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BACKGROUND: To conserve personal protective equipment (PPE) and reduce exposure to potentially infected COVID-19 patients, several Californian facilities independently implemented a method of acquiring portable chest radiographs through glass barriers that was originally developed by the University of Washington. METHODS: This work quantifies the transmission of radiation through a glass barrier using six radiographic systems at five facilities. Patient entrance air kerma (EAK) and effective dose were estimated both with and without the glass barrier. Beam penetrability and resulting exposure index (EI) and deviation index (DI) were measured and used to adjust the tube current-time product (mAs) for glass barriers. Because of beam hardening, the contrast-to-noise ratio (CNR) was measured with image quality phantoms to ensure diagnostic integrity. Finally, scatter surveys were performed to assess staff radiation exposure both inside and outside the exam room. RESULTS: The glass barriers attenuated a mean of 61% of the normal X-ray beams. When the mAs was increased to match EI values, there was no discernible degradation of image quality as determined by the CNR. This was corroborated with subjective assessments of image quality by chest radiologists. The glass-hardened beams acted as a filter for low energy X-rays, and some facilities observed slight changes in patient effective doses. There was scattering from both the phantoms and the glass barriers within the room. CONCLUSIONS: Glass barriers require an approximate 2.5 times increase in beam intensity, with all other technique factors held constant. Further refinements are necessary for increased source-to-image distance and beam quality in order to adequately match EI values. This does not result in a significant increase in the radiation dose delivered to the patient. The use of lead aprons, mobile shields, and increased distance from scattering sources should be employed where practicable in order to keep staff radiation doses as low as reasonably achievable.

We describe a 40-year-old man with severe COVID-19 requiring mechanical ventilation who developed aorto-bi-iliac arterial, right lower extremity arterial, intracardiac, pulmonary arterial and ilio-caval venous thromboses and required right lower extremity amputation for acute limb ischemia. This unique case illustrates COVID-19-associated thrombotic complications occurring at multiple, different sites in the cardiovascular system of a single infected patient.

With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19.

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of 0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required.

BackgroundIt is unknown whether immunosuppression influences the physiologic state of Mycobacterium tuberculosis in vivo. We evaluated the impact of host immunity by comparing M. tuberculosis and human gene transcription in sputum between human immunodeficiency virus (HIV)-infected and uninfected patients with tuberculosis.MethodsWe collected sputum specimens before treatment from Gambians and Ugandans with pulmonary tuberculosis, revealed by positive results of acid-fast bacillus smears. We quantified expression of 2179 M. tuberculosis genes and 234 human immune genes via quantitative reverse transcription-polymerase chain reaction. We summarized genes from key functional categories with significantly increased or decreased expression.ResultsA total of 24 of 65 patients with tuberculosis were HIV infected. M. tuberculosis DosR regulon genes were less highly expressed among HIV-infected patients with tuberculosis than among HIV-uninfected patients with tuberculosis (Gambia, P < .0001; Uganda, P = .037). In profiling of human genes from the same sputa, HIV-infected patients had 3.4-fold lower expression of IFNG (P = .005), 4.9-fold higher expression of ARG1 (P = .0006), and 3.4-fold higher expression of IL10 (P = .0002) than in HIV-uninfected patients with tuberculosis.ConclusionsM. tuberculosis in HIV-infected patients had lower expression of the DosR regulon, a critical metabolic and immunomodulatory switch induced by NO, carbon monoxide, and hypoxia. Our human data suggest that decreased DosR expression may result from alternative pathway activation of macrophages, with consequent decreased NO expression and/or by poor granuloma formation with consequent decreased hypoxic stress.

The American College of Radiology, with more than 30,000 members, is the principal organization of radiologists, radiation oncologists,and clinical medical physicists in the United States. The College is a nonprofit professional society whose primary purposes are to advance thescience of radiology, improve radiologic services to the patient, study the socioeconomic aspects of the practice of radiology, and encouragecontinuing education for radiologists, radiation oncologists, medical physicists, and persons practicing in allied professional fields.The American College of Radiology will periodically define new practice parameters and technical standards for radiologic practice to helpadvance the science of radiology and to improve the quality of service to patients throughout the United States. Existing practice parameters andtechnical standards will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated.Each practice parameter and technical standard, representing a policy statement by the College, has undergone a thorough consensusprocess in which it has been subjected to extensive review and approval. The practice parameters and technical standards recognize that the safeand effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document.Reproduction or modification of the published practice parameter and technical standard by those entities not providing these services is notauthorized.?

Background: Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk‐prediction model (called SPLC‐RAT) was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking. The predictive performance of SPLC‐RAT was evaluated in a hospital‐based cohort of lung cancer survivors. Methods: The authors analyzed data from 8448 ever‐smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997–2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC‐RAT and further explored the potential of improving SPLC detection through risk model‐based surveillance using SPLC‐RAT versus existing clinical surveillance guidelines. Results: Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person‐years. The application of SPLC‐RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10‐year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC‐RAT development cohort), the observed SPLC incidence was significantly elevated in the high‐risk versus low‐risk subgroup (13.1% vs. 1.1%, p < 1 × 10–6). The risk‐based surveillance through SPLC‐RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow‐ups needed to detect one SPLC (162 vs. 202). Conclusion: In a large, hospital‐based cohort, the authors validated the predictive performance of SPLC‐RAT in identifying high‐risk survivors of SPLC and showed its potential to improve SPLC detection through risk‐based surveillance. Plain Language Summary: Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC).However, no evidence‐based guidelines for SPLC surveillance are available for lung cancer survivors.Recently, an SPLC risk‐prediction model was developed and validated using data from population‐based epidemiological cohorts and clinical trials, but real‐world validation has been lacking.Using a large, real‐world cohort of lung cancer survivors, we showed the high predictive accuracy and risk‐stratification ability of the SPLC risk‐prediction model.Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model‐based surveillance strategies compared to the existing consensus‐based clinical guidelines, including the National Comprehensive Cancer Network. Given the rapidly growing number of lung cancer survivors who are now at high risk of developing second primary lung cancer (SPLC), previous studies have identified SPLC risk factors and developed SPLC risk‐prediction models, but they lack insight into real‐world validation to help improve clinical decision‐making in SPLC surveillance for lung cancer survivors. Using a large, hospital‐based real‐world cohort of lung cancer survivors, the authors validated the predictive accuracy of an SPLC risk‐prediction model (area under the curve of 0.81), that can identify high‐risk lung cancer survivors for SPLC and can be incorporated into clinical decision‐making for SPLC surveillance to improve the systematic management of lung cancer survivors. [ABSTRACT FROM AUTHOR]