Radiomics-based machine learning differentiates "ground-glass" opacities due to COVID-19 from acute non-COVID-19 lung disease.

Ground-glass opacities (GGOs) are a non-specific high-resolution computed tomography (HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia. However, GGOs are also seen in other acute lung diseases, thus making challenging the differential diagnosis. To this aim, we investigated the performance of a radiomics-based machine learning method to discriminate GGOs due to COVID-19 from those due to other acute lung diseases. Two sets of patients were included: a first set of 28 patients (COVID) diagnosed with COVID-19 infection confirmed by real-time polymerase chain reaction (RT-PCR) between March and April 2020 having (a) baseline HRCT at hospital admission and (b) predominant GGOs pattern on HRCT; a second set of 30 patients (nCOVID) showing (a) predominant GGOs pattern on HRCT performed between August 2019 and April 2020 and (b) availability of final diagnosis. Two readers independently segmented GGOs on HRCTs using a semi-automated approach, and radiomics features were extracted using a standard open source software (PyRadiomics). Partial least square (PLS) regression was used as the multivariate machine-learning algorithm. A leave-one-out nested cross-validation was implemented. PLS ß-weights of radiomics features, including the 5% features with the largest ß-weights in magnitude (top 5%), were obtained. The diagnostic performance of the radiomics model was assessed through receiver operating characteristic (ROC) analysis. The Youden's test assessed sensitivity and specificity of the classification. A null hypothesis probability threshold of 5% was chosen (p < 0.05). The predictive model delivered an AUC of 0.868 (Youden's index = 0.68, sensitivity = 93%, specificity 75%, p = 4.2 × 10-7). Of the seven features included in the top 5% features, five were texture-related. A radiomics-based machine learning signature showed the potential to accurately differentiate GGOs due to COVID-19 pneumonia from those due to other acute lung diseases. Most of the discriminant radiomics features were texture-related. This approach may assist clinician to adopt the appropriate management early, while improving the triage of patients.

Coronavirus disease 2019 (COVID-19) in the heart transplant population: a single-centre experience.

OBJECTIVES: Few anecdotal cases have been reported in the literature regarding heart transplant recipients and infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We report our experience with 6 patients hospitalized in Northern Italy during the outbreak. METHODS: Of the 396 living heart transplant recipients from 1985 to 2020 included in the study, 6 patients developed the novel 2019 coronavirus disease. Risk factors, last follow-up characteristics, onset presentation, in-hospital course of disease and blood examinations data were collected for these patients. RESULTS: All patients were symptomatic and had positive results from a nasopharyngeal swab test for SARS-CoV-2. Of the 6 patients, 5 were hospitalized and 1 remained self-quarantined at home. Two patients died and 3 were discharged home. Two patients were admittted to the intensive care unit . Immunosuppressive therapy was modified with a median reduction comprising doses that were 50% cyclosporine and 50% mycophenolate. All patients received a medium-dose of corticosteroids as a bolus medication in addition to their therapy. All hospitalized patients received hydroxychloroquine; 2 patients received ritonavir/lopinavir. Broad-spectrum antibiotics for prophylaxis were administered to all. One patient had an ischaemic stroke and died of sepsis. CONCLUSIONS: In the absence of any strong evidence regarding the treatment of heart transplant recipients infected with SARS-CoV-2, we faced a new challenge in managing viral infection in an immunosuppressed population. Because immunomodulation interaction with the infection seems to be crucial for developing severe forms of the disease, we managed to reduce immunosuppressive therapy by adding medium doses of corticosteroids. Despite the limited number of affected patients, this report suggests that special considerations should be given to treating coronavirus disease in the heart transplant recipient population.