AJR. American journal of roentgenology
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OBJECTIVE. Recurrent inflammation of the appendiceal stump after appendectomy is rare; published case series have included no more than six patients. The purpose of this study was to report the clinical and CT findings in a larger original series. ⋯ CONCLUSION. Stump appendicitis has a characteristic CT appearance and may occur within the first year after appendectomy or many years later. A long (≥ 2 cm) appendiceal stump from laparoscopic appendectomy and retained appendicolith may predispose adult patients to recurrent obstruction and inflammation.
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AJR Am J Roentgenol · Nov 2020
Comparative StudyComparison of Diagnostic Accuracy for TNM Stage Among Whole-Body MRI and Coregistered PET/MRI Using 1.5-T and 3-T MRI Systems and Integrated PET/CT for Non-Small Cell Lung Cancer.
OBJECTIVE. The purpose of this study was to compare diagnostic accuracy of TNM stage for whole-body MRI and coregistered PET/MRI using 1.5-T and 3-T MRI systems and PET/CT in patients with non-small cell lung cancer (NSCLC). SUBJECTS AND METHODS. ⋯ Moreover, diagnostic accuracy of whole-body MRI using a 3-T system was significantly higher than that of PET/MRI using a 1.5-T system (p = 0.02). CONCLUSION. Whole-body MRI and coregistered PET/MRI using 3-T and 1.5-T systems are as accurate or more accurate than PET/CT, whereas differences between 3-T and 1.5-T MRI systems are not considered significant.
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AJR Am J Roentgenol · Nov 2020
Comparative StudyA Comparison of Clinical and Chest CT Findings in Patients With Influenza A (H1N1) Virus Infection and Coronavirus Disease (COVID-19).
OBJECTIVE. The purpose of this study was to compare clinical and chest CT findings in patients with influenza A (H1N1) pneumonia and coronavirus disease (COVID-19) pneumonia. MATERIALS AND METHODS. ⋯ CONCLUSION. On CT, the significant differences between influenza A (H1N1) pneumonia and COVID-19 pneumonia were findings of linear opacification, crazy-paving sign, vascular enlargement, pleural thickening, and pleural effusion, which were more common in patients with COVID-19 pneumonia, and bronchiectasis and pleural effusion, which were more common in patients with influenza A (H1N1) pneumonia. Other imaging findings, including peripheral or peribronchovascular distribution, ground-glass opacities (GGO), consolidation, subpleural line, air bronchogram, and bronchial distortion, were not significantly different between the two patient groups.
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AJR Am J Roentgenol · Nov 2020
Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.
OBJECTIVE. Outpatient appointment no-shows are a common problem. Artificial intelligence predictive analytics can potentially facilitate targeted interventions to improve efficiency. ⋯ The no-show rates of contactable and noncontactable patients in the group at high risk of appointment no-shows as predicted by the model were 17.5% and 40.3%, respectively (p < 0.0001). CONCLUSION. Machine learning predictive analytics perform moderately well in predicting complex problems involving human behavior using a modest amount of data with basic feature engineering, and they can be incorporated into routine workflow to improve health care delivery.
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AJR Am J Roentgenol · Nov 2020
Diagnostic Ultrasound Services During the Coronavirus Disease (COVID-19) Pandemic.
OBJECTIVE. Nosocomial transmission of coronavirus disease (COVID-19) to frontline health care workers is well known, and health care workers may inadvertently become vectors for onward transmission. Ultrasound (US) service providers are at significant risk because scanning usually requires prolonged close patient contact. ⋯ With increasing use of point-of-care and portable diagnostic US services, the risk is substantial. CONCLUSION. Our experience and protocols may help service providers with their own effective response against COVID-19.