Introduction: The coming decade will see the emergence of many surgical robotic systems that need to prove their cost‐effectiveness and clinical usability to gain the trust of robotic surgeons worldwide. Herein, we provide a concise review of the currently available robotic systems. Since the da Vinci Surgical System's patent expired and its market monopoly ended, many robotic surgical systems have, and will continue to, enter the market. Central to this is the challenge of gaining the trust of robotic surgeons in a cost‐effective manner. However, the cumulative robotic surgical experience of Intuitive Surgical over these years—which has proven itself clinically and technically—is a great challenge for new surgical robots.Methods: This was a non‐systematic review of the literature, conducted through the PubMed search engine, using the following words: “Da Vinci,” “robotic surgical system,” and “new robotic surgical device.” Further information was obtained from the robotic system companies’ official websites and press releases.Conclusions: The open robotic market carries great challenges for new robotic surgical systems, especially when following well‐established da Vinci Surgical System. Surgeons’ trust, clinical publications, technical support, and market distribution all represent separate challenges that require address.

Jung HD, et al. Yonsei Med J. 2022 May;63(5):440-445. https://doi.org/10.3349/ymj.2022.63.5.440

A high nuclear grade is crucial to predicting tumor recurrence and metastasis in clear cell renal cell carcinomas (ccRCCs). We aimed to compare the mRNA profiles of tumor tissues and preoperative plasma in patients with localized T1 stage ccRCCs, and to evaluate the potential of the plasma mRNA profile for predicting high-grade ccRCCs. Data from a prospective cohort (n = 140) were collected between November 2018 and November 2019. Frozen tumor tissues and plasma were used to measure PBRM1, BAP1, SET domain-containing 2 (SETD2), KDM5C, FOXC2, CLIP4, AQP1, DDX11, BAIAP2L1, and TMEM38B mRNA levels, and correlation with the Fuhrman grade was investigated. Multivariate logistic regression analysis revealed significant association between high-grade ccRCC and SETD2 and DDX11 mRNA levels in tissues (odds ratio (β) = 0.021, 95% confidence interval (CI): 0.001–0.466, p = 0.014; β = 6.116, 95% CI: 1.729–21.631, p = 0.005, respectively) and plasma (β = 0.028, 95% CI 0.007–0.119, p < 0.001; β = 1.496, 95% CI: 1.187–1.885, p = 0.001, respectively). High-grade ccRCC prediction models revealed areas under the curve of 0.997 and 0.971 and diagnostic accuracies of 97.86% and 92.86% for the frozen tissue and plasma, respectively. SETD2 and DDX11 mRNA can serve as non-invasive plasma biomarkers for predicting high-grade ccRCCs. Studies with long follow-ups are needed to validate the prognostic value of these biomarkers in ccRCCs.