Fatal Cerebral Venous Thrombosis in a Pregnant Woman with Inherited Antithrombin Deficiency after BNT162b2 mRNA COVID-19 Vaccination.

Antithrombin deficiency is a high-risk factor for venous thromboembolism during pregnancy, whereas cerebral venous thrombosis is rare. Cerebral venous thrombosis related to coronavirus disease 2019 (COVID-19) vaccines has been reported; however, there are a few reports of cerebral venous thrombosis after a messenger RNA (mRNA) vaccination. A 25-year-old female in her sixth week of pregnancy presented with headache 24 days after BNT162b2 mRNA COVID-19 vaccination. The following day, she presented with altered sensorium and was diagnosed with severe cerebral venous thrombosis. She demonstrated heparin resistance and was found to have an inherited antithrombin deficiency. A heterozygous missense variant in SERPINC1 (c.379T>C, p.Cys127Arg, 'AT Morioka') was detected by DNA analysis. Despite intensive care with unfractionated heparin, antithrombin concentrate, and repeated endovascular treatments, she died on the sixth day of hospitalization. Cerebral venous thrombosis in pregnant women with an antithrombin deficiency can follow a rapid and fatal course. Treatment with unfractionated heparin and antithrombin concentrate may be ineffective in severe cerebral venous thrombosis cases with antithrombin deficiency. Early recognition of antithrombin deficiency and an immediate switch to other anticoagulants may be required. Although the association between cerebral venous thrombosis and the vaccine is uncertain, COVID-19 vaccinations may require careful evaluation for patients with prothrombic factors.

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.

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.

Frequency and Characteristics of Nodal and Deltoid FDG and 11C-Choline Uptake on PET Performed After COVID-19 Vaccination.

BACKGROUND. COVID-19 vaccination may trigger reactive lymphadenopathy, confounding imaging interpretation. There has been limited systematic analysis of PET findings after COVID-19 vaccination. OBJECTIVE. The purpose of this study was to evaluate the frequency and characteristics of abnormal FDG and 11C-choline uptake on PET performed after COVID-19 vaccination. METHODS. This retrospective study included 67 patients (43 men and 24 women; mean [± SD] age, 75.6 ± 9.2 years) who underwent PET examination between December 14, 2020, and March 10, 2021, after COVID-19 vaccination and who had undergone prevaccination PET examination without visible axillary node uptake. A total of 52 patients received the BNT162b2 mRNA COVID-19 vaccine (Pfizer-BioNTech; hereafter referred to as the Pfizer-BioNTech vaccine), and 15 received the SARS-CoV-2 mRNA-1273 vaccine (Moderna; hereafter referred to as the Moderna vaccine). Sixty-six of the patients underwent PET/CT, and one underwent PET/MRI. Fifty-four PET examinations used FDG, and 13 used 11C-choline. PET was performed a median of 13 and 10 days after vaccination for patients who had received one (n = 44) and two (n = 23) vaccine doses, respectively. Two nuclear medicine physicians independently reviewed images and were blinded to injection laterality and the number of days since vaccination. Lymph node or deltoid SUVmax greater than the blood pool SUVmax was considered positive. Interreader agreement was assessed, and the measurements made by the more experienced physician were used for subsequent analysis. RESULTS. Positive axillary lymph node uptake was observed in 10.4% (7/67) of patients (7.4% [4/54] of FDG examinations and 23.1% [3/13] of 11C-choline examinations); of the patients with positive axillary lymph nodes, four had received the Pfizer vaccine, and three had received the Moderna vaccine. Injection laterality was documented for five of seven patients with positive axillary lymph nodes and was ipsilateral to the positive node in all five patients. PET was performed within 24 days of vaccination for all patients with a positive node. One patient showed extraaxillary lymph node uptake (ipsilateral supraclavicular uptake on FDG PET). Ipsilateral deltoid uptake was present in 14.5% (8/55) of patients with documented injection laterality, including 42.9% (3/7) of patients with positive axillary lymph nodes. Interreader agreement for SUV measurements (expressed as intraclass correlation coefficients) ranged from 0.600 to 0.988. CONCLUSION. Increased axillary lymph node or ipsilateral deltoid uptake is occasionally observed on FDG or 11C-choline PET performed after COVID-19 vaccination with the Pfizer-BioNTech or Moderna vaccine. CLINICAL IMPACT. Interpreting physicians should recognize characteristics of abnormal uptake on PET after COVID-19 vaccination to guide optimal follow-up management and reduce unnecessary biopsies.