Comparison of semiquantitative chest CT scoring systems to estimate severity in coronavirus disease 2019 (COVID-19) pneumonia.

OBJECTIVES: To compare the clinical usefulness among three different semiquantitative computed tomography (CT) severity scoring systems for coronavirus disease 2019 (COVID-19) pneumonia. METHODS: Two radiologists independently reviewed chest CT images in 108 patients to rate three CT scoring systems (total CT score [TSS], chest CT score [CCTS], and CT severity score [CTSS]). We made a minor modification to CTSS. Quantitative dense area ratio (QDAR: the ratio of lung involvement to lung parenchyma) was calculated using the U-net model. Clinical severity at admission was classified as severe (n = 14) or mild (n = 94). Interobserver agreement, interpretation time, and degree of correlation with clinical severity as well as QDAR were evaluated. RESULTS: Interobserver agreement was excellent (intraclass correlation coefficient: 0.952-0.970, p < 0.001). Mean interpretation time was significantly longer in CTSS (48.9-80.0 s) than in TSS (25.7-41.7 s, p < 0.001) and CCTS (27.7-39.5 s, p < 0.001). Area under the curve for differentiating clinical severity at admission was 0.855-0.842 in TSS, 0.853-0.850 in CCTS, and 0.853-0.836 in CTSS. All scoring systems correlated with QDAR in the order of CCTS (ρ = 0.443-0.448), TSS (ρ = 0.435-0.437), and CTSS (ρ = 0.415-0.426). CONCLUSIONS: All semiquantitative scoring systems demonstrated substantial diagnostic performance for clinical severity at admission with excellent interobserver agreement. Interpretation time was significantly shorter in TSS and CCTS than in CTSS. The correlation between the scoring system and QDAR was highest in CCTS, followed by TSS and CTSS. CCTS appeared to be the most appropriate CT scoring system for clinical practice. KEY POINTS: • Three semiquantitative scoring systems demonstrate substantial accuracy (area under the curve: 0.836-0.855) for diagnosing clinical severity at admission and (area under the curve: 0.786-0.802) for risk of developing critical illness. • Total CT score (TSS) and chest CT score (CCTS) were considered to be more appropriate in terms of clinical usefulness as compared with CT severity score (CTSS), given the shorter interpretation time in TSS and CCTS, and the lowest correlation with quantitative dense area ratio in CTSS. • CCTS is assumed to distinguish subtle from mild lung involvement better than TSS by adopting a 5% threshold in scoring the degree of severity.

Development of intravascular large B-cell lymphoma during prophylactic antibiotic treatment for anti-interferon-gamma autoantibody syndrome: A case report.

Anti-interferon (IFN)-γ autoantibody-positive syndrome is one of the acquired non-HIV cellular immunodeficiencies, caused by abnormalities in the IFN-γ/interleukin (IL)-12 pathways. It is often diagnosed alongside the onset of disseminated mycobacterium infection, and requires continuous antimycobacterial chemotherapy; however, the detailed pathological mechanisms underlying this syndrome, including its prognosis, are not known. To the best of our knowledge, this is the first reported case of intravascular large B-cell lymphoma complicated by anti-IFN-γ autoantibody syndrome, presented in an 82-year-old woman. The patient had been diagnosed with anti-IFN-γ autoantibody immunodeficiency ten years ago. She had repeated subacute fever of undetermined origin for 13 months that made us suspect infections, such as disseminated mycobacterium disease and other viral and fungal infections, despite receiving prophylactic antimycobacterial chemotherapy with rifampicin and clarithromycin. However, all the screenings performed showed no evidence of infectious diseases; thus, she was finally diagnosed with intravascular large B-cell lymphoma via a random skin biopsy. Unfortunately, the patient debilitated rapidly and died. Evidence supporting a correlation between anti-IFN-γ autoantibody syndrome and carcinogenesis is still lacking, although it is known that patients with anti-IFN-γ autoantibody syndrome are at risk of persistent viral infection-related and T-cell lineage-related carcinogenesis. This case demonstrated that patients with anti-IFN-γ autoantibody syndrome are also at risk of developing B-cell lymphoma, such as intravascular lymphoma. This emphasizes that caution should be paid to increased risk of developing malignancy during the long-term management of anti-IFN-γ autoantibody syndrome with cellular immunodeficiency.

Severe Atelectasis due to Aspirated Valproic Acid Tablet.

A 60-year-old man treated with valproic acid (VPA) for epilepsy developed atelectasis and respiratory failure after an accidentally aspirated VPA tablet-induced mucus hypersecretion. Following bronchoscopic removal of the aspirated tablet, his respiratory status improved and massive sputum production did not recur. We hypothesized that the aspirated VPA tablet increased the expression of mucin-related genes, thereby increasing mucus production. Our in vitro experiments using a human respiratory epithelial cell line revealed that VPA directly upregulates the airway mucin-related genes. We believe that this is the first case report of aspirated VPA-induced severe atelectasis and respiratory failure, which were successfully treated with the bronchoscopic removal of the VPA tablet.

Successful Treatment of Granulomatous-lymphocytic Interstitial Lung Disease in a Patient with CTLA-4 Deficiency.

Common variable immunodeficiency (CVID) causes granulomatous-lymphocytic interstitial lung disease (GLILD) and has a poor prognosis. We herein report a case of GLILD in a 49-year-old woman with CTLA-4 deficiency-associated CVID. The patient presented with dyspnea that had worsened over the past two years. A laboratory examination revealed hypoglobulinemia and pancytopenia. Chest computed tomography showed diffuse infiltrative and granular shadows in the bilateral interstitium. A flow cytometric analysis of blood cells and genetic testing confirmed CTLA-4 deficiency. We performed video-assisted thoracoscopic surgery for the pathological diagnosis of GLILD and to exclude infection and malignancy. Corticosteroid treatment successfully improved the condition of the patient.

Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph.

The purpose of the present study was to evaluate the feasibility of applying the advanced lung cancer inflammation index (ALI) in patients with coronavirus disease 2019 (COVID-19) and to establish a combined ALI and radiologic risk prediction model for disease exacerbation. The present study included patients diagnosed with COVID-19 infection in our single institution from March to October 2020. Patients without clinical information and/or chest computed tomography (CT) upon admission were excluded. A radiologist assessed the CT severity score and abnormality on chest radiograph. The combined ALI and radiologic risk prediction model was developed via random forest classification. Among 79 patients (age, 43±19 years; male/female, 45:34), 72 experienced improvement and seven patients experienced exacerbation after admission. Significant differences were observed between the improved and exacerbated groups in the ALI (median, 47.6 vs. 13.2; P=0.011), frequency of chest radiograph abnormality (24.7 vs. 83.3%; P<0.001), and chest CT score (CCTS; median, 1 vs. 9; P<0.001). For the accuracy of predicting exacerbation, the receiver-operating characteristic curve analysis demonstrated an area under the curve of 0.79 and 0.92 for the ALI and CCTS, respectively. The combined ALI and radiologic risk prediction model had a sensitivity of 1.00 and a specificity of 0.81. Overall, ALI alone and CCTS alone modestly predicted the exacerbation of COVID-19, and the combined ALI and radiologic risk prediction model exhibited decent sensitivity and specificity.