Room: AAPM ePoster Library
Purpose: To assess the capability of different combinations of treatment planning and delivery systems to satisfy the UNC treatment planning protocol of stereotactic radiosurgery for multi-lesion brain cases.
Methods: A CT simulation scan of a patient with five brain lesions was used as a test case. Based on this anatomy, four treatment plans were developed using the following combination of planning systems and delivery machines: a) Precision-CyberKnife (Accuray); b) iPlan-Novalis (BrainLab); c) Raystation (Raysearch Laboratories)-VersaHD (Elekta); and d) Monaco-Versa HD (Elekta). For treatment planning, the UNC treatment protocol for brain multi-lesion cases was followed. However, experience and institution’s policy were used for deviations from the guidelines. The different dose distributions were examined based on their ability to satisfy the specified dose constraints but also their performance regarding dose conformity and organs at risk sparing.
Results: Precision and Raystation had conformity index values of 0.75 and 0.80 satisfying the clinical goal (=0.70), whereas iPlan and Monaco had 0.43 and 0.52. Four of the plans covered all five PTVs as prescribed (V20Gy = 98%) with the exception of Monaco (one lesion had 97.7%). All the plans failed to satisfy the constraint of V12Gy < 10cc for brain minus PTVs (Precision: 21.1cc, iPlan: 47.1cc, Raystation: 32.5cc, Monaco: 56.3cc). All the plans managed to satisfy the constraint of D0.035cc < 15Gy for brainstem (Precision: 14.2cc, iPlan: 13.4cc, Raysation: 14.9cc, Monaco: 15.0cc).
Conclusion: None of the plans satisfied all the requirements of the clinical protocol. However, their deviations were within the range of clinical acceptance. All the plans were comparable in terms of quality. Their main differences stem mainly from the planners’ approach to increase (or not) the level of target coverage against sparing brainstem and brain and less from the platform used (combination of planning system – machine).
Stereotactic Radiosurgery, Brain, Treatment Planning