Encrypted login | home

Program Information

Intensity Modulated Robotic Radiotherapy

no image available
B Wang

B Wang1*, L Jin1 , J Li1 , J Fan 1,2, L Chen1 , C Zhang1,3 , C Ma1 , (1) Fox Chase Cancer Center, Philadelphia, PA, (2) Virtua Fox Chase Cancer Center, Voorhees, NJ, (3) Qiqihar Medical University, Qiqihar, China

Presentations

SU-E-T-409 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: As compared with the IRIS-based models, the MLC-based CyberKnife system allows more efficient treatment delivery due to its improved coverage of large lesions and intensity modulation. The treatment delivery efficiency is mainly determined by the number of selected nodes. This study aimed to demonstrate that relatively small sets of optimally selected nodes could produce high-quality plans.

Methods: The full body path of the CyberKnife system consists of 110 nodes, from which we selected various sets for 4 prostate cancer cases using our in-house beam-selection software. With the selected nodes we generated IMRT plans using our in-house beamlet-based inverse-planning optimization program. We also produced IMRT plans using the MultiPlan treatment planning system (version 5.0) for the same cases. Furthermore, the nodes selected by MultiPlan were used to produce plans with our own optimization software so that we could compare the quality of the selected sets of nodes.

Results: Our beam-selection program selected one node-set for each case, with the number of nodes ranging from 23 to 34. The IMRT plans based on the selected nodes and our in-house optimization program showed adequate target coverage, with favorable critical structure sparing for the cases investigated. Compared with the plans using the nodes selected by MultiPlan, the plans generated with our selected beams provided superior rectum/bladder sparing for 75% of the cases. The plans produced by MultiPlan with various numbers of nodes also suggested that the plan quality was not compromised significantly when the number of nodes was reduced.

Conclusion: Our preliminary results showed that with beamlet-based planning optimization, one could produce high-quality plans with an optimal set of nodes for MLC-based robotic radiotherapy. Furthermore, our beam-selection strategy could help further improve critical structure sparing.


Contact Email: