Purpose: Accurate identification of the bile duct bifurcation site is crucial in pure laparoscopic donor right hepatectomy (PLDRH) for living donor liver transplantation. This study aimed to develop and evaluate a deep learning model to predict the bile duct bifurcation site for surgical precision. Methods: We retrospectively analyzed 55 PLDRH procedures conducted between August 2021 and April 2022. A deep learning model combining UNet with a MiT-B3 encoder was trained on 150 manually annotated frames. We then incorporated expert-reviewed pseudo-labels from an additional 901 frames to refine the model. Performance was evaluated using 5-fold cross-validation and an independent test set. Results: Clinical evaluation showed a 97% accuracy in 5-fold cross-validation and 93.3% accuracy in the independent test set. From the initial to final model, dice similarity coefficient improved from 0.392 to 0.472, intersection over union from 0.279 to 0.339, and sensitivity from 0.487 to 0.643, while specificity remained consistent at 0.993. Conclusion The proposed artificial intelligence (AI) model demonstrated strong clinical performance in predicting the bile duct bifurcation site during PLDRH. Despite modest quantitative scores, the high clinical accuracy highlights the potential of integrating AI for precise donor hepatectomy.

The operating room remains a paradox: it is one of the most sensor-rich environments in the hospital, yet it produces largely underutilized data. While surgical artificial intelligence (AI) has achieved remarkable progress in recent years, the day-to-day practice of surgery has changed little, with most systems confined to passive decision support. This narrative review traces the evolution of surgical AI from perception to cognition to early forms of action, arguing that the next paradigm shift requires “physical AI”—systems capable of meaningful physical interaction and autonomous execution. The clinical motivation for pursuing physical AI is clear: surgical outcomes vary substantially across surgeons, access is constrained by workforce shortages, and high-quality care remains tied to the scarcity of human expertise. If reliable autonomous systems can be developed, surgery could become more standardized, scalable, and reproducible.However, a critical bottleneck persists: the scarcity of synchronized, multimodal training data. The fundamental barrier is environmental rather than algorithmic, as most operating rooms are not configured to measure surgical practice objectively. We propose reconceptualizing the operating room as a “Surgical Data Factory”—a closed-loop ecosystem designed to capture multimodal signals, structure them via consensus taxonomies linked to outcomes, and utilize them for training, validation, and monitoring. Surgeons must transition from passive users to active architects of this infrastructure.Investing in systematic data governance is the prerequisite for responsibly developing, validating, and scaling physical AI in surgery.

Background/Aims: Fexuprazan, a novel potassium-competitive acid blocker, was developed for treating acid-related disorders. Pharmacokinetic and pharmacodynamic properties of fexuprazan, unlike those of proton pump inhibitors, are independent of food effect. This study aims to evaluate differences in efficacy and safety of fexuprazan in patients with erosive esophagitis (EE) according to the timing of dosing. Methods: In this multicenter, open-label noninferiority study, patients who had typical reflux symptoms with endoscopically confirmed EE were randomized 1:1 to receive fexuprazan 40 mg daily 30 minutes before or after meal. Treatment was completed after 2 weeks or 4 weeks when healing was endoscopically confirmed. The primary endpoint was the proportion of patients with healed EE confirmed by endoscopy up to week 4. Safety endpoints included treatment-emergent adverse events (TEAEs). Results: In the prior-to-meal group (n = 89) and after-meal group (n = 86), 4-week EE healing rates were 98.77% and 100.00% (difference, 0.01%; 95% CI, –0.01% to 0.04%) and 2-week EE healing rates were 95.77% and 97.14% (difference, 0.01%; 95% CI, –0.05% to 0.07%), respectively. TEAEs were 9.78% and 8.70% in the prior-to-meal group and the after-meal group, respectively. Conclusions Non-inferiority analysis revealed that taking fexuprazan after meal was non-inferior to taking fexuprazan before meals in patients with EE. The frequency of adverse events was similar between the 2 study groups. The drug is safe and effective for healing EE regardless of the timing of dosing.

Background: s/Aims: While large-for-size syndrome is uncommon in liver transplantation (LT), it can result in fatal outcome. To prevent such fatality, we manufactured 3D-printed intra-abdominal cavity replicas to provide intuitive understanding of the sizes of the graft and the patient’s abdomen in patients with small body size between July 2020 and February 2022. Methods: Clinical outcomes were compared between patients using our 3D model during LT, and patients who underwent LT without 3D model by using 1 : 5 ratio propensity score-matched analysis. Results: After matching, a total of 20 patients using 3D-printed abdominal cavity model and 100 patients of the control group were included in this study. There were no significant differences in 30-day postoperative complication (50.0% vs. 64.0%, p = 0.356) and the incidence of large-for-size syndrome (0% vs. 7%, p = 0.599). Overall survival of the 3D-printed group was similar to that of the control group (p = 0.665), but graft survival was significantly superior in the 3D-printed group, compared to the control group (p = 0.034). Conclusions Since it showed better graft survival, as well as low cost and short production time, our 3D-printing protocol can be a feasible option for patients with small abdominal cavity to prevent large-for-size syndrome after LT.

