The management of liver transplant recipients and their outcome prediction is complex due to nonlinear interaction of multiple pre,peri and postoperative factors.Artificial intelligence(AI)has a potentially significan...The management of liver transplant recipients and their outcome prediction is complex due to nonlinear interaction of multiple pre,peri and postoperative factors.Artificial intelligence(AI)has a potentially significant role in understanding and decision making at all stages of liver transplantation procedure.The role starts right from diagnosis of liver cirrhosis,followed by best course of action and prognostication.By analyzing numerous data points,AI can assist in the complex decision-making process of determining transplant candidacy.AI algorithms can analyze vast datasets of donor and recipient characteristics to improve the accuracy of matching,leading to better graft survival rates.This will help in optimizing the allocation of scarce organs,ensuring that they go to the most suitable recipients.AI can be used to predict the pre-operative risk factors and risk of post-operative complications such as graft rejection or post-transplant infections,allowing timely and tailored treatment.AI-powered imaging analysis can assist surgeons in preoperative planning and provide real-time guidance during surgery,increasing precision and improved safety.Therefore,AI has the potential to enhance long term patient and graft survival.The major challenges on use of AI are data availability,data quality,ethical considerations and clinical integration.In essence,AI holds great promise for revolutionizing liver transplantation albeit with some challenges.展开更多
Objective:The authors present outcomes of robotic liver resections in comparison with open technique questioning the need to have experience of laparoscopy for such procedures before transition to robotic assisted.Mat...Objective:The authors present outcomes of robotic liver resections in comparison with open technique questioning the need to have experience of laparoscopy for such procedures before transition to robotic assisted.Materials and methods:Retrospective review of liver resections done robotically from February 2015 to June 2017 compared to matched control cohort of open cases from January 2012 to December 2016.Results:Twenty-one patients in the study groupwere comparedwithmatched control of 42 open cases(1:2 ratio).The types of procedure were similar in both the groups.There were 4 left lateral hepatectomy,3 left hepatectomy,and 1 left hepatectomy with hepatico-jejunostomy,3 right hepatectomy,3 right posterior sectorectomy,4 bisegmentectomy and 4 mono-segmentectomy.There were 9 patients with primary liver cancer,2 each with livermetastasis and carcinoma gall bladder and 8 patients had benign liver disease.Mean blood losswas 370±311ml in the robotic group compared to 451±330ml in control group(p=0.06).Minor complications developed in 19.0%of robotic cases compared to 40.5%in open surgery,while major complications occurred in 4.7%of robotic cases compared to 7.1%of open cases.Mean hospital staywas 5.3±0.8 days for the robotic group and 7.7±4.2 days for open group(p=0.02).Local tumor recurrence occurred in 1 out of 13 resections done for malignancy in the robotic group and 7 out of 26 in the open group.Conclusion:This study highlights the utility of surgical robots for segmental and complex liver resections with equivalent outcomes and decreased length of hospital stay compared to open surgery without having experience of same with the laparoscopy.展开更多
Background: An accurate preoperative volumetric assessment of donor liver is essential for successful living donor liver transplant by ensuring adequate remnant and graft recipient weight ratio (GRWR). Methods: The st...Background: An accurate preoperative volumetric assessment of donor liver is essential for successful living donor liver transplant by ensuring adequate remnant and graft recipient weight ratio (GRWR). Methods: The study cohort consisted of 744 right lobe (RL), 65 left lobe (LL) and 33 left lateral sector (LLS) grafts from July 2010 to January 2014. A semi-automated interactive commercial software called AW Volume share 6 was used for volumetry. Bland Altman plot was used for assessing the agreement between estimated graft weight (EGW) and actual graft weight (AGW). Results: There was no statistically significant difference between EGW and AGW for RL graft weight (722±134 vs. 717±126 gm;P=0.06). Although Bland Altman graph showed that 95% limits of agreement was more in LL (?164 to +110) than RL (?156 to +147) and LLS grafts (?137 to +239), CT scan significantly overestimated LL graft weight (EGW =460±118 gm vs. AGW =433±102 gm;P=0.003) and underestimated LLS graft weight (EGW =203±48 gm vs. AGW =254±49 gm;P<0.001). Conclusions: CT volumetry overestimate LL graft and underestimate LLS graft weight. This should be factored in when selecting LL graft by taking higher GRWR.展开更多
