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 (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPESC=D-B-D-A and OCESC=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 DPESC in the GTV D-98 varied from -1.9% to -4.9%, while the OCESC ranged from 0.9% to 7.0%. The DPESC in the contralateral parotid D-50 reached 8.2%, while the OCESC in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPESC in cord D-2 reached -3.0%, while the OCESC reached to -7.0%. The magnitude of the DPESC and OCESC 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. (c) 2006 American Association of Physicists in Medicine.