From omission to excellence: Reducing the percentage of incomplete trainee reports by ensuring documentation of comparison studies.

The inclusion of comparison studies within radiology reports is an important, standard practice. Despite this, we identified that after-hours preliminary reports rendered by trainees within our institution often omitted reference to comparison studies for pediatric inpatient portable radiographs. We addressed this issue through a quality improvement project targeting pediatric radiographs. Key interventions included modifying the structured reports by removing default text in the comparison field, designating the comparison field as mandatory, and restructuring the report templates to remove extraneous information. We also initiated a targeted educational campaign. 392 reports before and 267 reports after intervention (total 732 reports) were evaluated to determine the number of reports lacking comparison information when comparisons were available. Following the interventions, there was a statistically significant decrease in incomplete reports from 12.5% to 6%. This project highlights the success of utilizing structured reporting to improve the quality of trainee reports.

Imaging Genomics and Multiomics: A Guide for Beginners Starting Radiomics-Based Research.

Radiomics uses advanced mathematical analysis of pixel-level information from radiologic images to extract existing information in traditional imaging algorithms. It is intended to find imaging biomarkers related to the genomics of tumors or disease patterns that improve medical care by advanced detection of tumor response patterns in tumors and to assess prognosis. Radiomics expands the paradigm of medical imaging to help with diagnosis, management of diseases and prognostication, leveraging image features by extracting information that can be used as imaging biomarkers to predict prognosis and response to treatment. Radiogenomics is an emerging area in radiomics that investigates the association between imaging characteristics and gene expression profiles. There are an increasing number of research publications using different radiomics approaches without a clear consensus on which method works best. We aim to describe the workflow of radiomics along with a guide of what to expect when starting a radiomics-based research project.

Teaching with Technology-Matching Pedagogy with Purpose in Radiology Education.

The response to pandemic-related teaching disruption has revealed dynamic levels of learning and teaching flexibility and rapid technology adoption of radiology educators and trainees. Shutdowns and distancing requirements accelerated the adoption of technology as an educational tool, in some instances supplanting in-person education entirely. Despite the limitations of remote interaction, many educational advantages were recognized that can be leveraged in developing distance learning paradigms. The specific strategies employed should match modern learning science, enabling both students and educators to mutually grow as lifelong learners. As panel members of the "COVID: Faculty perspective" Task Force of the Association of University Radiologists Radiology Research Alliance, we present a review of key learning principles which educators can use to identify techniques that enhance resident learning and present an organized framework for applying technology-aided techniques aligned with modern learning principles. Our aim is to facilitate the purposeful integration of learning tools into the training environment by matching these tools to established educational frameworks. With these frameworks in mind, radiology educators have the opportunity to re-think the balance between traditional curricular design and modern digital teaching tools and models.

COVID-19 Diagnosis on Chest Radiograph Using Artificial Intelligence.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disrupted the world since 2019, causing significant morbidity and mortality in developed and developing countries alike. Although substantial resources have been diverted to developing diagnostic, preventative, and treatment measures, disparities in the availability and efficacy of these tools vary across countries. We seek to assess the ability of commercial artificial intelligence (AI) technology to diagnose COVID-19 by analyzing chest radiographs. MATERIALS AND METHODS: Chest radiographs taken from symptomatic patients within two days of polymerase chain reaction (PCR) tests were assessed for COVID-19 infection by board-certified radiologists and commercially available AI software. Sixty patients with negative and 60 with positive COVID reverse transcription-polymerase chain reaction (RT-PCR) tests were chosen. Results were compared against results of the PCR test for accuracy and statistically analyzed by receiver operating characteristic (ROC) curves along with area under the curve (AUC) values. RESULTS: A total of 120 chest radiographs (60 positive and 60 negative RT-PCR tests) radiographs were analyzed. The AI software performed significantly better than chance (p = 0.001) and did not differ significantly from the radiologist ROC curve (p = 0.78). CONCLUSION: Commercially available AI software was not inferior compared with trained radiologists in accurately identifying COVID-19 cases by analyzing radiographs. While RT-PCR testing remains the standard, current advances in AI help correctly analyze chest radiographs to diagnose COVID-19 infection.

