title: A method of calculating a lung clinical target volume DVH for IMRT with intrafractional motion.
abstract: The motion of lung tumors from respiration has been reported in the literature to be as large as 1-2 cm. This motion requires an additional margin between the Clinical Target Volume (CTV) and the Planning Target Volume (PTV). In Intensity Modulated Radiotherapy (IMRT), while such a margin is necessary, the margin may not be sufficient to avoid unintended high and low dose regions to the interior on moving CTV. Gated treatment has been proposed to improve normal tissues sparing as well as to ensure accurate dose coverage of the tumor volume. The following questions have not been addressed in the literature: (a) what is the dose error to a target volume without a gated IMRT treatment? (b) What is an acceptable gating window for such a treatment. In this study, we address these questions by proposing a novel technique for calculating the three-dimensional (3-D) dose error that would result if a lung IMRT plan were delivered without a gated linac beam. The method is also generalized for gated treatment with an arbitrary triggering window. IMRT plans for three patients with lung tumors were studied. The treatment plans were generated with HELIOS for delivery with 6 MV on a CL2100 Varian linear accelerator with a 26 pair MLC. A CTV to PTV margin of 1 cm was used. An IMRT planning system searches for an optimized fluence map phi(x,y) for each port, which is then converted into a dynamic MLC file (DMLC). The DMLC file contains information about MLC subfield shapes and the fractional Monitor Units (MUs) to be delivered for each subfield. With a lung tumor, a CTV that executes a quasiperiodic motion z(t) does not receive phi(x,y), but rather an Effective Incident Fluence EIF(x,y). We numerically evaluate the EIF(x,y) from a given DMLC file by a coordinate transformation to the Target's Eye View (TEV). In the TEV coordinate system, the CTV itself is stationary, and the MLC is seen to execute a motion -z(t) that is superimposed on the DMLC motion. The resulting EIF(x,y) is input back into the dose calculation engine to estimate the 3-D dose to a moving CTV. In this study, we model respiratory motion as a sinusoidal function with an amplitude of 10 mm in the superior-inferior direction, a period of 5 s, and an initial phase of zero.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA. jkung@partners.org
authors.forename: J H
authors.initials: JH
authors.lastname: Kung
authors.forename: P
authors.initials: P
authors.lastname: Zygmanski
authors.forename: N
authors.initials: N
authors.lastname: Choi
authors.forename: G T Y
authors.initials: GT
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D016477:Artifacts; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D009068:Movement; D011859:Radiography; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D015203:Reproducibility of Results; D012119:Respiration; D012680:Sensitivity and Specificity