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Introduction: Surface Guided Radiation Therapy (SGRT) is being increasingly implemented into clinical practice across a number of techniques and irradiation-sites. This technology, which is provided by different vendors, can be used with most simulation- and delivery-systems. However, limited guidelines and the complexity of clinical settings have led to diverse patterns of operation. With the aim to understand current clinical practice a survey was designed focusing on specifics of the clinical implementation and usage.Materials and methods: A 32-question survey covered: type and number of systems, quality assurance (QA), clinical workflows, and identification of strengths/limitations. Respondents from different professional groups and countries were invited to participate. The survey was distributed internationally via ESTRO-membership, social media and vendors.Results: Of the 278 institutions responding, 172 had at least one SGRT-system and 136 use SGRT clinically. Implementation and QA were primarily based on the vendors' recommendations and phantoms. SGRT was mainly implemented in breast RT (116/136), with strong but diverse representation of other sites. Many (58/135) reported at least partial elimination of skin-marks and a third (43/126) used open-masks. The most common imaging protocol reported included the combination of radiographic imaging with SGRT. Patient positioning (115/136), motion management (104/136) and DIBH (99/136) were the main applications.Main barriers to broader application were cost, system integration issues and lack of demonstrated clinical value. A lack of guidelines in terms of QA of the system was highlighted.Conclusions: This overview of the SGRT status has the potential to support users, vendors and organisations in the development of practices, products and guidelines.

Artificial Intelligence (ai) systems are precious support for decision-making, with many applications also in the medical domain. The interaction betweenmds andaienjoys a renewed interest following the increased possibilities of deep learning devices. However, we still have limited evidence-based knowledge of the context, design, and psychological mechanisms that craft an optimal human–aicollaboration. In this multicentric study, 21 endoscopists reviewed 504 videos of lesions prospectively acquired from real colonoscopies. They were asked to provide an optical diagnosis with and without the assistance of anaisupport system. Endoscopists were influenced byai($$\textsc {or}=3.05$$OR=3.05), but not erratically: they followed theaiadvice more when it was correct ($$\textsc {or}=3.48$$OR=3.48) than incorrect ($$\textsc {or}=1.85$$OR=1.85). Endoscopists achieved this outcome through a weighted integration of their and theaiopinions, considering the case-by-case estimations of the two reliabilities. This Bayesian-like rational behavior allowed the human–aihybrid team to outperform both agents taken alone. We discuss the features of the human–aiinteraction that determined this favorable outcome.

Einleitung: Die Kollagenbiosynthese hat eine wesentliche Bedeutung in der Prostatkarzinomentstehung und Progression. Rezent konnte in mehreren soliden Tumoren gezeigt werden, dass RAS-Inhibitoren (Renin-Angiotensin-System-Inhibitoren) eine wesentliche Rolle in der Kollagensynthese spielen, indem Angiotensin [zum vollständigen Text gelangen Sie über die oben angegebene URL]