K Venkatesan

Medanta The Medicity

Papers

1

Total Citations

6

H-Index

1

About

K Venkatesan is a distinguished medical physicist whose research centers on stereotactic radiosurgery (SRS) and advanced dosimetric techniques for treating complex cerebrovascular conditions. His most notable contribution involves a pioneering dosimetric comparison of robotic CyberKnife and linear accelerator (LINAC) multi-leaf collimator-based systems for arteriovenous malformation (AVM) treatment. This 2021 study, which has garnered 6 citations, systematically evaluated 25 AVM patients to determine optimal collimation strategies, providing critical guidance for clinicians selecting between robotic and conventional SRS platforms. Venkatesan’s work directly addresses the practical challenge of achieving precise dose delivery while minimizing damage to surrounding healthy tissue—a fundamental concern in radiosurgery. By quantifying differences in treatment planning parameters between these two widely used technologies, his research helps establish evidence-based protocols for AVM management. His contributions are particularly valuable for medical physicists and radiation oncologists seeking to optimize SRS outcomes, as his comparative analysis offers actionable insights into the trade-offs between robotic flexibility and LINAC precision. Venkatesan’s focused investigation represents an important step toward personalized radiosurgery planning, demonstrating how systematic dosimetric evaluation can improve treatment quality for patients with challenging intracranial vascular malformations.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Dosimetric Comparison of Robotic and Linear Accelerator Multi-Leaf Collimator-Based Stereotactic Radiosurgery for Arteriovenous Malformation
6 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Medanta The Medicity

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago