SummaryBackgroundThis study is an outcome evaluation of the Drug-Eluting-Bead-Chemoembolization (DEB TACE) compared to conventional TACE (cTACE) with Cisplation and Lipiodol in patients with hepatocellular carcinoma (HCC) and Child-Pugh A Cirrhosis.Material/MethodsA comparison of interventional therapy with either cTACE or DEB-TACE of 22 patients each with unresectable HCC and Child-Pugh A Cirrhosis was carried out. A comparison of therapy-associated complications, tumour response rates and mean survival was performed. Tumour response was evaluated in accordance with the European Association for the Study of the Liver (EASL) response criteria by two radiologists in consensus reading.ResultsThe choice of TACE procedure (DEB TACE/cTACE) had no significant impact on therapy-associated complications. Objective Response (OR, complete response + partial response) for DEB-TACE was 22.7%; a further 68.2% was stable disease (SD). The respective response rates for the cTACE were OR 22.7 and SD 31.8%. Thus disease control was not significantly increased for DEB TACE (p=0.066). After DEB-TACE mean survival was significantly prolonged with 651±76 days vs. 414±43 days for cTACE (p=0.01).ConclusionsAssociated with a similar safety profile and an at least comparable tumour response, the DEB-TACE is a method of treatment for HCC that has the potential to improve mean survival compared to cTACE with Cisplatin/Lipiodol.

Background and objectives: The course of SARS-CoV-2 (COVID-19) is still under analysis. The majority of complications arising from the infection are related to the respiratory system. The adverse effect of the viral infection on bone and joint tissue has also been observed. Materials and Methods: We present a group of 10 patients with degeneration of large joints and adjacent epiphyses of long bones and the spine, with a background of bone infarctions and avascular necrosis (AVN) immediately after infection with the COVID-19 virus. In MR imaging, changes in the characteristics of AVN were documented. Results: Observation of this group showed a clear correlation among the history of COVID-19 disease in the patients, moderately severe symptoms, high levels of IgG antibodies, and the time of occurrence of joint changes. No other clinically significant complications were observed following COVID-19 infection in the study group. No other risk factors for AVN or autoimmune or degenerative diseases were found in the study group. The group of patients responded well to empirical treatment with steroids, which normalized acute inflammatory symptoms and pain in the joints. Conclusions: During coronavirus (COVID-19) infection, there are complications in the locomotor system, such as microembolism and the formation of AVN; hence, more research is needed.

Objectives: The aim of this study was to compare a diagnosis support system to detect COVID-19 pneumonia on chest radiographs (CXRs) against radiologists of various levels of expertise in chest imaging. Materials and Methods: Five publicly available databases comprising normal CXR, confirmed COVID-19 pneumonia cases, and other pneumonias were used. After the harmonization of the data, the training set included 7966 normal cases, 5451 with other pneumonia, and 258 CXRs with COVID-19 pneumonia, whereas in the testing data set, each category was represented by 100 cases. Eleven blinded radiologists with various levels of expertise independently read the testing data set. The data were analyzed separately with the newly proposed artificial intelligencebased system and by consultant radiologists and residents, with respect to positive predictive value (PPV), sensitivity, and F-score (harmonic mean for PPVand sensitivity). The χ 2 test was used to compare the sensitivity, specificity, accuracy, PPV, and F-scores of the readers and the system. Results: The proposed system achieved higher overall diagnostic accuracy (94.3%) than the radiologists (61.4% ± 5.3%). The radiologists reached average sensitivities for normal CXR, other type of pneumonia, and COVID-19 pneumonia of 85.0% ± 12.8%, 60.1% ± 12.2%, and 53.2% ± 11.2%, respectively, which were significantly lower than the results achieved by the algorithm (98.0%, 88.0%, and 97.0%; P < 0.00032). The mean PPVs for all 11 radiologists for the 3 categories were 82.4%, 59.0%, and 59.0% for the healthy, other pneumonia, and COVID-19 pneumonia, respectively, resulting in an F-score of 65.5% ± 12.4%, which was significantly lower than the F-score of the algorithm (94.3% ± 2.0%, P < 0.00001). When other pneumonia and COVID-19 pneumonia cases were pooled, the proposed system reached an accuracy of 95.7% for any pathology and the radiologists, 88.8%. The overall accuracy of consultants did not vary significantly compared with residents (65.0% ± 5.8% vs 67.4% ± 4.2%); however, consultants detected significantly more COVID-19 pneumonia cases (P = 0.008) and less healthy cases (P < 0.00001). Conclusions: The system showed robust accuracy for COVID-19 pneumonia detection on CXR and surpassed radiologists at various training levels.

• Inclusion of CSI in abdominal MRI protocols provides an effective solution for classifying adrenal masses discovered on MR exams • Visual evaluation of adrenal CSI is sufficient; use of quantitative indices does not improve diagnostic accuracy.