文摘The management of liver transplant recipients and their outcome prediction is complex due to nonlinear interaction of multiple pre,peri and postoperative factors.Artificial intelligence(AI)has a potentially significant role in understanding and decision making at all stages of liver transplantation procedure.The role starts right from diagnosis of liver cirrhosis,followed by best course of action and prognostication.By analyzing numerous data points,AI can assist in the complex decision-making process of determining transplant candidacy.AI algorithms can analyze vast datasets of donor and recipient characteristics to improve the accuracy of matching,leading to better graft survival rates.This will help in optimizing the allocation of scarce organs,ensuring that they go to the most suitable recipients.AI can be used to predict the pre-operative risk factors and risk of post-operative complications such as graft rejection or post-transplant infections,allowing timely and tailored treatment.AI-powered imaging analysis can assist surgeons in preoperative planning and provide real-time guidance during surgery,increasing precision and improved safety.Therefore,AI has the potential to enhance long term patient and graft survival.The major challenges on use of AI are data availability,data quality,ethical considerations and clinical integration.In essence,AI holds great promise for revolutionizing liver transplantation albeit with some challenges.
文摘Objective:The authors present outcomes of robotic liver resections in comparison with open technique questioning the need to have experience of laparoscopy for such procedures before transition to robotic assisted.Materials and methods:Retrospective review of liver resections done robotically from February 2015 to June 2017 compared to matched control cohort of open cases from January 2012 to December 2016.Results:Twenty-one patients in the study groupwere comparedwithmatched control of 42 open cases(1:2 ratio).The types of procedure were similar in both the groups.There were 4 left lateral hepatectomy,3 left hepatectomy,and 1 left hepatectomy with hepatico-jejunostomy,3 right hepatectomy,3 right posterior sectorectomy,4 bisegmentectomy and 4 mono-segmentectomy.There were 9 patients with primary liver cancer,2 each with livermetastasis and carcinoma gall bladder and 8 patients had benign liver disease.Mean blood losswas 370±311ml in the robotic group compared to 451±330ml in control group(p=0.06).Minor complications developed in 19.0%of robotic cases compared to 40.5%in open surgery,while major complications occurred in 4.7%of robotic cases compared to 7.1%of open cases.Mean hospital staywas 5.3±0.8 days for the robotic group and 7.7±4.2 days for open group(p=0.02).Local tumor recurrence occurred in 1 out of 13 resections done for malignancy in the robotic group and 7 out of 26 in the open group.Conclusion:This study highlights the utility of surgical robots for segmental and complex liver resections with equivalent outcomes and decreased length of hospital stay compared to open surgery without having experience of same with the laparoscopy.
文摘Background: An accurate preoperative volumetric assessment of donor liver is essential for successful living donor liver transplant by ensuring adequate remnant and graft recipient weight ratio (GRWR). Methods: The study cohort consisted of 744 right lobe (RL), 65 left lobe (LL) and 33 left lateral sector (LLS) grafts from July 2010 to January 2014. A semi-automated interactive commercial software called AW Volume share 6 was used for volumetry. Bland Altman plot was used for assessing the agreement between estimated graft weight (EGW) and actual graft weight (AGW). Results: There was no statistically significant difference between EGW and AGW for RL graft weight (722±134 vs. 717±126 gm;P=0.06). Although Bland Altman graph showed that 95% limits of agreement was more in LL (?164 to +110) than RL (?156 to +147) and LLS grafts (?137 to +239), CT scan significantly overestimated LL graft weight (EGW =460±118 gm vs. AGW =433±102 gm;P=0.003) and underestimated LLS graft weight (EGW =203±48 gm vs. AGW =254±49 gm;P<0.001). Conclusions: CT volumetry overestimate LL graft and underestimate LLS graft weight. This should be factored in when selecting LL graft by taking higher GRWR.
