CT quantification of COVID-19 pneumonia extent to predict individualized outcome.

OBJECTIVES:  This study aimed to predict individual COVID-19 patient prognosis at hospital admission using artificial intelligence (AI)-based quantification of computed tomography (CT) pulmonary involvement. BACKGROUND: Assessing patient prognosis in COVID-19 pneumonia is crucial for patient management and hospital and ICU organization. METHODS: We retrospectively analyzed 559 patients with PCR-verified COVID-19 pneumonia referred to the hospital for a severe disease course. We correlated the CT extent of pulmonary involvement with patient outcome. We also attempted to define cut-off values of pulmonary involvement for predicting different outcomes. RESULTS:  CT-based disease extent quantification is an independent predictor of patient morbidity and mortality, with the prognosis being impacted also by age and cardiovascular comorbidities. With the use of explored cut-off values, we divided patients into three groups based on their extent of disease: (1) less than 28 % (sensitivity 65.4 %; specificity 89.1 %), (2) ranging from 28 % (31 %) to 47 % (sensitivity 87.1 %; specificity 62.7 %), and (3) above 47 % (sensitivity 87.1 %; specificity, 62.7 %), representing low risk, risk for oxygen therapy and invasive pulmonary ventilation, and risk of death, respectively. CONCLUSION: CT quantification of pulmonary involvement using AI-based software helps predict COVID-19 patient outcomes (Tab. 4, Fig. 4, Ref. 38).

Posterior vs. anterior circulation infarction: demography, outcomes, and frequency of hemorrhage after thrombolysis.

BACKGROUND: Intravenous thrombolysis is considered to be the standard specific reperfusion therapy in acute ischemic stroke in both anterior and posterior cerebral circulation. AIMS: Our aim was to evaluate the 90-day outcome and rate of intracranial hemorrhage after recombinant tissue plasminogen activator administration in posterior circulation stroke and to compare the intracranial hemorrhage risk for posterior circulation stroke and anterior circulation stroke. METHODS: The set consisted of 877 consecutive acute ischemic stroke patients (777 anterior circulation stroke; 100 posterior circulation stroke) who underwent intravenous thrombolysis with recombinant tissue plasminogen activator in a standard dose of 0·9 mg/kg. The role of following factors was assessed: presenting characteristics, intracranial hemorrhage classification according to ECASS I, mortality, and 90-day clinical outcome assessed using the modified Rankin scale. RESULTS: Good clinical outcomes (modified Rankin scale 0-2) were noted in 59% of posterior circulation stroke patients, with a mortality rate of 19%. Intracerebral hemorrhage was significantly less frequent in posterior circulation stroke than in anterior circulation stroke patients (5·1 vs. 17·2%; P = 0·002). The risk of large hemorrhage (parenchymal hematoma 1 and 2) was 5·2 times higher in anterior circulation stroke patients (P = 0·007). The following additional statistically significant differences were found between posterior circulation stroke and anterior circulation stroke patients: median age, male gender, presence of atrial fibrillation, hyperlipidemia, median time to treatment, and median blood glucose level on admission. CONCLUSIONS: Our study suggests that posterior circulation stroke is associated with a lower risk of intracranial hemorrhage than anterior circulation stroke is.

Quantification of pleural effusion on CT by simple measurement.

AIMS: To find the simplest method for quantifying pleural effusion volume from CT scans. METHODS: Seventy pleural effusions found on chest CT examination in 50 consecutive adult patients with the presence of free pleural effusion were included. The volume of pleural effusion was calculated from a three-dimensional reconstruction of CT scans. Planar measurements were made on CT scans and their two-dimensional reconstructions in the sagittal plane and at three levels on transversal scans. Individual planar measurements were statistically compared with the detected volume of pleural effusion. Regression equations, averaged absolute difference between observed and predicted values and determination coefficients were found for all measurements and their combinations. A tabular expression of the best single planar measurement was created. RESULTS: The most accurate correlation between the volume and a single planar measurement was found in the dimension measured perpendicular to the parietal pleura on transversal scan with the greatest depth of effusion. Conversion of this measurement to the appropriate volume is possible by regression equation: Volume = 0.365 × b(3) - 4.529 × b(2) + 159.723 × b - 88.377. CONCLUSION: We devised a simple method of conversion of a single planar measurement on CT scan to the volume of pleural effusion. The tabular expression of our equation can be easily and effectively used in routine practice.