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Intrinsic Uncertainty in the Positional Accuracy Determined by Stereotactic Image Guidance System in Cranial Robotic Radiosurgery


R Thiyagarajan

Rajesh Thiyagarajan1*, Karrthick KP1 , Arunai Nambiraj2 , Tamil Selvan1 , Ashu Abhishek1 , Sasi Rajendran1 , Merin Raju1 , T Kataria1 , (1) Medanta The Medicity, Gurgaon, Haryana, India (2) VIT University, Vellore, Tamil Nadu, India

Presentations

WE-RAM1-GePD-JT-2 (Wednesday, August 2, 2017) 9:30 AM - 10:00 AM Room: Joint Imaging-Therapy ePoster Theater


Purpose: To quantify intrinsic uncertainty of positional accuracy determined by stereotactic image guidance in cranial robotic radiosurgery system.

Methods: In this study, Cyberknife (CK) VSI robotic radiosurgery system, anthropomorphic head and neck phantom and 6D skull tracking algorithm were used. The phantom was placed on the treatment couch in a random position but close to the image center of the CK. kV images were acquired and positional accuracy in translation and rotational directions was estimated by 6D skull tracking algorithm. The difference in phantom position with respect to the planning position was observed but not corrected. This process was repeated for 21 times consecutively without any gap in a single day. Similar positional shifts were obtained for 34 working days over two months. Everyday’s first set of shift was taken as reference and the deviation of the subsequent 20 sets were calculated. Mean and standard deviation (SD) were calculated for individual days as well as for all 34 days.

Results: Systematic and random error components are calculated from Mean and SD. Systematic error in lateral, verticaland longitudinal orientation were 0.03mm, 0.02mm and 0.03mm respectively. Systematic error for roll, pitch and yaw orientation were 0.02˚, 0.02˚ and 0.03˚ respectively. The magnitude of random error component is found to be 0.04mm, 0.04mm, 0.03mm, 0.04˚, 0.03˚ and 0.04˚ in lateral, vertical, longitudinal, roll, pitch and yaw orientation

Conclusion: The intrinsic uncertainty in 6D skull tracking algorithm based stereotactic image guidance system is quantified and found to be acceptable in the robotic radiosurgery domain. Periodical quality assurance estimating systematic and random errors required to ensure localization accuracy in radiosurgery.


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