Diagnostic performance and inter-observer variability of CO-RADS in the triage of patients with suspected COVID-19 infection: initial experience in Zagazig University Hospital.

Purpose: In many healthcare settings in developing nations, multislice computed tomography (MSCT) imaging may be the only available diagnostic modality for patients with suspected COVID-19 infection, due to a shortage of laboratory kits. This study aimed to evaluate the diagnostic performance and interobserver variability of CO-RADS (COVID-19 Reporting and Data System) in the triage of patients with suspected COVID-19 infection in Zagazig University Hospital. Material and methods: This study included 2500 patients with suspected COVID-19 infection, mean age 60.61 years ± 13.89. 61.4% were male. Unstable patients requiring urgent invasive ventilation, acute coronary syndrome patients, pregnant females, and patients with RT-PCR results available prior to MSCT were excluded from this study. RT-PCR was performed in all patients included in the study. Results: Fever and dry cough were the most common clinical symptoms, detected in 80.16% and 52.00%, respectively. The most common comorbidities were cardiovascular diseases, followed by chronic lung disease and diabetes, found in 27.36%, 22.80%, and 18.00%, respectively. Of the 1500 RT-PCR-positive patients, 40% had CO-RADS score 5, while 3.4% had CO-RADS score 1. Of the 1000 RT-PCR-negative patients, 36% had CO-RADS score 2 and 1% were scored as CO-RADS 5. There was excellent agreement in the studied patients as the weighted κ value was 0.846, which was more pronounced at CO-RADS 5 (24.40%). The sensitivity of CO-RADS was higher in the 2nd scenario (83.27% vs. 55.27%) while the specificity was higher in the 1st scenario (95% vs. 65%). Conclusion: The CO-RADS scoring system is a sensitive and specific method that can help in the diagnosis of COVID-19 during the peak of the COVID-19 pandemic. CO-RADS is a triage test in resource-constrained environments, assisting in the optimization of RT-PCR tests, isolation beds, and intensive care units.

Efficacy of contrast-enhanced FDG PET/CT in patients awaiting liver transplantation with rising alpha-fetoprotein after bridge therapy of hepatocellular carcinoma.

OBJECTIVE: To assess the diagnostic accuracy and illustrate positive findings of contrast-enhanced fluorine-18 fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) image in patients awaiting liver transplantation (LT) with rising alpha-fetoprotein (AFP) after bridge therapy of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This prospective study included 100 patients who were waiting for LT and who previously underwent locoregional therapy (LRT) of HCC. These patients had rising AFP levels on a routine follow-up examination awaiting LT. All patients underwent a contrast-enhanced 18F-FDG PET/CT examination. We calculated for each patient the maximum standardised uptake value (SUVmax) of the tumour and the ratio of the tumoral SUVmax to the normal-liver SUVmax. The diagnostic accuracy and positive contrast-enhanced findings of 18F-FDG PET/CT were established by histopathology and clinical and imaging follow-up as the reference standards. RESULTS: Contrast-enhanced 18F-FDG PET/CT detected tumour relapse in 78 patients (13 patients had intrahepatic lesions, 10 patients had extrahepatic metastases and 55 patients with combined lesions). The sensitivity, specificity and accuracy values of contrast-enhanced 18F-FDG PET/CT examination in the detection of HCC recurrence were 92.8%, 94.1% and 93%, respectively. A significant correlation was found between the AFP level and SUVmax ratio (r = 0.2283; p = 0.0224). The best threshold for 18F-FDG PET positivity was >1.21. CONCLUSION: Contrast-enhanced 18F-FDG PET/CT is a valuable tool for the detection of intrahepatic HCC recurrence or extrahepatic metastasis following rising AFP levels after LRT of HCC, and should be incorporated during routine workup awaiting LT. KEY POINTS: • 18F-FDG PET/CT is a valuable tool for the detection of HCC recurrence • 18 F-FDG PET/CT should be incorporated during routine workup awaiting liver transplantation • Significant correlation was found between AFP level and SUVmax ratio • The best threshold for 18 F-FDG PET positivity was >1.21 • The ideal cut-off value for AFP was >202.

Does a combined CT and MRI protocol enhance the diagnostic efficacy of LI-RADS in the categorization of hepatic observations? A prospective comparative study.

OBJECTIVE: To compare diagnostic performance and agreement between CT, MRI and combined CT/MRI in reference to LI-RADS classification system to categorize hepatic observations detected in hepatic patients during screening ultrasound. METHODS: 240 patients with 296 liver observations detected during ultrasound surveillance underwent hepatic CT and MRI examinations, histopathology, and clinical and radiological follow-up. Using LI-RADS v2014, six radiologists evaluated the observations independently and assigned a LI-RADS category to each observation using CT, MRI and combined CT/MRI. RESULTS: Combined CT and MRI in LI-RADS yielded better accuracy (91.29 %), sensitivity (90.71 %) and specificity (92.31 %) for hepatocellular carcinoma (HCC) diagnosis than using MRI or CT alone; accuracy, sensitivity and specificity decreased to 85.37 %, 86.34 %, and 83.65 %, respectively, for MRI and 67.6 %, 54.10 % and 91.35 %, respectively, for CT. The intraclass agreement of the LI-RADS scores between CT, MRI and combined CT/MRI was excellent (κ=0.9624 (95 % CI: 0.9318-0.9806)). CONCLUSION: CT and MRI are complementary to each other. Combined CT/MRI enabled a more precise determination of LI-RADS category of hepatic observations; however, due to the expense and minor increase in accuracy, the combined methodology should only be utilized in cases of suspected HCC. KEY POINTS: • Hepatic observation may be categorized differently depending on the imaging modality used. • We compared LI-RADS categorization between CT, MRI and combined CT/MRI. • MRI produces higher accuracy and sensitivity, while CT produces higher specificity. • Combining CT and MRI improves LIRADS categorization reports. • Considering additional cost, combined methodology could be restricted to challenging cases.