Program Information

PTV Margin Determination Based On Tumor Radiobiological Characteristics and Geometric Uncertainties Derived From Daily Cone-Beam CT Images

J Selvaraj

J Selvaraj*, Inlaks & Budhrani Hospital, India

Presentations

SU-C-BRE-5 Sunday 1:00PM - 1:55PM Room: Ballroom E

Purpose:To determine required PTV margins for ≤1% loss in mean population TCP using systematic (Σ) and random (σ) errors calculated from daily cone-beam CT (CBCT) images of head and neck patients.

Methods:Daily CBCT images were acquired for 50 head and neck patients. The CBCT image sets acquired at each fraction were registered with planning CT to obtain positional errors for each patient for each fraction. Systematic and random errors were calculated from data collected for 50 patients as described in IPEM On Target report. CTV delineation uncertainty of 2mm is added quadratically to systematic error. Assuming a spherical target volume, the dose in each voxel of target volume is summed for each fraction in the treatment by shifting the dose grid to calculate mean population TCP inclusive of geometric uncertainties using a Monte Carlo method. These simulations were repeated for the set of Σ & σ in each axis for different PTV margins and drop in TCP for each margin are obtained. In order to study the effect of dose-response curve on PTV margins, two different σα of 0.048 Gy-1 and 0.218 Gy-1 representing steep and shallow dose-response curves are studied. Σ were 2.5, 2.5, 2.1 mm and σ were 0.3, 0.3 0.2 mm respectively in x, y and z axis respectively.

Results:PTV margins based on tumor radiobiological characteristics are 4.8, 4.8 and 4 mm in x, y and z axis assuming 25 treatment fractions for σα 0.048 Gy-1 (steep) and 4.2,4.2 and 2.2 for σα of 0.218 Gy-1 (shallow). While the TCP-based margins did not differ much in x and y axis, it is considerably smaller in z axis for shallow DRC.

Conclusion:TCP based margins are substantially smaller than physical dose-based margin recipes. This study also demonstrates the importance of considering tumor radiobiological characteristics while deriving margins.


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