Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization- convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SC_opt), B: an SC_opt plan recalculated with Monte Carlo [MC (SC_opt)], and C: an MC optimized plan (MC_opt). For each structure, DPEs and OCEs were estimated as DPE_SC = D^B - D^A and OCE _SC = D^C - D^B where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE_SC in the GTV D₉₈ varied from -1.9% to -4.9%, while the OCE_SC ranged from 0.9% to 7.0%. The DPE_SC in the contralateral parotid D ₅₀ reached 8.2%, while the OCE_SC in the contralateral parotid D₅₀ varied from 0.91% to 6.99%. The DPE_SC in cord D₂ reached -3.0%, while the OCE_SC reached to -7.0%. The magnitude of the DPE_SC and OCE_SC differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.