Unmet needs and perspectives in rheumatoid arthritis-associated interstitial lung disease: A critical review.

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovitis as the most common clinical manifestation, and interstitial lung disease (RA-ILD) represents one of the most common and potentially severe extra-articular features. Our current understanding of the mechanisms and predictors of RA-ILD is limited despite the demonstration that an early identification of progressive fibrosing forms is crucial to provide timely treatment with antifibrotic therapies. While high resolution computed tomography is the gold standard technique for the diagnosis and follow-up of RA-ILD, it has been hypothesized that serum biomarkers (including novel and rare autoantibodies), new imaging techniques such as ultrasound of the lung, or the application of innovative radiologic algorithms may help towards predicting and detecting early forms of diseases. Further, while new treatments are becoming available for idiopathic and connective tissue disease-associated forms of lung fibrosis, the treatment of RA-ILD remains anecdotal and largely unexplored. We are convinced that a better understanding of the mechanisms connecting RA with ILD in a subgroup of patients as well as the creation of adequate diagnostic pathways will be mandatory steps for a more effective management of this clinically challenging entity.

The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the "Real World"?

(1) Background: Once lung lesions are identified on CT scans, they must be characterized by assessing the risk of malignancy. Despite the promising performance of computer-aided systems, some limitations related to the study design and technical issues undermine these tools' efficiency; an "intelligent agent" to detect and non-invasively characterize lung lesions on CT scans is proposed. (2) Methods: Two main modules tackled the detection of lung nodules on CT scans and the diagnosis of each nodule into benign and malignant categories. Computer-aided detection (CADe) and computer aided-diagnosis (CADx) modules relied on deep learning techniques such as Retina U-Net and the convolutional neural network; (3) Results: Tests were conducted on one publicly available dataset and two local datasets featuring CT scans acquired with different devices to reveal deep learning performances in "real-world" clinical scenarios. The CADe module reached an accuracy rate of 78%, while the CADx's accuracy, specificity, and sensitivity stand at 80%, 73%, and 85.7%, respectively; (4) Conclusions: Two different deep learning techniques have been adapted for CADe and CADx purposes in both publicly available and private CT scan datasets. Experiments have shown adequate performance in both detection and diagnosis tasks. Nevertheless, some drawbacks still characterize the supervised learning paradigm employed in networks such as CNN and Retina U-Net in real-world clinical scenarios, with CT scans from different devices with different sensors' fingerprints and spatial resolution. Continuous reassessment of CADe and CADx's performance is needed during their implementation in clinical practice.

Risk factors for myocardial injury and death in patients with COVID-19: insights from a cohort study with chest computed tomography.

AIMS: Whether pulmonary artery (PA) dimension and coronary artery calcium (CAC) score, as assessed by chest computed tomography (CT), are associated with myocardial injury in patients with coronavirus disease 2019 (COVID-19) is not known. The aim of this study was to explore the risk factors for myocardial injury and death and to investigate whether myocardial injury has an independent association with all-cause mortality in patients with COVID-19. METHODS AND RESULTS: This is a single-centre cohort study including consecutive patients with laboratory-confirmed COVID-19 undergoing chest CT on admission. Myocardial injury was defined as high-sensitivity troponin I >20 ng/L on admission. A total of 332 patients with a median follow-up of 12 days were included. There were 68 (20.5%) deaths; 123 (37%) patients had myocardial injury. PA diameter was higher in patients with myocardial injury compared with patients without myocardial injury [29.0 (25th-75th percentile, 27-32) mm vs. 27.7 (25-30) mm, P < 0.001). PA diameter was independently associated with an increased risk of myocardial injury [adjusted odds ratio 1.10, 95% confidence interval (CI) 1.02-1.19, P = 0.01] and death [adjusted hazard ratio (HR) 1.09, 95% CI 1.02-1.17, P = 0.01]. Compared with patients without myocardial injury, patients with myocardial injury had a lower prevalence of a CAC score of zero (25% vs. 55%, P < 0.001); however, the CAC score did not emerge as a predictor of myocardial injury by multivariable logistic regression. Myocardial injury was independently associated with an increased risk of death by multivariable Cox regression (adjusted HR 2.25, 95% CI 1.27-3.96, P = 0.005). Older age, lower estimated glomerular filtration rate, and lower PaO2/FiO2 ratio on admission were other independent predictors for both myocardial injury and death. CONCLUSIONS: An increased PA diameter, as assessed by chest CT, is an independent risk factor for myocardial injury and mortality in patients with COVID-19. Myocardial injury is independently associated with an approximately two-fold increased risk of death.

Gadoxetic acid-enhanced MRI of transient hepatic enhancement differences: Another cause of hypointense observation on hepatobiliary phase.

PURPOSE: To retrospectively determine the frequency, natural history and factors associated with the presence of transient hepatic enhancement difference showing hypointensity on hepatobiliary phase images of gadoxetic acid-enhanced MRI. MATERIALS AND METHODS: Gadoxetic acid-enhanced MRI of 125 patients (91 men; 34 women) with transient hepatic enhancement difference were retrospectively reviewed. Three readers qualitatively and quantitatively evaluated MR imaging features and evolution at follow up. The Chi-square test, Fisher's exact test and Kruskall-Wallis rank test were used for statistical analysis. RESULTS: Transient hepatic enhancement difference were hypointense on hepatobiliary phase images in 20 of 125 cases (16%). At univariate analysis there was association with wedge-shape morphology (p < 0.001), size ≥21 mm (p < 0.001), hyperintensity on T2-weighted imaging (p < 0.001), restricted diffusion (p < 0.001) and previous treatment (p < 0.005). At multivariate analysis, the following factors were associated: previous treatment (p < 0.05), hyperintensity on T2-weighted imaging (p < 0.001) and size ≥21 mm (p < 0.001). Of 12 patients with hypointense transient hepatic enhancement difference on hepatobiliary phase images who had follow-up MRI, nine showed reduction in size. CONCLUSION: Transient hepatic enhancement difference observations showing hypointensity on hepatobiliary phase images of gadoxetic acid-enhanced MRI are not infrequent and may shrink at follow-up. They are more likely associated with size ≥21 mm, hyperintensity on T2-weighted images and previous treatment of adjacent tumor.

The cheating liver: imaging of focal steatosis and fatty sparing.

Focal steatosis and fatty sparing are a frequent finding in liver imaging, and can mimic solid lesions. Liver regional variations in the degree of fat accumulation can be related to vascular anomalies, metabolic disorders, use of certain drugs or coexistence of hepatic masses. CT and MRI are the modalities of choice for the noninvasive diagnosis of hepatic steatosis. Knowledge of CT and MRI appearance of focal steatosis and fatty sparing is crucial for an accurate diagnosis, and to rule-out other pathologic processes. This paper will review the CT and MRI techniques for the diagnosis of hepatic steatosis and the CT and MRI features of common and uncommon causes of focal steatosis and fatty sparing.

Evaluation of insulin resistance in a cohort of HIV-infected youth.

OBJECTIVE: Metabolic abnormalities, including impairment of glucose homeostasis, have been well characterized in HIV-infected patients. In contrast to adults, insulin resistance and diabetes mellitus appear to be relatively uncommon finding in youth. DESIGN: We assessed insulin resistance, and associated risk factors, in a population of vertically HIV-infected children and young adults, when compared with a control population of healthy children. METHODS: At the time of enrolment, weeks of pregnancy, birth weight, sex, age, weight, height, body mass index (BMI), pubertal stages, CDC classification, blood pressure, clinical lipodystrophy, hepatitis B or C co-infection, antiretroviral therapy, CD4 T lymphocyte counts, and HIV-RNA levels were recorded. Fasting plasma glucose and insulin levels and homeostatic model assessment-insulin resistance (HOMA-IR) were determined. These parameters were compared between HIV patients and healthy controls with multivariate analyses. RESULTS: Fasting insulin levels (OR=1.21, P<0.001) and glycemia (OR=0.89, P<0.001) were significantly different between HIV-infected patients and controls. Antiretroviral therapy duration (r=0.281, P<0.05), triglyceride levels (r=0.286, P<0.05), age (r=0.299, P<0.05), and BMI SDS (r=0.485, P<0.001) were significant predictor variables of insulin resistance, expressed as HOMA-IR. Moreover, clinical lipodystrophy seems to be strongly correlated to glycemia (P<0.05), triglyceride levels (P<0.05), serum insulin levels (P<0.001), HOMA-IR (P<0.05), and also with therapy duration (P<0.05). CONCLUSIONS: Both HIV infection and antiretroviral therapy demonstrate differential effects on glucose metabolism in HIV-infected children. Targeted prevention of insulin resistance and diabetes mellitus in HIV-infected children and young adults is needed in order to avoid the associated long-term complications that would otherwise occur, given the improvement in life expectancy of HIV-infected individuals.