Takuji Kagiya

Hirosaki University

Papers

1

Total Citations

25

H-Index

1

About

Dr. Takuji Kagiya is a leading colorectal surgeon whose research focuses on advancing minimally invasive surgical techniques for rectal cancer, particularly through robotic-assisted approaches. His most-cited work, a 2020 study comparing robotic-assisted laparoscopic lateral lymph node dissection (RALLD) to conventional laparoscopic methods for advanced lower rectal cancer, has garnered 25 citations and demonstrates his commitment to improving surgical precision and patient outcomes. Dr. Kagiya’s major contributions center on optimizing lateral lymph node dissection—a critical procedure for reducing local recurrence in rectal cancer—by evaluating the short-term benefits of robotic technology, including enhanced visualization and dexterity. His research addresses a key challenge in colorectal oncology: balancing radical cancer clearance with reduced postoperative morbidity. Through comparative studies, he has provided early evidence that robotic assistance may offer advantages over standard laparoscopy, such as lower blood loss and shorter hospital stays, though he emphasizes the need for long-term oncologic validation. Dr. Kagiya’s work is instrumental in shaping evidence-based guidelines for robotic rectal cancer surgery, bridging the gap between technological innovation and clinical practice. His findings are widely referenced by surgeons and researchers exploring the role of robotics in complex pelvic dissections, underscoring his impact on the field.

Research Focus

Key Achievements

1
H-Index
1
Papers
25
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Short-term outcomes of robotic-assisted laparoscopic versus laparoscopic lateral lymph node dissection for advanced lower rectal cancer
25 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Hirosaki University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago