Jason M. Scovell

Baylor College of Medicine

Papers

3

Total Citations

146

H-Index

3

About

Jason M. Scovell is a urologic surgeon and researcher whose work sits at the intersection of surgical innovation, simulation training, and diagnostic precision. His most impactful contribution lies in advancing preoperative planning for complex kidney tumor resections. In his highly cited 2016 study (130 citations), Scovell pioneered the use of patient-specific, 3D-printed silicone renal models for robot-assisted laparoscopic partial nephrectomy. By enabling surgeons to physically rehearse tumor resections on tissue-like replicas, this work directly improved surgical outcomes and set a new standard for personalized surgical preparation. Beyond 3D printing, Scovell has refined functional imaging interpretation, demonstrating that percent tracer clearance at 40 minutes in MAG3 renal scans is more sensitive than traditional half-time measurements for diagnosing symptomatic ureteropelvic junction obstruction. He has also advanced surgical education by validating a step-by-step simulation-training model for robotic intracorporeal bowel anastomosis. Collectively, Scovell’s research bridges cutting-edge technology with practical clinical application, enhancing both the safety of complex urologic surgeries and the training of the next generation of robotic surgeons.

Research Focus

Key Achievements

3
H-Index
3
Papers
146
Total Citations
49
Avg Citations/Paper
🏆 Most Cited Paper
Utility of patient‐specific silicone renal models for planning and rehearsal of complex tumour resections prior to robot‐assisted laparoscopic partial nephrectomy
130 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Baylor College of Medicine

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago