 2500 German terms) were then reviewed by German and English-speaking radiologists to further evaluate clinical utility. Overall success rates of both methods were calculated by adding the percentage of terms marked correct by string comparison to the percentage marked correct during manual review extrapolated to the terms that had been initially marked incorrect during string analysis. 64,632 English and 47,425 German RadLex terms were analyzed. 3507 (5.4%) of the Google Translate-rendered English to German translations were concordant with the official German RadLex terms when evaluated via character-by-character concordance. 3288 (6.9%) of the Google Translate-rendered German to English translations matched the corresponding English RadLex terms. Human review of a random sample of non-concordant machine translations revealed that 95.5% of such English to German translations were understandable, whereas 43.9% of such German to English translations were understandable. Combining both string matching and human review resulted in an overall Google Translate success rate of 95.7% for English to German translations and 47.8% for German to English translations. For certain radiologic text translation tasks, Google Translate may be a useful tool for translating multi-language radiology reports into a common language for natural language processing and subsequent labeling of datasets for machine learning. Indeed, string matching analysis alone is an incomplete method for evaluating machine translation. However, when human review of automated translation is also incorporated, measured performance improves. Additional evaluation using longer text samples and full imaging reports is needed. An apparent discordance between English to German versus German to English translation suggests that the direction of translation affects accuracy.

Glenoid bony morphology of osteoarthritis prior to shoulder arthroplasty: what the surgeon wants to know and why.

Shoulder arthroplasty is performed with increasing frequency, and osteoarthritis is the most common indication for this procedure. However, the glenoid side of the joint is widely recognized as a limiting factor in the long-term durability of shoulder replacement, and osteoarthritis leads to characteristic bony changes at the glenoid which can exacerbate this challenge by reducing the already limited glenoid bone stock, by altering biomechanics, and by interfering with operative exposure. This article reviews the Walch classification system for glenoid morphology. Several typical findings of osteoarthritis at the glenoid are discussed including central bone loss, posterior bone loss, retroversion, biconcavity, inclination, osteophyte formation, subchondral bone quality, and bone density. The three primary types of shoulder arthroplasty are reviewed, along with several techniques for addressing glenoid deformity, including eccentric reaming, bone grafting, and the use of augmented glenoid components. Ultimately, a primary objective at shoulder arthroplasty is to correct glenoid deformity while preserving bone stock, which depends critically on characterizing the glenoid at pre-operative imaging. Understanding the surgical techniques and the implications of glenoid morphology on surgical decision-making enables the radiologist to provide the morphologic information needed by the surgeon.

CT-Based 3D Printing of the Glenoid Prior to Shoulder Arthroplasty: Bony Morphology and Model Evaluation.

To demonstrate the 3D printed appearance of glenoid morphologies relevant to shoulder replacement surgery and to evaluate the benefits of printed models of the glenoid with regard to surgical planning. A retrospective review of patients referred for shoulder CT was performed, leading to a cohort of nine patients without arthroplasty hardware and exhibiting glenoid changes relevant to shoulder arthroplasty planning. Thin slice CT images were used to create both humerus-subtracted volume renderings of the glenoid, as well as 3D surface models of the glenoid, and 11 printed models were created. Volume renderings, surface models, and printed models were reviewed by a musculoskeletal radiologist for accuracy. Four fellowship-trained orthopaedic surgeons specializing in shoulder surgery reviewed each case individually as follows: First, the source CT images were reviewed, and a score for the clarity of the bony morphologies relevant to shoulder arthroplasty surgery was given. The volume rendering was reviewed, and the clarity was again scored. Finally, the printed model was reviewed, and the clarity again scored. Each printed model was also scored for morphologic complexity, expected usefulness of the printed model, and physical properties of the model. Mann-Whitney-Wilcoxon signed rank tests of the clarity scores were calculated, and the Spearman's ρ correlation coefficient between complexity and usefulness scores was computed. Printed models demonstrated a range of glenoid bony changes including osteophytes, glenoid bone loss, retroversion, and biconcavity. Surgeons rated the glenoid morphology as more clear after review of humerus-subtracted volume rendering, compared with review of the source CT images (p = 0.00903). Clarity was also better with 3D printed models compared to CT (p = 0.00903) and better with 3D printed models compared to humerus-subtracted volume rendering (p = 0. 00879). The expected usefulness of printed models demonstrated a positive correlation with morphologic complexity, with Spearman's ρ 0.73 (p = 0.0108). 3D printing of the glenoid based on pre-operative CT provides a physical representation of patient anatomy. Printed models enabled shoulder surgeons to appreciate glenoid bony morphology more clearly compared to review of CT images or humerus-subtracted volume renderings. These models were more useful as glenoid complexity increased.

Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging.

Standard clinical terms, codes, and ontologies promote clarity and interoperability. Within radiology, there is a variety of relevant content resources, tools and technologies. These provide the basis for fundamental imaging workflows such as reporting and billing, and also facilitate a range of applications in quality improvement and research. This article reviews the key characteristics of lexicons, coding systems, and ontologies. A number of standards are described, including International Classification of Diseases-10-Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and RadLex. Tools for accessing this material are reviewed, such as the National Center for Biomedical Ontology BioPortal system. Web services are discussed as a mechanism for semantic application development. Several example systems, workflows, and research applications using semantic technology are also surveyed.

Single-Center Experience Implementing the LOINC-RSNA Radiology Playbook for Adult Abdomen/Pelvis CT and MR Procedures Using a Semi-Automated Method.

The LOINC-RSNA Radiology Playbook represents the future direction of standardization for radiology procedure names. We developed a software solution ("RadMatch") utilizing Python 2.7 and FuzzyWuzzy, an open-source fuzzy string matching algorithm created by SeatGeek, to implement the LOINC-RSNA Radiology Playbook for adult abdomen and pelvis CT and MR procedures performed at our institution. Execution of this semi-automated method resulted in the assignment of appropriate LOINC numbers to 86% of local CT procedures. For local MR procedures, appropriate LOINC numbers were assigned to 75% of these procedures whereas 12.5% of local MR procedures could only be partially mapped. For the standardized local procedures, only 63% of CT and 71% of MR procedures had corresponding RadLex Playbook identifier (RPID) codes in the LOINC-RSNA Radiology Playbook, which limited the utility of RPID codes. RadMatch is a semi-automated open-source software tool that can assist radiology departments seeking to standardize their radiology procedures via implementation of the LOINC-RSNA Radiology Playbook.

Use of Radiology Procedure Codes in Health Care: The Need for Standardization and Structure.

Radiology procedure codes are a fundamental part of most radiology workflows, such as ordering, scheduling, billing, and image interpretation. Nonstandardized unstructured procedure codes have typically been used in radiology departments. Such codes may be sufficient for specific purposes, but they offer limited support for interoperability. As radiology workflows and the various forms of clinical data exchange have become more sophisticated, the need for more advanced interoperability with use of standardized structured codes has increased. For example, structured codes facilitate the automated identification of relevant prior imaging studies and the collection of data for radiation dose tracking. The authors review the role of imaging procedure codes in radiology departments and across the health care enterprise. Standards for radiology procedure coding are described, and the mechanisms of structured coding systems are reviewed. In particular, the structure of the RadLex™ Playbook coding system and examples of the use of this system are described. Harmonization of the RadLex Playbook system with the Logical Observation Identifiers Names and Codes standard, which is currently in progress, also is described. The benefits and challenges of adopting standardized codes-especially the difficulties in mapping local codes to standardized codes-are reviewed. Tools and strategies for mitigating these challenges, including the use of billing codes as an intermediate step in mapping, also are reviewed. In addition, the authors describe how to use the RadLex Playbook Web service application programming interface for partial automation of code mapping. © RSNA, 2017.

Ontology-based image navigation: exploring 3.0-T MR neurography of the brachial plexus using AIM and RadLex.

Disorders of the peripheral nervous system have traditionally been evaluated using clinical history, physical examination, and electrodiagnostic testing. In selected cases, imaging modalities such as magnetic resonance (MR) neurography may help further localize or characterize abnormalities associated with peripheral neuropathies, and the clinical importance of such techniques is increasing. However, MR image interpretation with respect to peripheral nerve anatomy and disease often presents a diagnostic challenge because the relevant knowledge base remains relatively specialized. Using the radiology knowledge resource RadLex®, a series of RadLex queries, the Annotation and Image Markup standard for image annotation, and a Web services-based software architecture, the authors developed an application that allows ontology-assisted image navigation. The application provides an image browsing interface, allowing users to visually inspect the imaging appearance of anatomic structures. By interacting directly with the images, users can access additional structure-related information that is derived from RadLex (eg, muscle innervation, muscle attachment sites). These data also serve as conceptual links to navigate from one portion of the imaging atlas to another. With 3.0-T MR neurography of the brachial plexus as the initial area of interest, the resulting application provides support to radiologists in the image interpretation process by allowing efficient exploration of the MR imaging appearance of relevant nerve segments, muscles, bone structures, vascular landmarks, anatomic spaces, and entrapment sites, and the investigation of neuromuscular relationships.

We Built This House; It's Time to Move in: Leveraging Existing DICOM Structure to More Completely Utilize Readily Available Detailed Contrast Administration Information.

The Digital Imaging and Communications in Medicine (DICOM) standard is the universal format for interoperability in medical imaging. In addition to imaging data, DICOM has evolved to support a wide range of imaging metadata including contrast administration data that is readily available from many modern contrast injectors. Contrast agent, route of administration, start and stop time, volume, flow rate, and duration can be recorded using DICOM attributes [1]. While this information is sparsely and inconsistently recorded in routine clinical practice, it could potentially be of significant diagnostic value. This work will describe parameters recorded by automatic contrast injectors, summarize the DICOM mechanisms available for tracking contrast injection data, and discuss the role of such data in clinical radiology.

Accuracy of MRI in diagnosing peripheral nerve disease: a systematic review of the literature.

OBJECTIVE: MRI is increasingly being used to evaluate extracranial peripheral nerve disease in clinical practice. The objective of this study was to systematically review the accuracy of MRI in distinguishing normal from abnormal extracranial peripheral nerves. CONCLUSION: There is significant heterogeneity between studies investigating the accuracy of MRI. Studies have shown that nerve T2-weighted or STIR hyperintensity, nerve enlargement, and nerve flattening are associated with peripheral nerve disease.

Demographics, utilization, workflow and outcomes based on observational data from the RSNA-ACR 3D Printing Registry.

OBJECTIVE: To report data from the first three years of operation of the RSNA-ACR 3D Printing Registry. METHODS: Data from June 2020 to June 2023 was extracted, including demographics, indications, workflow and user assessments. Clinical indications were stratified by 12 organ systems. Imaging modalities, printing technologies and number of parts per case were assessed. Effort data was analyzed, dividing staff into provider and non-provider categories. The opinions of clinical users were evaluated through a Likert-scale questionnaire, and estimates of procedure time saved were collected. RESULTS: A total of 20 sites and 2,637 cases were included, consisting of 1,863 anatomic models and 774 anatomic guides. Mean patient age for models and guides was 42.4 ± 24.5 years and 56.3 ± 18.5 years respectively. Cardiac models were the most common type of models (27.2%), and neurologic guides were the most common type of guides (42.4%). Material jetting, vat photopolymerization and material extrusion were the most common printing technologies used overall (85.6% of all cases). On average, providers spent 92.4 minutes and non-providers spent 335.0 minutes per case. Providers spent most time on consultation (33.6 minutes), while non-providers focused most on segmentation (148.0 minutes). Confidence in treatment plans increased after using 3D printing (p<.001). Estimated procedure time savings for 155 cases was 40.5 ± 26.1 minutes. CONCLUSION: 3D printing is performed in healthcare facilities for many clinical indications. The registry provides insight into the technologies and workflows used to create anatomic models and guides, and the data shows clinical benefits from 3D printing.

Utility and Costs During the Initial Year of 3D Printing in an Academic Hospital.

OBJECTIVE: There is a paucity of utility and cost data regarding the launch of 3D printing in a hospital. The objective of this project is to benchmark utility and costs for radiology-based in-hospital 3D printing of anatomic models in a single, adult academic hospital. METHODS: All consecutive patients for whom 3D printed anatomic models were requested during the first year of operation were included. All 3D printing activities were documented by the 3D printing faculty and referring specialists. For patients who underwent a procedure informed by 3D printing, clinical utility was determined by the specialist who requested the model. A new metric for utility termed Anatomic Model Utility Points with range 0 (lowest utility) to 500 (highest utility) was derived from the specialist answers to Likert statements. Costs expressed in United States dollars were tallied from all 3D printing human resources and overhead. Total costs, focused costs, and outsourced costs were estimated. The specialist estimated the procedure room time saved from the 3D printed model. The time saved was converted to dollars using hospital procedure room costs. RESULTS: The 78 patients referred for 3D printed anatomic models included 11 clinical indications. For the 68 patients who had a procedure, the anatomic model utility points had an overall mean (SD) of 312 (57) per patient (range, 200-450 points). The total operation cost was $213,450. The total cost, focused costs, and outsourced costs were $2,737, $2,180, and $2,467 per model, respectively. Estimated procedure time saved had a mean (SD) of 29.9 (12.1) min (range, 0-60 min). The hospital procedure room cost per minute was $97 (theoretical $2,900 per patient saved with model). DISCUSSION: Utility and cost benchmarks for anatomic models 3D printed in a hospital can inform health care budgets. Realizing pecuniary benefit from the procedure time saved requires future research.

High resolution imaging of tunnels by magnetic resonance neurography.

Peripheral nerves often traverse confined fibro-osseous and fibro-muscular tunnels in the extremities, where they are particularly vulnerable to entrapment and compressive neuropathy. This gives rise to various tunnel syndromes, characterized by distinct patterns of muscular weakness and sensory deficits. This article focuses on several upper and lower extremity tunnels, in which direct visualization of the normal and abnormal nerve in question is possible with high resolution 3T MR neurography (MRN). MRN can also serve as a useful adjunct to clinical and electrophysiologic exams by discriminating adhesive lesions (perineural scar) from compressive lesions (such as tumor, ganglion, hypertrophic callous, or anomalous muscles) responsible for symptoms, thereby guiding appropriate treatment.

The application of three-dimensional diffusion-weighted PSIF technique in peripheral nerve imaging of the distal extremities.

PURPOSE: To evaluate whether the addition of the three-dimensional diffusion-weighted reversed fast imaging with steady state free precession (3D DW-PSIF) sequence improves the identification of peripheral nerves in the distal extremities. MATERIALS AND METHODS: Twelve MR neurography (MRN) studies of the distal upper extremity and 12 MRN studies of distal lower extremity were evaluated. From the 24 subjects who were enrolled, 10 had clinically suspected peripheral neuropathy, whereas 14 suffered from various orthopedic diseases and had no clinical signs of neuropathy. In each examination, the ability to identify each peripheral nerve on T2-weighted and 3D DW-PSIF sequences was evaluated using a semi-quantitative (0-2) scale. Thereafter, a total certainty score was registered for each sequence. RESULTS: Combining the results of all studies, the mean certainty score was 1.92 ± 0.28 on the 3D DW-PSIF images and 1.50 ± 0.72 on the T2-weighted images (P < 0.001). In the upper extremity studies, the corresponding certainty scores were 2.0 and 1.70 ± 0.55, respectively (P = 0.008), and in the lower extremity studies, 1.86 ± 0.35 and 1.36 ± 0.79, respectively (P < 0.001). CONCLUSION: The 3D DW-PSIF images provide improved identification of the nerves compared with the T2-weighted images, and should be incorporated in the MRN protocol, whenever accurate nerve localization and/or presurgical evaluation are required.

MR neurography findings of soleal sling entrapment.

OBJECTIVE: The ever-increasing use of higher field strength (3 T) scanners and novel pulse sequences with improved spatial resolution and signal-to-noise ratio have rendered MR neurography (MRN) a valuable technique in the assessment of peripheral neuropathies. The aim of this study is to illustrate the imaging findings of high-resolution MRN in patients who suffer from tibial nerve entrapment due to a soleal fibromuscular sling and to correlate the imaging findings with intraoperative and clinical examination results. CONCLUSION: This article depicts the surgically confirmed imaging findings of high-resolution MRN in tibial nerve entrapment by the soleal sling.

High-resolution MR neurography: evaluation before repeat tarsal tunnel surgery.

