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Evaluation Study
Journal Article
Evaluation of a dedicated brain metastases treatment planning optimization for radiosurgery: a new treatment paradigm?
Radiation Oncology 2016 Februrary 3
PURPOSE: To investigate the feasibility of a novel dedicated treatment planning solution, to automatically target multiple brain metastases with a single isocenter and multiple inversely-optimized dynamic conformal arcs (DCA), and to benchmark it against the well-established multiple isocenter DCA (MIDCA) and volumetric modulated arc therapy (VMAT) approaches.
MATERIAL AND METHODS: Ten previously treated patients were randomly selected, each representing a variable number of lesions ranging between 1 to 8. The original MIDCA treatments were replanned with both VMAT and the novel brain metastases tool. The plans were compared by means of Paddick conformity (CI) and gradient index (GI), and the volumes receiving 10 Gy (V10) and 12 Gy (V12).
RESULTS: The brain metastases software tool generated plans with similar CI (0.65 ± 0.08) as both established treatment techniques while improving the gradient (mean GI = 3.9 ± 1.4). The normal tissue exposure in terms of V10 (48.5 ± 35.9 cc) and V12 (36.3 ± 27.1 cc) compared similarly to the MIDCA technique and surpassed VMAT plans.
CONCLUSIONS: The automated brain metastases planning algorithm software is an optimization of DCA radiosurgery by increasing delivery efficiency to the level of VMAT approaches. Improving dose gradients and normal tissue sparing over VMAT, revives DCA as the paradigm for linac-based stereotactic radiosurgery of multiple brain metastases.
MATERIAL AND METHODS: Ten previously treated patients were randomly selected, each representing a variable number of lesions ranging between 1 to 8. The original MIDCA treatments were replanned with both VMAT and the novel brain metastases tool. The plans were compared by means of Paddick conformity (CI) and gradient index (GI), and the volumes receiving 10 Gy (V10) and 12 Gy (V12).
RESULTS: The brain metastases software tool generated plans with similar CI (0.65 ± 0.08) as both established treatment techniques while improving the gradient (mean GI = 3.9 ± 1.4). The normal tissue exposure in terms of V10 (48.5 ± 35.9 cc) and V12 (36.3 ± 27.1 cc) compared similarly to the MIDCA technique and surpassed VMAT plans.
CONCLUSIONS: The automated brain metastases planning algorithm software is an optimization of DCA radiosurgery by increasing delivery efficiency to the level of VMAT approaches. Improving dose gradients and normal tissue sparing over VMAT, revives DCA as the paradigm for linac-based stereotactic radiosurgery of multiple brain metastases.
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