Characteristics and performance of the first commercial multileaf collimator for a robotic radiosurgery system

Purpose: The "InCise™ multileaf-collimator (MLC)" is the first commercial MLC to be mounted on a robotic SRS/SBRT platform (CyberKnife). The authors assessed characteristics and performance of this novel device in a preclinical five months test period. Methods: Commissioning beam data were acquired with unshielded diodes. EBT3 radiochromic films were employed for measurement of transmission, leaf/bank position accuracy (garden fence) before and after exercising the MLC, for end-to-end testing and further characterization of the beam. The robot workspace with MLC was assessed analytically by transformation to an Euler geometry ("plane," "gantry," and "collimator" angles) and by measuring pointing accuracy at each node. Stability over time was evaluated in picket fence and adapted Winston-Lutz tests (AQA). Results: Beam penumbrae (80%-20%, with 100% = 2 × dose at inflection point for field sizes ≥ 50 × 50 mm2) were 2.2-3.7 mm for square fields in reference condition (source-axis-distance 800 mm, depth 15 mm) and depended on field size and off-axis position. Transmission and leakage did not exceed 0.5%. Accessible clinical workspace with MLC covered non-coplanar gantry angles of [-113°; +112°] and collimator angles of [-100°; +107°], with an average robot pointing accuracy of 0.12 ± 0.09 mm. For vertical beams, garden fence tests exhibited an average leaf positioning error of ≤0.2 mm, which increased by 0.25 and 0.30 mm (banks X1 and X2) with leaves traveling parallel to gravity. After execution of a leaf motion stress routine, garden fence tests showed slightly increased jaggedness and allowed to identify one malfunctioning leaf motor. Total system accuracy with MLC was 0.38 ± 0.05 mm in nine end-to-end tests. Picket fence and AQA tests displayed stable results over the test period. Conclusions: The InCise™ MLC for CyberKnife showed high accuracy and adequate characteristics for SRS/SBRT applications. MLC performance after exercise demands specific quality assurance measures.

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