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A Collimator-Based 3-Dimensional Grid Therapy Technique in a Small Animal Radiation Research Platform

J Jin

J Jin1*, V Kong1 , H Zhang1 , (1) Georgia Regents University, Augusta, GA,


SU-F-T-508 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Three dimensional (3D) Grid Therapy using MLC-based inverse-planning has been proposed to achieve the features of both conformal radiotherapy and spatially fractionated radiotherapy, which may deliver very high dose in a single fraction to portions of a large tumor with relatively low normal tissue dose. However, the technique requires relatively long delivery time. This study aims to develop a collimator-based 3D grid therapy technique. Here we report the development of the technique in a small animal radiation research platform.

Methods: Similar as in the MLC-based technique, 9 non-coplanar beams in special channeling directions were used for the 3D grid therapy technique. Two specially designed grid collimators were fabricated, and one of them was selectively used to match the corresponding gantry/couch angles so that the grid opening of all 9 beams are met in the 3D space in the target. A stack of EBT3 films were used as 3D dosimetry to demonstrate the 3D grid-like dose distribution in the target. Three 1-mm beams were delivered to the stack of films in the area outside the target for alignment when all the films were scanned to reconstruct the 3D dosimtric image.

Results: 3D film dosimetry showed a lattice-like dose distribution in the 3D target as well as in the axial, sagittal and coronal planes. The dose outside the target also showed a grid like dose distribution, and the average dose gradually decreased with the distance to the target. The peak to valley ratio was approximately 5:1. The delivery time was 7 minutes for 18 Gy peak dose, comparing to 6 minutes to deliver a 18-Gy 3D conformal plan.

Conclusion: We have demonstrated the feasibility of the collimator-based 3D grid therapy technique which can significantly reduce delivery time comparing to MLC-based inverse planning technique.

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