Radiologists' Diagnostic Performance in Differentiation of Rickets and Classic Metaphyseal Lesions on Radiographs: A Multicenter Study.

BACKGROUND. Despite evidence supporting the specificity of classic metaphyseal lesions (CML) for the diagnosis of child abuse, some medicolegal practitioners claim that CML result from rickets rather than trauma. OBJECTIVE. The purpose of this study was to evaluate radiologists' diagnostic performance in differentiating rickets and CML on radiographs. METHODS. This retrospective seven-center study included children younger than 2 years who underwent knee radiography from January 2007 to December 2018 and who had either rickets (25-hydroxyvitamin D level < 20 ng/mL and abnormal knee radiographs) or knee CML and a diagnosis of child abuse from a child abuse pediatrician. Additional injuries were identified through medical record review. Radiographs were cropped and zoomed to present similar depictions of the knee. Eight radiologists independently interpreted radiographs for diagnoses of rickets or CML, rated confidence levels, and recorded associated radiographic signs. RESULTS. Seventy children (27 girls, 43 boys) had rickets; 77 children (37 girls, 40 boys) had CML. Children with CML were younger than those with rickets (mean, 3.7 vs 14.2 months, p < .001; 89.6% vs 5.7% younger than 6 months; 3.9% vs 65.7% older than 1 year). All children with CML had injuries in addition to the knee CML identified at physical examination or other imaging examinations. Radiologists had almost perfect agreement for moderate- or high-confidence interpretations of rickets (κ = 0.92) and CML (κ = 0.89). Across radiologists, estimated sensitivity, specificity, and accuracy for CML for moderate- or high-confidence interpretations were 95.1%, 97.0%, and 96.0%. Accuracy was not significantly different between pediatric and nonpediatric radiologists (p = .20) or between less experienced and more experienced radiologists (p = .57). Loss of metaphyseal zone of provisional calcification, cupping, fraying, and physeal widening were more common in rickets than CML, being detected in less than 4% of children with CML. Corner fracture, bucket-handle fracture, subphyseal lucency, deformed corner, metaphyseal irregularity, and subperiosteal new bone formation were more common in CML than rickets, being detected in less than 4% of children with rickets. CONCLUSION. Radiologists had high interobserver agreement and high diagnostic performance for differentiating rickets and CML. Recognition that CML mostly occur in children younger than 6 months and are unusual in children older than 1 year may assist interpretation. CLINICAL IMPACT. Rickets and CML have distinct radiographic signs, and radiologists can reliably differentiate these two entities.

Early pulmonary complications related to cancer treatment in children.

In this review, we summarize early pulmonary complications related to cancer therapy in children and highlight characteristic findings on imaging that should be familiar to a radiologist reviewing imaging from pediatric cancer patients.

Late pulmonary complications related to cancer treatment in children.

As the number of childhood cancer survivors increases, a heightened awareness and recognition of therapy-related late effects is becoming more important. Pulmonary complications are the third leading cause of late mortality in cancer survivors. Diagnosis of these complications on chest imaging helps facilitate prompt treatment to mitigate adverse outcomes. In this review, we summarize the imaging of late pulmonary complications of cancer therapy in children and highlight characteristic findings that should be recognized by radiologists.

Skeletal muscle mass as a marker to predict outcomes in children and young adults with cancer.

