Critical preparedness and operational response actions directed for the acute and post-acute COVID-19 pandemic in Brazil: the experience of a nationwide outpatient healthcare group.

ABSTRACT: While the new Coronavirus Disease 2019 (COVID-19) pandemic rapidly spread across the world, South America was reached later in relation to Asia, Europe and the United States of America (USA). Brazil concentrates now the largest number of cases in the continent and, as the disease speedily progressed throughout the country, prompt and challenging operational strategies had to be taken by institutions caring for COVID-19 and non-COVID-19 patients in order to assure optimal workflows, triage, and management. Although hospitals in the USA, Europe and Asia have shared their experience on this subject, little has been discussed about such strategies in South America or by the perspective of outpatient centers, which are paramount in the radiology field. This article shares the guidelines adopted early in the pandemic by a nationwide outpatient healthcare center composed by a network of more than 200 patient service centers and nearly 2,000 radiologists in Brazil, discussing operational and patient management strategies, staff protection, changes adopted in the fellowship program, and the effectiveness of such measures.

Portable Chest Radiography Through Glass During COVID-19 Pandemic-Initial Experience in a Tertiary Care Center.

BACKGROUND: Portable chest radiograph for COVID-19 positive patients and persons under investigation can be acquired through glass doors or walls of isolation rooms to limit exposure to the pathogen and conserve resources. PURPOSE: To report our initial experience with acquiring portable chest radiographs through glass doors of isolation rooms. METHODS: Only 1 of 2 radiology technologist team members donned personal protective equipment and stayed inside the isolation room, while the second technologist and the radiography unit remained outside during the procedure. First hundred radiographs acquired through glass at the emergency department of our institute formed the "through glass radiograph" group. Hundred consecutive portable chest radiographs performed in a conventional manner formed the "conventional radiograph" group for comparison. Imaging database and feedback from operations leader were used to identify occurrences of a failed procedure. Suggestion of repeating the study and comments related to quality of the study were recorded from the reports of the staff radiologist. RESULTS: There was no instance of failed acquisition, nondiagnostic examination, or suggestion of repetition in both groups. No significant difference in the number of reports with quality related remarks (P > .05) was found between the 2 groups. Radiography through glass doors was associated with increased suboptimal positioning related remarks in radiology reports (P < .05). No significant association was identified among other comments about image quality. CONCLUSION: Our initial clinical experience suggests that the acquisition of portable chest radiographs through the glass doors of isolation rooms is technically feasible and results in diagnostic quality studies.

Web-Based Technology for Remote Viewing of Radiological Images: App Validation.

BACKGROUND: Internet technologies can create advanced and rich web-based apps that allow radiologists to easily access teleradiology systems and remotely view medical images. However, each technology has its own drawbacks. It is difficult to balance the advantages and disadvantages of these internet technologies and identify an optimal solution for the development of medical imaging apps. OBJECTIVE: This study aimed to compare different internet platform technologies for remotely viewing radiological images and analyze their advantages and disadvantages. METHODS: Oracle Java, Adobe Flash, and HTML5 were each used to develop a comprehensive web-based medical imaging app that connected to a medical image server and provided several required functions for radiological interpretation (eg, navigation, magnification, windowing, and fly-through). Java-, Flash-, and HTML5-based medical imaging apps were tested on different operating systems over a local area network and a wide area network. Three computed tomography colonography data sets and 2 ordinary personal computers were used in the experiment. RESULTS: The experimental results demonstrated that Java-, Flash-, and HTML5-based apps had the ability to provide real-time 2D functions. However, for 3D, performances differed between the 3 apps. The Java-based app had the highest frame rate of volume rendering. However, it required the longest time for surface rendering and failed to run surface rendering in macOS. The HTML5-based app had the fastest surface rendering and the highest speed for fly-through without platform dependence. Volume rendering, surface rendering, and fly-through performances of the Flash-based app were significantly worse than those of the other 2 apps. CONCLUSIONS: Oracle Java, Adobe Flash, and HTML5 have individual strengths in the development of remote access medical imaging apps. However, HTML5 is a promising technology for remote viewing of radiological images and can provide excellent performance without requiring any plug-ins.

Imaging of the small bowel: a review of current practice.

This article summarises radiological imaging of the small bowel, with an emphasis on Crohn's disease. Different imaging techniques are discussed, including the advantages and disadvantages of each modality, and radiological findings for common small bowel pathologies are described, supplemented with pictorial examples.

Radioanalytical Techniques to Quantitatively Assess the Biological Uptake and In Vivo Behavior of Hazardous Substances.

Concern about environmental exposure to hazardous substances has grown over the past several decades, because these substances have adverse effects on human health. Methods used to monitor the biological uptake of hazardous substances and their spatiotemporal behavior in vivo must be accurate and reliable. Recent advances in radiolabeling chemistry and radioanalytical methodologies have facilitated the quantitative analysis of toxic substances, and whole-body imaging can be achieved using nuclear imaging instruments. Herein, we review recent literature on the radioanalytical methods used to study the biological distribution, changes in the uptake and accumulation of hazardous substances, including industrial chemicals, nanomaterials, and microorganisms. We begin with an overview of the radioisotopes used to prepare radiotracers for in vivo experiments. We then summarize the results of molecular imaging studies involving radiolabeled toxins and their quantitative assessment. We conclude the review with perspectives on the use of radioanalytical methods for future environmental research.

Radiomic prediction models for the level of Ki-67 and p53 in glioma.

OBJECTIVE: To identify glioma radiomic features associated with proliferation-related Ki-67 antigen and cellular tumour antigen p53 levels, common immunohistochemical markers for differentiating benign from malignant tumours, and to generate radiomic prediction models. METHODS: Patients with glioma, who were scanned before therapy using standard brain magnetic resonance imaging (MRI) protocols on T1 and T2 weighted imaging, were included. For each patient, regions-of-interest (ROI) were drawn based on tumour and peritumoral areas (5/10/15/20 mm), and features were identified using feature calculations, and used to create and assess logistic regression models for Ki-67 and p53 levels. RESULTS: A total of 92 patients were included. The best area under the curve (AUC) for the Ki-67 model was 0.773 for T2 weighted imaging in solid glioma (sensitivity, 0.818; specificity, 0.833), followed by a less reliable AUC of 0.773 (sensitivity, 0.727; specificity 0.667) in 20-mm peritumoral areas. The highest AUC for the p53 model was 0.709 (sensitivity, 1; specificity, 0.4) for T2 weighted imaging in 10-mm peritumoral areas. CONCLUSION: Using T2-weighted imaging, the prediction model for Ki-67 level in solid glioma tissue was better than the p53 model. The 20-mm and 10-mm peritumoral areas in the Ki-67 and p53 model, respectively, showed predictive effects, suggesting value in further research into areas without conventional MRI features.

Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant.

BACKGROUND & AIMS: In the context of liver transplantation (LT) for hepatocellular carcinoma (HCC), prediction models are used to ensure that the risk of post-LT recurrence is acceptably low. However, the weighting that 'response to neoadjuvant therapies' should have in such models remains unclear. Herein, we aimed to incorporate radiological response into the Metroticket 2.0 model for post-LT prediction of "HCC-related death", to improve its clinical utility. METHODS: Data from 859 transplanted patients (2000-2015) who received neoadjuvant therapies were included. The last radiological assessment before LT was reviewed according to the modified RECIST criteria. Competing-risk analysis was applied. The added value of including radiological response into the Metroticket 2.0 was explored through category-based net reclassification improvement (NRI) analysis. RESULTS: At last radiological assessment prior to LT, complete response (CR) was diagnosed in 41.3%, partial response/stable disease (PR/SD) in 24.9% and progressive disease (PD) in 33.8% of patients. The 5-year rates of "HCC-related death" were 3.1%, 9.6% and 13.4% in those with CR, PR/SD, or PD, respectively (p <0.001). Log10AFP (p <0.001) and the sum of number and diameter of the tumour/s (p <0.05) were determinants of "HCC-related death" for PR/SD and PD patients. To maintain the post-LT 5-year incidence of "HCC-related death" <30%, the Metroticket 2.0 criteria were restricted in some cases of PR/SD and in all cases with PD, correctly reclassifying 9.4% of patients with "HCC-related death", at the expense of 3.5% of patients who did not have the event. The overall/net NRI was 5.8. CONCLUSION: Incorporating the modified RECIST criteria into the Metroticket 2.0 framework can improve its predictive ability. The additional information provided can be used to better judge the suitability of candidates for LT following neoadjuvant therapies. LAY SUMMARY: In the context of liver transplantation for patients with hepatocellular carcinoma, prediction models are used to ensure that the risk of recurrence after transplantation is acceptably low. The Metroticket 2.0 model has been proposed as an accurate predictor of "tumour-related death" after liver transplantation. In the present study, we show that its accuracy can be improved by incorporating information relating to the radiological responses of patients to neoadjuvant therapies.

Radiomics: from qualitative to quantitative imaging.

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes. As a result of advances in both computational hardware and machine learning algorithms, computers are making great strides in obtaining quantitative information from imaging and correlating it with outcomes. Radiomics, in its two forms "handcrafted and deep," is an emerging field that translates medical images into quantitative data to yield biological information and enable radiologic phenotypic profiling for diagnosis, theragnosis, decision support, and monitoring. Handcrafted radiomics is a multistage process in which features based on shape, pixel intensities, and texture are extracted from radiographs. Within this review, we describe the steps: starting with quantitative imaging data, how it can be extracted, how to correlate it with clinical and biological outcomes, resulting in models that can be used to make predictions, such as survival, or for detection and classification used in diagnostics. The application of deep learning, the second arm of radiomics, and its place in the radiomics workflow is discussed, along with its advantages and disadvantages. To better illustrate the technologies being used, we provide real-world clinical applications of radiomics in oncology, showcasing research on the applications of radiomics, as well as covering its limitations and its future direction.

Dual-energy CT: theoretical principles and clinical applications.

The physical principles of dual-energy computed tomography (DECT) are as old as computed tomography (CT) itself. To understand the strengths and the limits of this technology, a brief overview of theoretical basis of DECT will be provided. Specific attention will be focused on the interaction of X-rays with matter, on the principles of attenuation of X-rays in CT toward the intrinsic limits of conventional CT, on the material decomposition algorithms (two- and three-basis-material decomposition algorithms) and on effective Rho-Z methods. The progresses in material decomposition algorithms, in computational power of computers and in CT hardware, lead to the development of different technological solutions for DECT in clinical practice. The clinical applications of DECT are briefly reviewed in relation to the specific algorithms.

Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

PURPOSE: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground truth. The second aim is to demonstrate the feasibility of magnetic resonance imaging (MRI)-based proton therapy planning for the brain by assessing the range shift error within the clinical acceptance threshold. METHODS AND MATERIALS: The image database included 15 pairs of MRI/CT scans of the head. Three DCNNs were trained to estimate, for each voxel, the Hounsfield unit (HU) value from MRI intensities. Each DCNN gave an estimation in the axial, sagittal, and coronal plane, respectively. The median HU among the 3 values was selected to build the sCT. The sCT/CT agreement was evaluated by a mean absolute error (MAE) and mean error, computed within the head contour and on 6 different tissues. Dice similarity coefficients were calculated to assess the geometric overlap of bone and air cavities segmentations. A 3-beam proton therapy plan was simulated for each patient. Beam-by-beam range shift (RS) analysis was conducted to assess the proton-stopping power estimation. RS analysis was performed using clinically accepted thresholds of (1) 3.5% + 1 mm and (2) 2.5% + 1.5 mm of the total range. RESULTS: DCNN multiplane statistically outperformed single-plane prediction of sCT (P < .025). MAE and mean error within the head were 54 ± 7 HU and -4 ± 17 HU (mean ± standard deviation), respectively. Soft tissues were very close to perfect agreement (11 ± 3 HU in terms of MAE). Segmentation of air and bone regions led to a Dice similarity coefficient of 0.92 ± 0.03 and 0.93 ± 0.02, respectively. Proton RS was always below clinical acceptance thresholds, with a relative RS error of 0.14% ± 1.11%. CONCLUSIONS: The multiplane DCNN approach significantly improved the sCT prediction compared with other DCNN methods presented in the literature. The method was demonstrated to be highly accurate for MRI-only proton planning purposes.

Clinical effectiveness of a sonographer-led, cardiologist-interpreted stress echocardiography service in the rapid access stable chest pain clinic.

AIMS: To assess the clinical effectiveness of a sonographer-led, cardiologist-interpreted stress echocardiography (SE) service in a rapid access stable chest pain clinic (RACPC) setting. METHODS AND RESULTS: Baseline data was collected prospectively on 768 consecutive patients, referred from the RACPC, who underwent SE between May 2014 and May 2015. Retrospective analysis was performed on follow-up data for outcomes. Among 768 patients (mean age 58 years, 57.8% males) with a mean pre-test probability of coronary artery disease (CAD) of 31%, 675 (88%) underwent SE on the same day as the RACPC consultation. Diagnostic tests were obtained in 749 (97.5%) cases with 62 (8.1%) demonstrating inducible ischemia. Coronary angiography was performed in 61 patients of whom 54 demonstrated flow-limiting CAD (positive predictive value: 88.5%). There was no occurrence of serious adverse events. During a mean follow-up period of 2.5 years, 20 first cardiac events were recorded, of which annualised events in the normal SE group were 0.64% versus 5.8% in patients with an abnormal SE (log rank p < 0.001). CONCLUSION: Sonographer-led SE interpreted by a cardiologist is feasible, safe and efficacious. It impacted on the management of patients with appropriate outcomes and may be a cost-efficient and safer alternative to other non-invasive imaging modalities in the RACPC setting.

Sí: un error es un tesoro, pues nos permite aprender; pero en el informe radiológico, ¿no sería mejor hablar de discrepancias? / Certainly: an error is a gift, so we can learn from it. Nevertheless, related to the radiological report, should we not consider talking about discrepancies?

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Instagram as a Vehicle for Education: What Radiology Educators Need to Know.

Since its inception in 2010, Instagram has rapidly grown into one of the world's largest social media forums, with over 700 million registered users. In the field of medicine, Instagram has been used for professional development and is also being added to the armamentarium of social media vehicles for education. Utilization of Instagram for medical education lags behind Facebook and Twitter, as many educators may not recognize the potential role. The purpose of this manuscript is to describe unique features of Instagram that are not found on Facebook and Twitter, with the aim of facilitating use of Instagram for radiology education.