Papers

2

Total Citations

12

H-Index

2

About

Tie-Niu Song is a pioneering thoracic surgeon whose research centers on advancing robotic esophagectomy techniques for esophageal cancer treatment. His major contributions lie in systematically characterizing the learning curve for robotic lymphadenectomy across both McKeown and Ivor Lewis approaches, demonstrating that mastery of thoracic lymph node dissection requires distinct skill acquisition for each surgical method. In a landmark 2021 retrospective study of the first 100 robotic esophagectomy cases, Song established critical benchmarks for surgical training and quality improvement, showing that proficiency in one approach does not automatically transfer to the other. His work on pretreatment-assisted robot intrathoracic layered anastomosis has further refined the technically demanding Ivor-Lewis procedure, proposing a novel anastomotic technique that addresses the longstanding challenge of intrathoracic esophago-gastric reconstruction. With his papers accumulating over a dozen citations in the surgical oncology literature, Song's research directly impacts how thoracic surgeons train for and perform minimally invasive esophageal cancer surgery, ultimately improving patient outcomes through standardized, evidence-based robotic techniques.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
From McKeown to Ivor Lewis, the learning curve for thoracic lymphadenectomy over the first 100 robotic esophagectomy cases: a retrospective study
8 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Sichuan University, West China Hospital of Sichuan University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago