Johan F. Langenhuijsen

Radboud University Medical Center, Radboud University Nijmegen

Papers

4

Total Citations

214

H-Index

4

About

Johan F. Langenhuijsen is a leading urologic oncologist whose research focuses on optimizing surgical outcomes for patients with renal tumors, particularly through partial nephrectomy. His work centers on refining resection techniques, evaluating intraoperative imaging, and understanding predictors of surgical success. Langenhuijsen’s most influential study, a prospective multicenter investigation with 93 citations, demonstrated how different resection techniques impact perioperative outcomes and surgical margins after partial nephrectomy. He has also advanced the field by exploring intraoperative imaging to support complete tumor resection (74 citations) and by developing the Surface-Intermediate-Base (SIB) margin score—a standardized system for reporting resection techniques. His research on predictors of positive surgical margins after robot-assisted partial nephrectomy, involving a large international consortium, has provided critical insights for improving surgical precision. Langenhuijsen’s work has been instrumental in reducing the risk of Trifecta failure—a composite outcome of negative margins, no complications, and renal function preservation—particularly for highly complex renal masses. With over 200 citations across his key papers, his contributions continue to shape best practices in nephron-sparing surgery, directly benefiting surgeons and patients alike.

Research Focus

Key Achievements

4
H-Index
4
Papers
214
Total Citations
54
Avg Citations/Paper
🏆 Most Cited Paper
Impact of Resection Technique on Perioperative Outcomes and Surgical Margins after Partial Nephrectomy for Localized Renal Masses: A Prospective Multicenter Study
93 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: Radboud University Medical Center, Radboud University Nijmegen

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago