Luciano Haiquel

Institute Mutualiste Montsouris

Papers

1

Total Citations

3

H-Index

1

About

Luciano Haiquel is a urologic surgeon and researcher whose work centers on precision oncology and surgical personalization in prostate cancer care. His primary research focus lies in refining nerve-sparing techniques during robot-assisted radical prostatectomy (RARP), particularly for men with unilateral high-risk prostate cancer. Haiquel’s major contribution is the development and external validation of an algorithm that tailors nerve-sparing approaches based on individual tumor characteristics, aiming to preserve erectile function without compromising oncologic control. His most-cited paper, "External validation of an algorithm to personalize nerve sparing approaches during robot-assisted radical prostatectomy in men with unilateral high-risk prostate cancer" (2024), has already garnered 3 citations, signaling early impact in a rapidly evolving field. This work builds on his broader expertise in surgical outcomes, imaging-guided decision-making, and the integration of risk-stratification tools into operative planning. Haiquel’s research is notable for bridging the gap between high-risk disease management and functional preservation, a persistent challenge in urologic oncology. His findings offer a practical, evidence-based framework for surgeons, directly benefiting patients by reducing postoperative morbidity. As his algorithm gains wider adoption, Haiquel is poised to shape the next generation of personalized robotic prostate surgery.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
External validation of an algorithm to personalize nerve sparing approaches during robot-assisted radical prostatectomy in men with unilateral high-risk prostate cancer
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Institute Mutualiste Montsouris

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago