Structured reporting for fibrosing lung disease: a model shared by radiologist and pulmonologist

Objectives: To apply the Delphi exercise with iterative involvement of radiologists and pulmonologists with the aim of defining a structured reporting template for high-resolution computed tomography (HRCT) of patients with fibrosing lung disease (FLD). Methods: The writing committee selected the HRCT criteria\ue2\u80\u94the Delphi items\ue2\u80\u94for rating from both radiology panelists (RP) and pulmonology panelists (PP). The Delphi items were first rated by RPs as \ue2\u80\u9cessential\ue2\u80\u9d, \ue2\u80\u9coptional\ue2\u80\u9d, or \ue2\u80\u9cnot relevant\ue2\u80\u9d. The items rated \ue2\u80\u9cessential\ue2\u80\u9d by < 80% of the RP were selected for the PP rating. The format of reporting was rated by both RP and PP. Results: A total of 42 RPs and 12 PPs participated to the survey. In both Delphi round 1 and 2, 10/27 (37.7%) items were rated \ue2\u80\u9cessential\ue2\u80\u9d by more than 80% of RP. The remaining 17/27 (63.3%) items were rated by the PP in round 3, with 2/17 items (11.7%) rated \ue2\u80\u9cessential\ue2\u80\u9d by the PP. PP proposed additional items for conclusion domain, which were rated by RPs in the fourth round. Poor consensus was observed for the format of reporting. Conclusions: This study provides a template for structured report of FLD that features essential items as agreed by expert thoracic radiologists and pulmonologists

CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19

Background Lower muscle mass is a known predictor of unfavorable outcome, but its prognostic impact on COVID-19 patients is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in COVID-19 patients. Materials and Methods Clinical/laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed COVID-19, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. Extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation of paravertebral muscles were measured on axial CT images at T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation odds ratios (OR) with 95% confidence intervals (CIs), were used to build four models to predict ICU admission and death, tested and compared using receiver operating characteristic curve (ROC) analysis. Results A total 552 patients (364 men; median age 65 years, interquartile range 54-75) were included. In a CT-based model, lower-than-median T5 paravertebral muscle area showed the highest ORs for ICU admission (OR 4.8, 95% CI 2.7-8.5; P<.001) and death (OR 2.3, 95% CI 1.0-2.9; P=.027). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle area still showed the highest ORs both for ICU admission (OR 4.3; 95% CI 2.5-7.7; P<.001) and death (OR 2.3, 95% CI 1.3-3.7; P=.001). At ROC analysis, the CT-based model and the model including clinical variables showed the same area under the curve (AUC) for ICU admission prediction (AUC 0.83, P=.380) and were not different in predicting death (AUC 0.86 versus AUC 0.87, respectively, P=.282). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT was independently associated with ICU admission and hospital mortality