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An Accurate Linear Model of Tomotherapy MLC-Detector System for Patient Specific Delivery QA

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Y Chen

Y Chen1*, X Mo1 , M Chen1 , G Olivera1 , M Reeher2 , D Parnell1 , S Key1 , D Galmarini3 , W Lu1 , (1) 21st Century Oncology, Madison, WI, (2) 21st Century Oncology, Naples, FL, (3) 21st Century Oncology, Fort Myers, Florida


SU-E-T-475 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system.

A leaf pattern basis (LPB) consisting of no-leaf-open, single-leaf-open, double-leaf-open and triple-leaf-open patterns are chosen to represent linear and major nonlinear effects of leaf fluence as a linear system. An arbitrary leaf pattern can be expressed as (or decomposed to) a linear combination of the LPB either pulse by pulse or weighted by dwelling time. The exit detector responses to the LPB are obtained by processing returned detector signals resulting from the predefined leaf patterns for each jaw setting. Through forward transformation, detector signal can be predicted given a delivery plan. An equivalent leaf open time (LOT) sinogram containing output variation information can also be inversely calculated from the measured detector signals. Twelve patient plans were delivered in air. The equivalent LOT sinograms were compared with their planned sinograms.

The whole calibration process was done in 20 minutes. For two randomly generated leaf patterns, 98.5% of the active channels showed differences within 0.5% of the local maximum between the predicted and measured signals. Averaged over the twelve plans, 90% of LOT errors were within +/-10 ms. The LOT systematic error increases and shows an oscillating pattern when LOT is shorter than 50 ms.

The LPB method models the MLC-detector response accurately, which improves patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is sensitive enough to detect systematic LOT errors as small as 10 ms.

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