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SU‐FF‐J‐03: Real Time Motion Adaptive Delivery—Experimental Validation
Author(s) -
Mauer C,
Lu W,
Lucas D,
Zhang J,
Olivera G,
Ruchala K
Publication year - 2007
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2760508
Subject(s) - tomotherapy , imaging phantom , trajectory , motion (physics) , dosimetry , computer science , physics , nuclear medicine , computer vision , optics , medicine , radiation therapy , radiology , astronomy
Purpose: A real time motion adaptive delivery (MAD) technique to compensate for the effects of intra‐fraction respiratory motion in TopoTherapy/TomoTherapy delivery was developed. This technique was evaluated using dosimetric measurements on a TomoTherapy machine with a motion phantom. Methods: Motion adaptive delivery is a technique that re‐uses the planned sinogram by shuffling its projection and leaf indices, based on instantaneous target position. MAD can be implemented using commercial TomoTherapy systems without hardware modifications. A standard helical plan on a stationary phantom is compared to the same plan on a moving phantom, and a motion adaptive delivery on a moving phantom. The dosimetric differences are measured by delivering plans to film placed on a synchronized motion phantom. The experiment is repeated for different target volume shapes and motion directions. Results: We measured the MAD to be within 2% of dose of a regular treatment delivered to a stationary phantom. These results are consistent for different IMRT target shapes (spherical, ellipsoid, saddle‐shaped), target motions (lateral, inferior‐superior), and field sizes (1.0 and 2.5 cm). Discussions and Conclusions: We present an experimental validation measuring the effects of intra‐fraction motion on helical TomoTherapy plans compared to Motion Adaptive Delivery (MAD). The dose measured in motion adaptive deliveries is within 2% of a regular helical treatment dose to a stationary target.