Purpose: Treatment options for hepatocellular carcinoma (HCC) vary according to known guidelines among liver resection (LR), liver transplantation (LT), radiofrequency ablation (RFA), and transarterial chemoembolization (TACE). This study aimed to compare the outcomes of initial treatment for patients with resectable HCC within Milan criteria (MC) via nationwide data. Methods: Patients with resectable HCC (Child-Pugh class A; platelet count, ≥100,000/μL) within MC from the Korean Liver Cancer Association databank were analyzed, retrospectively. Outcomes according to initial treatment and subgroups according to tumor size and number were analyzed. Overall survival (OS) rates after initial treatment were compared. Results: A total of 3,241 patients who underwent LR (n = 1,371), LT (n = 12), RFA (n = 679), or TACE (n = 1,179) were included. The 5-year OS rates differed significantly between the groups (P < 0.05), except for LT (LR, 84.9%; LT, 82.5%;RFA, 76.2%; and TACE, 59.9%). For patients with a single tumor of any size, the 5-year OS rates of the LR group were significantly higher than RFA and TACE groups. For patients with multiple tumors, the 5-year OS rates were 78.2%, 100%, 74.3%, and 53.0% for the LR, LT, RFA, and TACE groups, respectively, but without significant difference between LR and RFA (P = 0.86). Conclusion For resectable HCC within MC, the LR had the highest OS rate for a single tumor of any size. LR and RFA showed no significant differences in OS rate for multiple tumors. LR has a much more optimistic outlook for HCC within MC.

Background: s/Aims: While large-for-size syndrome is uncommon in liver transplantation (LT), it can result in fatal outcome. To prevent such fatality, we manufactured 3D-printed intra-abdominal cavity replicas to provide intuitive understanding of the sizes of the graft and the patient’s abdomen in patients with small body size between July 2020 and February 2022. Methods: Clinical outcomes were compared between patients using our 3D model during LT, and patients who underwent LT without 3D model by using 1 : 5 ratio propensity score-matched analysis. Results: After matching, a total of 20 patients using 3D-printed abdominal cavity model and 100 patients of the control group were included in this study. There were no significant differences in 30-day postoperative complication (50.0% vs. 64.0%, p = 0.356) and the incidence of large-for-size syndrome (0% vs. 7%, p = 0.599). Overall survival of the 3D-printed group was similar to that of the control group (p = 0.665), but graft survival was significantly superior in the 3D-printed group, compared to the control group (p = 0.034). Conclusions Since it showed better graft survival, as well as low cost and short production time, our 3D-printing protocol can be a feasible option for patients with small abdominal cavity to prevent large-for-size syndrome after LT.

Purpose: Treatment options for hepatocellular carcinoma (HCC) vary according to known guidelines among liver resection (LR), liver transplantation (LT), radiofrequency ablation (RFA), and transarterial chemoembolization (TACE). This study aimed to compare the outcomes of initial treatment for patients with resectable HCC within Milan criteria (MC) via nationwide data. Methods: Patients with resectable HCC (Child-Pugh class A; platelet count, ≥100,000/μL) within MC from the Korean Liver Cancer Association databank were analyzed, retrospectively. Outcomes according to initial treatment and subgroups according to tumor size and number were analyzed. Overall survival (OS) rates after initial treatment were compared. Results: A total of 3,241 patients who underwent LR (n = 1,371), LT (n = 12), RFA (n = 679), or TACE (n = 1,179) were included. The 5-year OS rates differed significantly between the groups (P < 0.05), except for LT (LR, 84.9%; LT, 82.5%;RFA, 76.2%; and TACE, 59.9%). For patients with a single tumor of any size, the 5-year OS rates of the LR group were significantly higher than RFA and TACE groups. For patients with multiple tumors, the 5-year OS rates were 78.2%, 100%, 74.3%, and 53.0% for the LR, LT, RFA, and TACE groups, respectively, but without significant difference between LR and RFA (P = 0.86). Conclusion For resectable HCC within MC, the LR had the highest OS rate for a single tumor of any size. LR and RFA showed no significant differences in OS rate for multiple tumors. LR has a much more optimistic outlook for HCC within MC.

Background/Aims: Fexuprazan, a novel potassium-competitive acid blocker, was developed for treating acid-related disorders. Pharmacokinetic and pharmacodynamic properties of fexuprazan, unlike those of proton pump inhibitors, are independent of food effect. This study aims to evaluate differences in efficacy and safety of fexuprazan in patients with erosive esophagitis (EE) according to the timing of dosing. Methods: In this multicenter, open-label noninferiority study, patients who had typical reflux symptoms with endoscopically confirmed EE were randomized 1:1 to receive fexuprazan 40 mg daily 30 minutes before or after meal. Treatment was completed after 2 weeks or 4 weeks when healing was endoscopically confirmed. The primary endpoint was the proportion of patients with healed EE confirmed by endoscopy up to week 4. Safety endpoints included treatment-emergent adverse events (TEAEs). Results: In the prior-to-meal group (n = 89) and after-meal group (n = 86), 4-week EE healing rates were 98.77% and 100.00% (difference, 0.01%; 95% CI, –0.01% to 0.04%) and 2-week EE healing rates were 95.77% and 97.14% (difference, 0.01%; 95% CI, –0.05% to 0.07%), respectively. TEAEs were 9.78% and 8.70% in the prior-to-meal group and the after-meal group, respectively. Conclusions Non-inferiority analysis revealed that taking fexuprazan after meal was non-inferior to taking fexuprazan before meals in patients with EE. The frequency of adverse events was similar between the 2 study groups. The drug is safe and effective for healing EE regardless of the timing of dosing.