PURPOSE: Nutrition is an important outcome predictor in oncology patients including treatment response, physical disability, quality of life, and overall survival. Sarcopenia (loss of skeletal muscle mass and function) is a demonstrated marker of nutritional status in adults, but data are more limited in children. The purpose of this study was to evaluate whether total psoas muscle area (tPMA) measured at the time of cancer diagnosis predicts overall survival (OS), disease free survival (DFS), or number of days neutropenic. METHODS: A retrospective study was performed. tPMA was measured at the L3 and L4 mid-lumbar vertebral body level by a single reviewer on cross-sectional imaging studies performed within 2 weeks of primary oncologic diagnosis for all oncology patients who received their primary therapy at Cincinnati Children's Hospital between 1/1/2000 and 12/31/2013. Spearman's correlation was used to assess the association between tPMA and OS, DFS, days neutropenic, and adjusted days neutropenic. Subanalysis was performed assessing the relationship of tumor type and age at diagnosis with each parameter. RESULTS: 164 patients (median age 9.9 years; 89 M/75 F) were included in the study. Days neutropenic and normalized days neutropenic were significantly but weakly negatively correlated with tPMA at L3 (r = - 0.24, p < 0.002 and r = - 0.18, p < 0.05 respectively) and L4 (r = - 0.25, p < 0.002; and and r = - 0.19, p < 0.02 respectively). At subanalysis, the correlation between anthropometric features and normalized days neutropenic was only seen with brain tumors. There was no statistically significant relationship between sarcopenia at diagnosis and DFS or OS overall or in subanalysis. CONCLUSION: There is a weak inverse relationship between days neutropenic and psoas muscle bulk in pediatric and young adult oncology patients suggesting a relationship between nutritional status and cell recovery. Measures of sarcopenia, however, did not correlate with DFS or OS.

Normative Values of Pediatric Thoracic Aortic Diameters Indexed to Body Surface Area Using Computed Tomography.

PURPOSE: The purpose of this study was to establish normative values for the thoracic aorta diameter in pediatric patients from birth to 18 years of age using computed tomography (CT) measurements and to create nomograms related to body surface area (BSA). METHODS: A total of 623 pediatric patients without cardiovascular disease (42.1% females; from 3 d to 18 y old) with high-quality, non-electrocardiogram-gated, contrast-enhanced CT imaging of the chest were retrospectively evaluated. Systematic measurements of the aortic diameter at predetermined levels were recorded, and demographic data including age, sex, ethnicity, and BSA were collected. Reference graphs plotting BSA over aortic diameter included the mean and Z -3 to Z +3, where Z represents SDs from the mean. RESULTS: The study population was divided into 2 groups (below 2 and greater than or equal to 2 y old). There were no significant differences in average aortic measurements between males and females. Both age groups exhibited significant positive correlations among all size-related metrics (all P <0.001) with BSA having the highest correlation. For both groups, the average orthogonal thoracic aortic diameters at each level of the thoracic aorta were used to create nomograms. CONCLUSION: This study establishes clinically applicable, BSA-specific reference values of the normal thoracic aorta for the pediatric population from CT imaging.

Multispecialty Enterprise Imaging Workgroup Consensus on Interactive Multimedia Reporting Current State and Road to the Future: HIMSS-SIIM Collaborative White Paper.

Diagnostic and evidential static image, video clip, and sound multimedia are captured during routine clinical care in cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, endoscopic procedural specialties, and other medical disciplines. Providers typically describe the multimedia findings in contemporaneous electronic health record clinical notes or associate a textual interpretative report. Visual communication aids commonly used to connect, synthesize, and supplement multimedia and descriptive text outside medicine remain technically challenging to integrate into patient care. Such beneficial interactive elements may include hyperlinks between text, multimedia elements, alphanumeric and geometric annotations, tables, graphs, timelines, diagrams, anatomic maps, and hyperlinks to external educational references that patients or provider consumers may find valuable. This HIMSS-SIIM Enterprise Imaging Community workgroup white paper outlines the current and desired clinical future state of interactive multimedia reporting (IMR). The workgroup adopted a consensus definition of IMR as "interactive medical documentation that combines clinical images, videos, sound, imaging metadata, and/or image annotations with text, typographic emphases, tables, graphs, event timelines, anatomic maps, hyperlinks, and/or educational resources to optimize communication between medical professionals, and between medical professionals and their patients." This white paper also serves as a precursor for future efforts toward solving technical issues impeding routine interactive multimedia report creation and ingestion into electronic health records.

Blockchain Technology: Principles and Applications in Medical Imaging.

