A method for deriving a 4D-interpolated balanced planning target for mobile tumor radiotherapy

Tumor control and normal tissue toxicity are strongly correlated to the tumor and normal tissue volumes receiving high prescribed dose levels in the course of radiotherapy. Planning target definition is, therefore, crucial to ensure favorable clinical outcomes. This is especially important for stereotactic body radiation therapy of lung cancers, characterized by high fractional doses and steep dose gradients. The shift in recent years from population-based to patient-specific treatment margins, as facilitated by the emergence of 4D medical imaging capabilities, is a major improvement. The commonly used motion-encompassing, or internal-target volume (ITV), target definition approach provides a high likelihood of coverage for the mobile tumor but inevitably exposes healthy tissue to high prescribed dose levels. The goal of this work was to generate an interpolated balanced planning target that takes into account both tumor coverage and normal tissue sparing from high prescribed dose levels, thereby improving on the ITV approach.

For each 4DCT dataset, 4D deformable image registration was used to derive two bounding targets, namely, a 4D-intersection and a 4D-composite target which minimized normal tissue exposure to high prescribed dose levels and maximized tumor coverage, respectively. Through definition of an "effective overlap volume histogram" the authors derived an "interpolated balanced planning target" intended to balance normal tissue sparing from prescribed doses with tumor coverage. To demonstrate the dosimetric efficacy of the interpolated balanced planning target, the authors performed 4D treatment planning based on deformable image registration of 4D-CT data for five previously treated lung cancer patients. Two 4D plans were generated per patient, one based on the interpolated balanced planning target and the other based on the conventional ITV target. Plans were compared for tumor coverage and the degree of normal tissue sparing resulting from the new approach was quantified.

Analysis of the 4D dose distributions from all five patients showed that while achieving tumor coverage comparable to the ITV approach, the new planning target definition resulted in reductions of lung V(10), V(20), and V(30) of 6.3% ± 1.7%, 10.6% ± 3.9%, and 12.9% ± 5.5%, respectively, as well as reductions in mean lung dose, mean dose to the GTV-ring and mean heart dose of 8.8% ± 2.5%, 7.2% ± 2.5%, and 10.6% ± 3.6%, respectively.

The authors have developed a simple and systematic approach to generate a 4D-interpolated balanced planning target volume that implicitly incorporates the dynamics of respiratory-organ motion without requiring 4D-dose computation or optimization. Preliminary results based on 4D-CT data of five previously treated lung patients showed that this new planning target approach may improve normal tissue sparing without sacrificing tumor coverage.