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This document from the European Society of Thoracic Imaging (ESTI) and the European Society of Radiology (ESR) discusses the role of imaging in the long-term follow-up of COVID-19 patients, to define which patients may benefit from imaging, and what imaging modalities and protocols should be used. Insights into imaging features encountered on computed tomography (CT) scans and potential pitfalls are discussed and possible areas for future review and research are also included. KEY POINTS: • Post-COVID-19 pneumonia changes are mainly consistent with prior organizing pneumonia and are likely to disappear within 12 months of recovery from the acute infection in the majority of patients. • At present, with the longest series of follow-up examinations reported not exceeding 12 months, the development of persistent or progressive fibrosis in at least some individuals cannot yet be excluded. • Residual ground glass opacification may be associated with persisting bronchial dilatation and distortion, and might be termed "fibrotic-like changes" probably consistent with prior organizing pneumonia.

This document from the European Society of Thoracic Imaging (ESTI) and the European Society of Radiology (ESR) discusses the role of imaging in the long-term follow-up of COVID-19 patients, to define which patients may benefit from imaging, and what imaging modalities and protocols should be used. Insights into imaging features encountered on computed tomography (CT) scans and potential pitfalls are discussed and possible areas for future review and research are also included. KEY POINTS: • Post-COVID-19 pneumonia changes are mainly consistent with prior organizing pneumonia and are likely to disappear within 12 months of recovery from the acute infection in the majority of patients. • At present, with the longest series of follow-up examinations reported not exceeding 12 months, the development of persistent or progressive fibrosis in at least some individuals cannot yet be excluded. • Residual ground glass opacification may be associated with persisting bronchial dilatation and distortion, and might be termed "fibrotic-like changes" probably consistent with prior organizing pneumonia. Keywords: COVID-19; Diagnostic imaging; Follow-up; Lung; Multidetector computed tomography

OBJECTIVE: To retrospectively evaluate if texture-based radiomics features are able to detect interstitial lung disease (ILD) and to distinguish between the different disease stages in patients with systemic sclerosis (SSc) in comparison with mere visual analysis of high-resolution computed tomography (HRCT). METHODS: Sixty patients (46 females, median age 56 years) with SSc who underwent HRCT of the thorax were retrospectively analyzed. Visual analysis was performed by two radiologists for the presence of ILD features. Gender, age, and pulmonary function (GAP) stage was calculated from clinical data (gender, age, pulmonary function test). Data augmentation was performed and the balanced dataset was split into a training (70%) and a testing dataset (30%). For selecting variables that allow classification of the GAP stage, single and multiple logistic regression models were fitted and compared by using the Akaike information criterion (AIC). Diagnostic accuracy was evaluated from the area under the curve (AUC) from receiver operating characteristic (ROC) analyses, and diagnostic sensitivity and specificity were calculated. RESULTS: Values for some radiomics features were significantly lower (p < 0.05) and those of other radiomics features were significantly higher (p = 0.001) in patients with GAP2 compared with those in patients with GAP1. The combination of two specific radiomics features in a multivariable model resulted in the lowest AIC of 10.73 with an AUC of 0.96, 84% sensitivity, and 99% specificity. Visual assessment of fibrosis was inferior in predicting individual GAP stages (AUC 0.86; 83% sensitivity; 74% specificity). CONCLUSION: The correlation of radiomics with GAP stage, but not with the visually defined features of ILD-HRCT, implies that radiomics might capture features indicating severity of SSc-ILD on HRCT, which are not recognized by visual analysis. KEY POINTS: Radiomics features can predict GAP stage with a sensitivity of 84% and a specificity of

The origin of biological morphology and form is one of the deepest problems in science, underlying our understanding of development and the functioning of living systems. In 1952, Alan Turing showed that chemical morphogenesis could arise from a linear instability of a spatially uniform state, giving rise to periodic pattern formation in reaction–diffusion systems but only those with a rapidly diffusing inhibitor and a slowly diffusing activator. These conditions are disappointingly hard to achieve in nature, and the role of Turing instabilities in biological pattern formation has been called into question. Recently, the theory was extended to include noisy activator–inhibitor birth and death processes. Surprisingly, this stochastic Turing theory predicts the existence of patterns over a wide range of parameters, in particular with no severe requirement on the ratio of activator–inhibitor diffusion coefficients. To explore whether this mechanism is viable in practice, we have genetically engineered a synthetic bacterial population in which the signaling molecules form a stochastic activator–inhibitor system. The synthetic pattern-forming gene circuit destabilizes an initially homogenous lawn of genetically engineered bacteria, producing disordered patterns with tunable features on a spatial scale much larger than that of a single cell. Spatial correlations of the experimental patterns agree quantitatively with the signature predicted by theory. These results show that Turing-type pattern-forming mechanisms, if driven by stochasticity, can potentially underlie a broad range of biological patterns. These findings provide the groundwork for a unified picture of biological morphogenesis, arising from a combination of stochastic gene expression and dynamical instabilities. Keywords: Turing patterns; biofilm; synthetic biology; signaling molecules; stochastic gene expression, National Science Foundation (U.S.) (Grant CCF-1521925), National Institutes of Health (U.S.) (Grant CCF-1521925), National Science Foundation (U.S.) (Grant CNS-1446474), National Institutes of Health (U.S.) (Grant CNS-1446474)

PURPOSE To build a simple model to teach and validate non-pulsatile and pulsatile flow quantification in ultrasound. MATERIALS AND METHODS The setting consists of the following connected components: (1) medical syringe pump producing an adjustable constant flow (ml/min), (2) modulator modifying constant flow to a reproducible pulsatile flow, (3) water tank containing a diagonal running silicone tube (0.5 mm inner diameter), and (4) a fixated ultrasound probe (L9 Linear Array 9 MHz, GE Logiq E9) measuring the flow inside the tube. Commercially available microbubbles suspended with physiological saline solution were used for ultrasonic visibility. Spectral Doppler of different flow profiles is performed. RESULTS The syringe pump produces an adjustable, constant flow and serves as the reference standard. The filling volume of the tube system is 1.2 ml. Microbubbles are very well detected by ultrasound and can be used as an easy and clean blood mimicking substance. The modulator generates different physiological and pathological flow profiles. Velocities are similar to those found within human blood vessels. Thus, it is possible to train and validate flow measurements in ultrasound. CONCLUSION The model produces non-pulsatile and various pulsatile flow profiles and allows validation of flow measurements. The compact size permits easy and economic setup for flow measurements in research, skills lab and continuing education.