|Methods and Materials: Inverse treatment planning for
hypothetical lung gross tumor volumes (GTV) and planned treatment
volume (PTV) expansions were performed. We tested the hypothesis
that the maximum acceptable dose (MAD) to be delivered to the lesion
by SBRT could be predicted by PTV and lung volume. Dose constraints
on normal tissue were as designated by the RTOG protocol. Inverse
planning was performed to find the maximum tolerated SBRT dose up to
Plans were run with the goal of delivering a MAD between 30–60 Gy. This was defined as the maximal dose to be delivered to the tumor while still meeting several of the normal tissue constraints defined by the Radiation Therapy Oncology Group (RTOG) 0236 protocol. These constraints are as follows: for the heart, trachea, and ipsilateral bronchus, a 30-Gy maximum point dose; for the esophagus, a 27-Gy maximum point dose; for the brachial plexus, a 24-Gy maximum point dose; and for the spinal cord, an 18-Gy maximum point dose. In regard to lung dose constraints, for no deviation, the V20 must be <10%. For a minor protocol deviation, the volume of lung receiving 20 Gy (V20) was required to be restricted to <15%. Both constraints were used in this study to create separate predictive equations. As iterations were run for each plan, doses were increased or decreased by multiples of 3 Gy until the MAD was achieved. Doses were prescribed to cover 95% of the PTV. A 2.5-cm jaw width was used for all plans.
Results: Regression analysis of the data obtained indicated a linear relationship between MAD, PTV, and lung volume. This generated two equations which may be useful predictive tools. Seven patients with Stage I and II NSCLC treated at the University of Virginia with this method tolerated the treatment extremely well, and suffered no greater than grade I toxicity, with no evidence of disease recurrence in follow-up from 2–20 months.
Conclusions: Helical tomotherapy SBRT for lung lesions is well-tolerated. In addition, the likely MAD for patients considered for this type of treatment can be predicted by PTV and lung volume.