Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

• Published in: International journal of radiation oncology, biology, physics Vol. 93; no. 4; pp. 916 - 924
• Main Authors: Winter, Jeff D., PhD, Wong, Raimond, MD, Swaminath, Anand, MD, Chow, Tom, PhD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.11.2015
• Subjects: Aged; Aged, 80 and over; BIOMEDICAL RADIOGRAPHY; CORRELATIONS; Dose Fractionation; ERRORS; Female; Fiducial Markers; FORECASTING; Hematology, Oncology and Palliative Medicine; Humans; LINEAR ACCELERATORS; Linear Models; LIVER; Liver Neoplasms - diagnostic imaging; Liver Neoplasms - secondary; Liver Neoplasms - surgery; Male; Middle Aged; Movement; Particle Accelerators; POSITIONING; Radiography; Radiology; RADIOLOGY AND NUCLEAR MEDICINE; Radiosurgery - methods; Radiosurgery - standards; RADIOTHERAPY; Radiotherapy Planning, Computer-Assisted - methods; Radiotherapy Setup Errors; Respiration; Retrospective Studies; Robotics - methods; Uncertainty
• ISSN: 0360-3016; 1879-355X
• DOI: 10.1016/j.ijrobp.2015.08.031

Purpose To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately before beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude ( r =0.53-0.66, P <.001), whereas only weak correlations existed for correlation errors. Conclusions Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.