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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 article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does "trustworthy AI" mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic.

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: Assessment of scoliotic curve flexibility and stiffness is essential for planning surgical treatment in adolescent idiopathic scoliosis (AIS). Measurement of curve flexibility is currently insufficiently precise. The purpose of this study was to introduce and validate a novel method of superimposing radiographs for more reliable measurement of curve flexibility. Material and methods: Two independent radiologists measured Cobb angles separately on standard anterior-posterior (AP) (n = 48) and supine bending radiographs (n = 48), in patients with AIS, who were randomly included from a surgical database. The same readers repeated the measurements after the bending radiographs were semi-automatically superimposed on the AP radiographs by fusing the caudad end vertebra. Curve flexibility was calculated. Inter-reader agreement between the two independent readers was calculated using interclass correlation coefficient (ICC). Results: A moderate inter-reader agreement was achieved in the upper curve (ICC = 0.57) and a good agreement in the lower curve (ICC = 0.72) with the standard method of assessing curve flexibility. With the use of the semiautomatic superimposition, however, almost perfect agreement was achieved for both the upper and the lower curves flexibilities (ICC = 0.93 and 0.97, respectively). Conclusion: The introduced semi-automatic superimposition technique for measurement of scoliotic curve flexibility in AIS is more precise and reliable than the current standard method. Key Points : • A technique using semiautomatic superimposition of anterior-posterior and bending radiographs is introduced • Almost perfect agreement was achieved for scoliotic curves flexibilities measurements • This method is more precise and reliable than the current standard method

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

Contains fulltext : 229597.pdf (publisher's version ) (Open Access), Background: Improved imaging techniques have increased the incidence of subsegmental pulmonary embolism (ssPE). Indirect evidence is suggesting that ssPE may represent a more benign presentation of venous thromboembolism not necessarily requiring anticoagulant treatment. However, correctly diagnosing ssPE is challenging with reported low interobserver agreement, partly due to the lack of widely accepted diagnostic criteria. Objectives: We sought to derive uniform diagnostic criteria for ssPE, guided by expert consensus. Methods: Based on an extensive literature review and expert opinion of a Delphi steering committee, two surveys including statements regarding diagnostic criteria and management options for ssPE were established. These surveys were conducted electronically among two panels, respectively: expert thoracic radiologists and clinical venous thromboembolism specialists. The Delphi method was used to achieve consensus after multiple survey rounds. Consensus was defined as a level of agreement >70%. Results: Twenty-nine of 40 invited radiologists (73%) and 40 of 51 clinicians (78%) participated. Following two survey rounds by the expert radiologists, consensus was achieved on 15 of 16 statements, including on the established diagnostic criteria for ssPE (96% agreement): a contrast defect in a subsegmental artery, that is, the first arterial branch division of any segmental artery independent of artery diameter, visible in at least two subsequent axial slices, using a computed tomography scanner with a desired maximum collimator width of

BACKGROUND: Careful selection of malignant pleural mesothelioma (MPM) patients for curative treatment is of highest importance, as the multimodal treatment regimen is challenging for patients and harbors a high risk of substantial toxicity. Radiomics-a quantitative method for image analysis-has shown its prognostic ability in different tumor entities and could therefore play an important role in optimizing patient selection for radical cancer treatment. So far, radiomics as a prognostic tool in MPM was not investigated. MATERIALS AND METHODS: This study is based on 72 MPM patients treated with surgery in a curative intent at our institution between 2009 and 2017. Pre-treatment Fluorine-18 fluorodeoxyglucose (FDG) PET and CT scans were used for radiomics outcome modeling. After extraction of 1404 CT and 1410 FDG PET features from each image, a preselection by principal component analysis was performed to include only robust, non-redundant features for the cox regression to predict the progression-free survival (PFS) and the overall survival (OS). Results were validated on a separate cohort. Additionally, SUVmax and SUVmean, and volume were tested for their prognostic ability for PFS and OS. RESULTS: For the PFS a concordance index (c-index) of 0.67 (95% CI 0.52-0.82) and 0.66 (95% CI 0.57-0.78) for the training cohort (n = 36) and internal validation cohort (n = 36), respectively, were obtained for the PET radiomics model. The PFS advantage of the low-risk group translated also into an OS advantage. On CT images, no radiomics model could be trained. SUV max and SUV mean were also not prognostic in terms of PFS and OS. CONCLUSION: We were able to build a successful FDG PET radiomics model for the prediction of PFS in MPM. Radiomics could serve as a tool to aid clinical decision support systems for treatment of MPM in future.

Zusammenfassung: Viele Chemotherapeutika wirken direkt oder indirekt toxisch auf die Lunge und Atemwege. Dies kann zu potenziell tödlichen Nebenwirkungen führen. Die diagnostische Herausforderung liegt darin, die Veränderungen in der Bildgebung als solche frühzeitig zu erkennen, da sie oft unspezifisch sind. Zudem können sie mit pulmonaler Stauung, Infektionen, Strahlungspneumonitis oder einer primären Grunderkrankung verwechselt werden. In diesem Übersichtsartikel werden die morphologischen Veränderungen im Bereich der Lunge und der Atemwege, eingeteilt nach anatomischer Lokalisation, dargestellt und einige häufig verwendete Chemotherapeutika und ihre Nebenwirkungen aufgeführt.