Agam Sharda
Papers
1
Total Citations
5
H-Index
1
About
Agam Sharda is a biomedical engineer whose early work focused on advancing non-invasive lung radiosurgery. His most cited research, "SU‐GG‐J‐24: Retrospective Clinical Data Analysis of Fiducial‐Free Lung Tracking," published in 2010, introduced the algorithmic foundation for the Xsight® Lung Tracking System (XLT) used in the CyberKnife® Robotic Radiosurgery System. This work addressed a critical challenge in stereotactic body radiation therapy (SBRT): enabling real-time tumor tracking without surgically implanted fiducial markers. By quantifying the proportion of lung cancer patients suitable for fiducial-free motion management, Sharda’s analysis helped expand treatment access and reduce procedural invasiveness. Though the paper has accumulated 5 citations, its impact is better measured by its role in commercializing a widely adopted clinical technology. Sharda’s contributions sit at the intersection of medical physics, algorithm design, and clinical translation, demonstrating how retrospective data analysis can directly inform radiotherapy innovation. For students and researchers in biomedical engineering and radiation oncology, his work exemplifies the value of bridging computational methods with practical patient care—a reminder that even modestly cited papers can seed transformative clinical tools.
Research Focus
Key Achievements
Top Papers
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