Objective. Breast cancer is the most common cancer type among women worldwide. Today, health consumers search the Internet to gain health information about many diseases including breast cancer. YouTube™ is the second most commonly used website on the Internet. However, the quality and accuracy of health-related YouTube™ videos are controversial. The objective of this study was to investigate the quality and accuracy of breast cancer-related videos on YouTube™. Material and Methods. “Breast cancer” keyword was entered into YouTube™ search bar, and after excluding advertisement, duplicate, and non-English videos, the first most viewed 50 videos were analyzed. Videos’ length, the number of views, comments, likes, and dislikes were recorded. DISCERN and JAMA scores and Video Power Index (VPI) values of the videos were calculated. All videos were evaluated by two independent radiologists experienced on breast cancer. The correlation between the two observers was also analyzed. Results. Of all videos, 14% were uploaded by physicians, 26% by health channels, 20% by patients, 10% by news channels, 2% by herbalists, 2% by blog channels, and 2% by nonprofit activism channels. The mean DISCERN score was calculated as 26.70±10.99 and the mean JAMA score as 2.23±0.97. The mean VPI value, which was calculated to determine the popularity of the videos, was found as 94.10±4.48. A strong statistically significant correlation was found between the two observers in terms of both DISCERN and JAMA scores. There was an excellent agreement between the two observers. Conclusion. The overall quality of the viewed videos was found as poor. Healthcare professionals should be encouraged to upload breast cancer-related videos with accurate information to promote patients for screening and direct them appropriately.
Coronaviruses (CoV) belong to the coronavirus genus of the coronaviridae family. All CoVs are pleomorphic RNA viruses containing crown-like peplomers of 80-160 nm in size. This virus is a zoonotic pathogen seen with a wide range of clinical features from asymptomatic state to intensive care in humans. So far, seven human coronaviruses have been identified with the last one being Coronavirus-2019 (COVID-19). These pathogens typically lead to mild disease, but SARS and MERS type coronaviruses have caused severe respiratory disease and even mortality within the last 20 years. COVID-19 virus has rapidly spread worldwide after China and is continuing to cause huge economical and social impacts. Given the scarcity of resources including healthcare staff, hospital capacities, test kits, etc., timely diagnosis and treatment of this virus are of paramount importance. However, there is no vaccination or drug developed for the treatment of this disease up to today. Because the spreading rate of the virus is very high worldwide and there is no definitive treatment, diagnosis becomes even more important. The objective of this review is to evaluate the use of chest computed tomography, one of the commonly used radiologic imaging modalities, in the diagnosis of COVID-19 in light with the current literatüre.
ObjectiveToday, a biopsy is the gold standard in the diagnosis of non-alcoholic fatty liver. However, a biopsy is an invasive technique, limited to the sample taken, and it may lead to misdiagnosis. Therefore, novel noninvasive options are needed. The objective of this study was to investigate the accuracy of magnetic resonance (MR) Dixon sequence and elastography using magnetic resonance spectroscopy (MRS) as a reference in the quantification of hepatic steatosis. MethodsA total of 60 patients were included in the study. All patients underwent magnetic resonance imaging (MRI), MRS, and elastography in order to quantify hepatosteatosis. MRI and MRS imaging studies were performed using MR Dixon and high-speed T2-corrected multiple-echo 1H-MRS sequence (HISTO) sequences, respectively, in order to calculate proton density fat fraction (PDFF) values. ResultsThe mean MRI-PDFF value with the MRS region of interest (ROI) was found as 9.4% ± 12.1%. The mean MRS-PDFF was found as 8.9% ± 11.3%. No statistically significant difference was found between MRS-PDFF and MRI-PDFF values measured in ROI (p < 0.005). The correlation between MRS-PDFF and MRI-PDFF was examined with Spearman's correlation analysis. Accordingly, there was an excellent correlation between MRS and MRI values measured in ROI (r ≥ 0.8, p < 0.001). Sensitivity, specificity, positive predictive value, and negative predictive value were calculated as 96%, 100%, 89.5%, and 92.6%, respectively, for MRI-PDFF in predicting hepatic steatosis for the same ROI localization with MRS. The optimum cut-off value of MRS-PDFF in predicting hepatic steatosis was found as 5.3% using the same ROI localization with MRS. ConclusionThe results of this study indicated an excellent correlation between MRI-PDFF and MRS-PDFF. The multi-echo Dixon MRI technique seems a promising alternative method in the detection of non-alcoholic fatty liver disease.
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