Development and Testing of an Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It mainly refers to the technique that can guide or automate treatment planning in clinic by learning from prior knowledge. Dierent models are developed to realize it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This model can automatically determine both beam conguration and optimization objectives with non-coplanar beams based on patient-specic anatomical information. Although plans automatically generated by this model demonstrate equivalent or better dosimetric quality compared to clinical approved plans, its validity and generality are limited due to the empirical assignment to a coecient called angle spread constraint dened in the beam eciency index used for beam ranking. To eliminate these limitations, a systematic study on this coecient is needed to acquire evidences for its optimal value.;To achieve this purpose, eleven lung cancer patients with complex tumor shape with non-coplanar beams adopted in clinical approved plans were retrospectively studied in the frame of the automatic lung IMRT treatment algorithm. The primary and boost plans used in three patients were treated as dierent cases due to the dierent target size and shape. A total of 14 lung cases, thus, were re-planned using the knowledge-based automatic lung IMRT planning algorithm by varying angle spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good as possible. Important dosimetric parameters for PTV and OARs, quantitatively re ecting the plan quality, were extracted from the DVHs and analyzed as a function of angle spread constraint for each case. Comparisons of these parameters between clinical plans and model-based plans were evaluated by two-sampled Students t-tests, and regression analysis on a composite index built on the percentage errors between dosimetric parameters in the model-based plans and those in the clinical plans as a function of angle spread constraint was performed.;Results show that model-based plans generally have equivalent or better quality than clinical approved plans, qualitatively and quantitatively. All dosimetric param- eters except those for lungs in the automatically generated plans are statistically better or comparable to those in the clinical plans. On average, more than 15% reduction on conformity index and homogeneity index for PTV and V40, V60 for heart while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The intra-plan comparison among model-based plans demonstrates that plan quality does not change much with angle spread constraint larger than 0.4. Further examination on the variation curve of the composite index as a function of angle spread constraint shows that 0.6 is the optimal value that can result in statistically the best achievable plans.