Artificial intelligence(AI)has made considerable progress within the last decade and is the subject of contemporary literature.This trend is driven by improved computational abilities and increasing amounts of complex...Artificial intelligence(AI)has made considerable progress within the last decade and is the subject of contemporary literature.This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation.Renal cell carcinoma(RCC)has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging.This creates considerable challenges as approximately 10%e17%of kidney tumors are designated as benign in histopathological evaluation;however,certain co-morbid populations(the obese and elderly)have an increased peri-interventional risk.AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions.The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC.Currently,AI applications can be found in any aspect of RCC management including diagnostics,perioperative care,pathology,and follow-up.Most commonly applied models include neural networks,random forest,support vector machines,and regression.However,for implementation in daily practice,health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets,define meaningful endpoints,and unify interpretation.展开更多
Objective:Kidney cancers account for approximately 2%of all newly diagnosed cancer in 2020.Among the primary treatment options for kidney cancer,urologist may choose between radical or partial nephrectomy,or ablative ...Objective:Kidney cancers account for approximately 2%of all newly diagnosed cancer in 2020.Among the primary treatment options for kidney cancer,urologist may choose between radical or partial nephrectomy,or ablative therapies.Nowadays,robotic-assisted partial nephrectomy(RAPN)for the management of renal cancers has gained popularity,up to being considered the gold standard.However,RAPN is a challenging procedure with a steep learning curve.Methods:In this narrative review,different imaging technologies used to guide and aid RAPN are discussed.Results:Three-dimensional visualization technology has been extensively discussed in RAPN,showing its value in enhancing robotic-surgery training,patient counseling,surgical planning,and intraoperative guidance.Intraoperative imaging technologies such as intracorporeal ultrasound,near-infrared fluorescent imaging,and intraoperative pathological examination can also be used to improve the outcomes following RAPN.Finally,artificial intelligence may play a role in the field of RAPN soon.Conclusion:RAPN is a complex surgery;however,many imaging technologies may play an important role in facilitating it.展开更多
文摘Artificial intelligence(AI)has made considerable progress within the last decade and is the subject of contemporary literature.This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation.Renal cell carcinoma(RCC)has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging.This creates considerable challenges as approximately 10%e17%of kidney tumors are designated as benign in histopathological evaluation;however,certain co-morbid populations(the obese and elderly)have an increased peri-interventional risk.AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions.The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC.Currently,AI applications can be found in any aspect of RCC management including diagnostics,perioperative care,pathology,and follow-up.Most commonly applied models include neural networks,random forest,support vector machines,and regression.However,for implementation in daily practice,health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets,define meaningful endpoints,and unify interpretation.
文摘Objective:Kidney cancers account for approximately 2%of all newly diagnosed cancer in 2020.Among the primary treatment options for kidney cancer,urologist may choose between radical or partial nephrectomy,or ablative therapies.Nowadays,robotic-assisted partial nephrectomy(RAPN)for the management of renal cancers has gained popularity,up to being considered the gold standard.However,RAPN is a challenging procedure with a steep learning curve.Methods:In this narrative review,different imaging technologies used to guide and aid RAPN are discussed.Results:Three-dimensional visualization technology has been extensively discussed in RAPN,showing its value in enhancing robotic-surgery training,patient counseling,surgical planning,and intraoperative guidance.Intraoperative imaging technologies such as intracorporeal ultrasound,near-infrared fluorescent imaging,and intraoperative pathological examination can also be used to improve the outcomes following RAPN.Finally,artificial intelligence may play a role in the field of RAPN soon.Conclusion:RAPN is a complex surgery;however,many imaging technologies may play an important role in facilitating it.