Blockchain is an immutable, encrypted, distributed ledger technology. While initially devised for and most commonly referenced with cryptocurrencies, there are an increasing number of applications outside finance, many of which are relevant to medical imaging. In this paper, the concepts and principles underlying the technology and applications relevant to medical imaging are discussed, in addition to potential challenges with implementations such as public versus private key access, distributed ledger size constraints, speed, complexity, and security pitfalls. Potential use cases for blockchain specifically relevant to medical imaging include image sharing including direct patient ownership of images, tracking of implanted medical devices, research, teleradiology, and artificial intelligence. While blockchain offers exciting ways to facilitate the storage and distribution of medical images, similar to the advent of picture archiving and communication systems decades ago, it does have several key limitations of which healthcare providers of medical imaging and imaging informatics professionals should be aware.

Radiology, Mobile Devices, and Internet of Things (IoT).

Radiology by its nature is intricately connected to the Internet and is at the forefront of technology in medicine. The past few years have seen a dramatic rise in Internet-based technology in healthcare, with imaging as a core application. Numerous Internet-based applications and technologies have made forays into medicine, and for radiology it is more seamless than in other clinical specialties. Many applications in the practice of radiology are Internet based and more applications are being added every day. Introduction of mobile devices and their integration into imaging workflow has reinforced the role played by the Internet in radiology. Due to the rapid proliferation of wearable devices and smartphones, IoT-enabled technology is evolving healthcare from conventional hub-based systems to more personalized healthcare systems. This article briefly discusses how the IoT plays a useful role in daily imaging workflow and current and potential future applications, how mobile devices can be integrated into radiology workflows, and the impact of the IoT on resident and medical student education, research, and patient engagement in radiology.

Use of MR Urography in Pediatric Patients.

PURPOSE OF REVIEW: In this article, we describe the basics of how magnetic resonance urography (MRU) is performed in the pediatric population as well as the common indications and relative performance compared to standard imaging modalities. RECENT FINDINGS: Although MRU is still largely performed in major academic or specialty imaging centers, more and more applications in the pediatric setting have been described in the literature. MRU is a comprehensive imaging modality for evaluating multiple pediatric urologic conditions combining excellent anatomic detail with functional information previously only available via renal scintigraphy. While generally still reserved for problem solving, MRU should be considered for some conditions as an early imaging technique.

Deep Learning in Radiology.

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care.

A Comprehensive Approach to Convert a Radiology Department From Coding Based on International Classification of Diseases, Ninth Revision, to Coding Based on International Classification of Diseases, Tenth Revision.

PURPOSE: The purpose of this study was to adapt our radiology reports to provide the documentation required for specific International Classification of Diseases, tenth rev (ICD-10) diagnosis coding. MATERIALS AND METHODS: Baseline data were analyzed to identify the reports with the greatest number of unspecified ICD-10 codes assigned by computer-assisted coding software. A two-part quality improvement initiative was subsequently implemented. The first component involved improving clinical histories by utilizing technologists to obtain information directly from the patients or caregivers, which was then imported into the radiologist's report within the speech recognition software. The second component involved standardization of report terminology and creation of four different structured report templates to determine which yielded the fewest reports with an unspecified ICD-10 code assigned by an automated coding engine. RESULTS: In all, 12,077 reports were included in the baseline analysis. Of these, 5,151 (43%) had an unspecified ICD-10 code. The majority of deficient reports were for radiographs (n = 3,197; 62%). Inadequacies included insufficient clinical history provided and lack of detailed fracture descriptions. Therefore, the focus was standardizing terminology and testing different structured reports for radiographs obtained for fractures. At baseline, 58% of radiography reports contained a complete clinical history with improvement to >95% 8 months later. The total number of reports that contained an unspecified ICD-10 code improved from 43% at baseline to 27% at completion of this study (P < .0001). CONCLUSION: The number of radiology studies with a specific ICD-10 code can be improved through quality improvement methodology, specifically through the use of technologist-acquired clinical histories and structured reporting.