Purpose:The development of computer-aided diagnostic ͑CAD͒ methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography ͑CT͒ scans. The Lung Image Database Consortium ͑LIDC͒ and Image Database Resource Initiative ͑IDRI͒ completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute ͑NCI͒, further advanced by the Foundation for the National Institutes of Health ͑FNIH͒, and accompanied by the Food and Drug Administration ͑FDA͒ through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ͑"noduleՆ 3 mm," "noduleϽ 3 mm," and "non-noduleՆ 3 mm"͒. In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results:The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "noduleՆ 3 mm" by at least one radiologist, of which 928 ͑34.7%͒ received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions:The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

The goal of this study is to explore predictors of COVID-19 vaccine hesitancy, including socio-demographic factors, comorbidity, risk perception, and experience of discrimination, in a sample of the U.S. population. We used a cross-sectional online survey study design, implemented between 13–23 December 2020. The survey was limited to respondents residing in the USA, belonging to priority groups for vaccine distribution. Responses were received from 2650 individuals (response rate 84%) from all 50 states and Puerto Rico, American Samoa, and Guam. The five most represented states were California (13%), New York (10%), Texas (7%), Florida (6%), and Pennsylvania (4%). The majority of respondents were in the age category 25–44 years (66%), male (53%), and working in the healthcare sector (61%). Most were White and non-Hispanic (66%), followed by Black and non-Hispanic (14%) and Hispanic (8%) respondents. Experience with racial discrimination was a predictor of vaccine hesitancy. Those reporting racial discrimination had 21% increased odds of being at a higher level of hesitancy compared to those who did not report such experience (OR = 1.21, 95% C.I. 1.01–1.45). Communication and logistical aspects during the COVID-19 vaccination campaign need to be sensitive to individuals’ past-experience of racial discrimination in order to increase vaccine coverage.

Use of local bone graft alone achieved a similar fusion rate in single-level fusion but a much smaller fusion rate in multilevel fusion compared with the ICBG group. Local bone graft alone achieved a similar clinical outcome but less morbidity irrespective of number of fusion level.

Hesitancy towards the COVID-19 vaccine remains high among the US population. Now that the vaccine is available to priority populations, it is critical to convince those that are hesitant to take the vaccine. Public health communication about the vaccine as well as misinformation on the vaccine occurs through a variety of different information channels. Some channels of information are more commonly found to spread misinformation. Given the expansive information environment, we sought to characterize the use of different media channels for COVID-19 vaccine information and determine the relationship between information channel and vaccine acceptance. We used quota sampling of vaccine priority groups [N = 2,650] between December 13 and 23, 2020 and conducted bivariate chi-squared tests and multivariable multinomial logistic regression analyses to determine the relative impact of channels of information on vaccine acceptance. We found traditional channels of information, especially National TV, National newspapers, and local newspapers increased the likelihood of vaccine acceptance. Individuals who received information from traditional media compared to social media or both traditional and social media were most likely to accept the vaccine. The implications of this study suggest social media channels have a role to play in educating the hesitant to accept the vaccine, while traditional media channels should continue to promote data-driven and informed vaccine content to their viewers.

Vaccine hesitancy (delay in obtaining a vaccine, despite availability) represents a significant hurdle to managing the COVID-19 pandemic. Vaccine hesitancy is in part related to the prevalence of anti-vaccine misinformation and disinformation, which are spread through social media and user-generated content platforms. This study uses qualitative coding methodology to identify salient narratives and rhetorical styles common to anti-vaccine and COVID-denialist media. It organizes these narratives and rhetorics according to theme, imagined antagonist, and frequency. Most frequent were narratives centered on “corrupt elites” and rhetorics appealing to the vulnerability of children. The identification of these narratives and rhetorics may assist in developing effective public health messaging campaigns, since narrative and emotion have demonstrated persuasive effectiveness in other public health communication settings.