Objectives Radiologists’ perception is likely to influence the adoption of artificial intelligence (AI) into clinical practice. We investigated knowledge and attitude towards AI by radiologists and residents in Europe and beyond. Methods Between April and July 2019, a survey on fear of replacement, knowledge, and attitude towards AI was accessible to radiologists and residents. The survey was distributed through several radiological societies, author networks, and social media. Independent predictors of fear of replacement and a positive attitude towards AI were assessed using multivariable logistic regression. Results The survey was completed by 1,041 respondents from 54 mostly European countries. Most respondents were male (n = 670, 65%), median age was 38 (24–74) years, n = 142 (35%) residents, and n = 471 (45%) worked in an academic center. Basic AI-specific knowledge was associated with fear (adjusted OR 1.56, 95% CI 1.10–2.21, p = 0.01), while intermediate AI-specific knowledge (adjusted OR 0.40, 95% CI 0.20–0.80, p = 0.01) or advanced AI-specific knowledge (adjusted OR 0.43, 95% CI 0.21–0.90, p = 0.03) was inversely associated with fear. A positive attitude towards AI was observed in 48% (n = 501) and was associated with only having heard of AI, intermediate (adjusted OR 11.65, 95% CI 4.25–31.92, p < 0.001), or advanced AI-specific knowledge (adjusted OR 17.65, 95% CI 6.16–50.54, p < 0.001). Conclusions Limited AI-specific knowledge levels among radiology residents and radiologists are associated with fear, while intermediate to advanced AI-specific knowledge levels are associated with a positive attitude towards AI. Additional training may therefore improve clinical adoption. Key Points • Forty-eight percent of radiologists and residents have an open and proactive attitude towards artificial intelligence (AI), while 38% fear of replacement by AI. • Intermediate and advanced AI-specific knowledge levels may enhance adoption of AI in clinical practice, while rudimentary knowledge levels appear to be inhibitive. • AI should be incorporated in radiology training curricula to help facilitate its clinical adoption.

Objectives Currently, hurdles to implementation of artificial intelligence (AI) in radiology are a much-debated topic but have not been investigated in the community at large. Also, controversy exists if and to what extent AI should be incorporated into radiology residency programs. Methods Between April and July 2019, an international survey took place on AI regarding its impact on the profession and training. The survey was accessible for radiologists and residents and distributed through several radiological societies. Relationships of independent variables with opinions, hurdles, and education were assessed using multivariable logistic regression. Results The survey was completed by 1041 respondents from 54 countries. A majority (n = 855, 82%) expects that AI will cause a change to the radiology field within 10 years. Most frequently, expected roles of AI in clinical practice were second reader (n = 829, 78%) and work-flow optimization (n = 802, 77%). Ethical and legal issues (n = 630, 62%) and lack of knowledge (n = 584, 57%) were mentioned most often as hurdles to implementation. Expert respondents added lack of labelled images and generalizability issues. A majority (n = 819, 79%) indicated that AI should be incorporated in residency programs, while less support for imaging informatics and AI as a subspecialty was found (n = 241, 23%). Conclusions Broad community demand exists for incorporation of AI into residency programs. Based on the results of the current study, integration of AI education seems advisable for radiology residents, including issues related to data management, ethics, and legislation. Key Points • There is broad demand from the radiological community to incorporate AI into residency programs, but there is less support to recognize imaging informatics as a radiological subspecialty. • Ethical and legal issues and lack of knowledge are recognized as major bottlenecks for AI implementation by the radiological community, while the shortage in labeled data and IT-infrastructure issues are less often recognized as hurdles. • Integrating AI education in radiology curricula including technical aspects of data management, risk of bias, and ethical and legal issues may aid successful integration of AI into diagnostic radiology.

In vivo ophthalmic imaging, electroretinography, and postmortem histological RNA and protein analyses were used to monitor retinal health and function in normal (HbAA) and sickle (HbSS) hemoglobin-producing mice over a one-year period and in additional HbAA and HbSS mice treated with MMF (15 mg/ml) for 5 months. Functional and morphological abnormalities and molecular hallmarks of oxidative stress/inflammation were evident early in HbSS retinas and increased in number and severity with age. Treatment with MMF, a known inducer of Nrf2, induced γ-globin expression and fetal hemoglobin production, improved hematological profiles, and ameliorated SR-related pathology. Innovation and Conclusion: United States Food and Drug Administration-approved formulations in which MMF is the primary bioactive ingredient are currently available to treat multiple sclerosis; such drugs may be effective for treatment of ocular and systemic complications of SCD, and given the pleiotropic effects, other nonsickle-related diseases in which oxidative stress, inflammation, and retinal vascular pathology figure prominently. Antioxid. Redox Signal. 25, 921-935.

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Erectile dysfunction (ED) or impotence is estimated to affect around 20-30 million men in the United States (Rhoden et al, 2002). Vascular etiology is purported to be the most prevalent cause of ED in the elderly population, with venogenic ED being the most common subtype (Shafik et al, 2007; Rebonato et al, 2014). A patient, who developed severe venogenic ED, was referred to interventional radiology after ineffective pharmaceutical treatments. Selective embolization of bilateral external and internal pudendal veins was performed through accessing the deep dorsal vein of penis. Subsequent venogram verified successful embolization with stasis within the outflow of the deep dorsal vein of penis. Close to 6 weeks after the procedure, the patient purports to be able to achieve approximately 65% of full penile erection and complete penile erection with penile stimulation and 0.25 mL injection of alprostadil after 25 minutes.