OBJECTIVE: The purpose of this study was to retrospectively determine the accuracy of high-resolution MR neurography (MRN) in presurgical evaluation before repeat tarsal tunnel surgery. MATERIALS AND METHODS: Ten MRN studies of nine patients (one man, eight women; mean age, 44.4 years; range, 23-67 years) who had been referred to a peripheral nerve specialist because of persistent symptoms after tarsal tunnel release were reviewed. The MRN findings studied included presence and location of focal fibrosis, presence or absence of nerve abnormality, location of nerve abnormality, and presence of neuroma formation and regional muscle denervation. The diagnostic accuracy of MRN in detection of posterior tibial nerve, medial plantar nerve, and lateral plantar nerve injury was calculated with clinical and intraoperative findings as the reference standards. RESULTS: Nine of 10 MRN studies (90%) had findings of nerve reentrapment related to focal fibrosis. Injured nerves were reliably visualized with MRN in all patients. MRN had a sensitivity of 77% for posterior tibial nerve, 100% for medial plantar nerve, and 100% for lateral plantar nerve injury, and the overall accuracy was 86%. The sensitivity of MRN was 91% for the presence of focal fibrosis affecting the three nerves and 67% for neuroma detection. Regional muscle denervation was better evaluated on MRN studies than at surgery. Smaller (1-3 mm) abnormal cutaneous nerve branches were better seen at surgery. CONCLUSION: MRN yields accurate morphologic information about the location and extent of nerve injury after failed tarsal tunnel release and facilitates preoperative diagnosis.

MR neurography: past, present, and future.

OBJECTIVE: MR neurography (MRN) has increasingly been used in clinical practice for the evaluation of peripheral nerve disease. This article reviews the historic perspective of MRN, the current imaging trends of this modality, and the future directions and applications that have shown potential for improved imaging and diagnostic capabilities. CONCLUSION: MRN has come a long way in the past 2 decades. Excellent depiction of 3D nerve anatomy and pathology is currently possible. Further technical developments in diffusion-based nerve and muscle imaging, whole-body MRN, and nerve-specific MR contrast agents will likely play a major role in advancing this novel field and understanding peripheral neuromuscular diseases in the years to come.

Five levels of PACS modularity: integrating 3D and other advanced visualization tools.

The current array of PACS products and 3D visualization tools presents a wide range of options for applying advanced visualization methods in clinical radiology. The emergence of server-based rendering techniques creates new opportunities for raising the level of clinical image review. However, best-of-breed implementations of core PACS technology, volumetric image navigation, and application-specific 3D packages will, in general, be supplied by different vendors. Integration issues should be carefully considered before deploying such systems. This work presents a classification scheme describing five tiers of PACS modularity and integration with advanced visualization tools, with the goals of characterizing current options for such integration, providing an approach for evaluating such systems, and discussing possible future architectures. These five levels of increasing PACS modularity begin with what was until recently the dominant model for integrating advanced visualization into the clinical radiologist's workflow, consisting of a dedicated stand-alone post-processing workstation in the reading room. Introduction of context-sharing, thin clients using server-based rendering, archive integration, and user-level application hosting at successive levels of the hierarchy lead to a modularized imaging architecture, which promotes user interface integration, resource efficiency, system performance, supportability, and flexibility. These technical factors and system metrics are discussed in the context of the proposed five-level classification scheme.

An online evidence-based decision support system for distinguishing benign from malignant vertebral compression fractures by magnetic resonance imaging feature analysis.

Decision support systems have been used to promote the practice of evidence-based medicine. Computer-assisted diagnosis can serve as one element of evidence-based radiology. One area where such tools may provide benefit is analysis of vertebral compression fractures (VCFs), which can be a challenge in MRI interpretation. VCFs may be benign or malignant in etiology, and several MRI features may help to make this important distinction. We describe a web-based decision support system for discriminating benign from malignant VCFs as a prototype for a more general diagnostic decision support framework for radiologists. The system has three components: a feature checklist with an image gallery derived from proven reference cases, a prediction model, and a reporting mechanism. The website allows users to input the findings for a case to be interpreted using a structured feature checklist. The image gallery complements the checklist, for clarity and training purposes. The input from the checklist is then used to calculate the likelihood of malignancy by a logistic regression prediction model. Standardized report text is generated that summarizes pertinent positive and negative findings. This computer-assisted diagnosis system demonstrates the integration of three areas where diagnostic decision support can aid radiologists: first, in image interpretation, through feature checklists and illustrative image galleries; second, in feature-based prediction modeling; and third, in structured reporting. We present a diagnostic decision support tool that provides radiologists with evidence-based guidance for discriminating benign from malignant VCF. This model may be useful in other difficult-diagnosis situations and requires further clinical testing.