title: Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients.
abstract: 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 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 D50 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.
authors.affiliation: Radiation Oncology Department, Virginia Commonwealth University Medical Center, 401 College Street, Richmond, Virginia 23298, USA. ndogan@vcu.edu
authors.forename: Nesrin
authors.initials: N
authors.lastname: Dogan
authors.forename: Jeffery V
authors.initials: JV
authors.lastname: Siebers
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
authors.forename: Fritz
authors.initials: F
authors.lastname: Lerma
authors.forename: Yan
authors.initials: Y
authors.lastname: Wu
authors.forename: Mirek
authors.initials: M
authors.lastname: Fatyga
authors.forename: Jeffrey F
authors.initials: JF
authors.lastname: Williamson
authors.forename: Rupert K
authors.initials: RK
authors.lastname: Schmidt-Ullrich
mesh_terms: D000465:Algorithms; D001822:Body Burden; D002294:Carcinoma, Squamous Cell / Q000503:physiopathology / Q000532:radiotherapy*; D003198:Computer Simulation; D006258:Head and Neck Neoplasms / Q000503:physiopathology / Q000532:radiotherapy*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D012062:Relative Biological Effectiveness