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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.

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.

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

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.

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.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.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.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.

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.

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.

By virtue of its information technology-oriented infrastructure, the specialty of radiology is uniquely positioned to be at the forefront of efforts to promote data sharing across the healthcare enterprise, including particularly image sharing. The potential benefits of image sharing for clinical, research, and educational applications in radiology are immense. In this work, our group-the Association of University Radiologists (AUR) Radiology Research Alliance Task Force on Image Sharing-reviews the benefits of implementing image sharing capability, introduces current image sharing platforms and details their unique requirements, and presents emerging platforms that may see greater adoption in the future. By understanding this complex ecosystem of image sharing solutions, radiologists can become important advocates for the successful implementation of these powerful image sharing resources.

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. Summary 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.

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 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.