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Report No. 329 - AAPM Task Group 329: Reference dose specification for dose calculations: dose-to-water or dose-to-muscle? (2019)

Category: Reports

Linac calibration is done in water, but patients are comprised primarily of soft-tissue. Conceptually, and specified in NRG/RTOG trials, dose should be reported as dose-to-muscle to describe the dose to the patient. Historically, the dose-to-water of the linac calibration was often converted to dose-to-muscle for patient calculations through manual application of a 0.99 dose-to-water to dose-to-muscle correction factor, applied during the linac clinical reference calibration. However, many current treatment planning system (TPS) dose calculation algorithms approximately provide dose-to-muscle (tissue), making application of a manual scaling unnecessary. There is little guidance on when application of a scaling factor is appropriate, resulting in highly inconsistent application of this scaling by the community. In this report we provide guidance on the steps necessary to go from the linac absorbed dose-to-water calibration to dose-to-muscle in patient, for various commercial treatment planning system algorithms. If the treatment planning system does not account for the difference between dose-to-water and dose-to-muscle, then TPS reference dose scaling is warranted. We have tabulated the major vendors’ TPS in terms of whether they approximate dose-to-muscle or calculate dose-to-water and recommend the correction factor required to report dose-to-muscle directly from the treatment planning system algorithm. Physicists should use this report to determine the applicable correction required for specifying the reference dose in their TPS to achieve this goal and should remain attentive to possible changes to their dose calculation algorithm in the future.

Medical Physics

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Task Group No. 329 - AAPM report on reference dose specification for dose calculations: dose-to-water or dose-to-muscle (TG329)

Stephen Kry, Vladimir Feygelman, Peter Balter, Tom Knöös, Chang Ming Charlie Ma, Michael Snyder, Brian Tonner, Oleg Vassiliev

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