Four-dimensional targeting error analysis in image-guided radiotherapy.

Image-guided therapy (IGT) involves acquisition and processing of biomedical images to actively guide medical interventions. The proliferation of IGT technologies has been particularly significant in image-guided radiotherapy (IGRT), as a way to increase the tumor targeting accuracy. When IGRT is applied to moving tumors, image guidance becomes challenging, as motion leads to increased uncertainty. Different strategies may be applied to mitigate the effects of motion: each technique is related to a different technological effort and complexity in treatment planning and delivery. The objective comparison of different motion mitigation strategies can be achieved by quantifying the residual uncertainties in tumor targeting, to be detected by means of IGRT technologies. Such quantification requires an extension of targeting error theory to a 4D space, where the 3D tumor trajectory as a function of time measured (4D Targeting Error, 4DTE). Accurate 4DTE analysis can be represented by a motion probability density function, describing the statistical fluctuations of tumor trajectory. We illustrate the application of 4DTE analysis through examples, including weekly variations in tumor trajectory as detected by 4DCT, respiratory gating via external surrogates and real-time tumor tracking.

Design and testing of a simulation framework for dosimetric motion studies integrating an anthropomorphic computational phantom into four-dimensional Monte Carlo.

We have designed a simulation framework for motion studies in radiation therapy by integrating the anthropomorphic NCAT phantom into a 4D Monte Carlo dose calculation engine based on DPM. Representing an artifact-free environment, the system can be used to identify class solutions as a function of geometric and dosimetric parameters. A pilot dynamic conformal study for three lesions ( approximately 2.0 cm) in the right lung was performed (70 Gy prescription dose). Tumor motion changed as a function of tumor location, according to the anthropomorphic deformable motion model. Conformal plans were simulated with 0 to 2 cm margin for the aperture, with additional 0.5 cm for beam penumbra. The dosimetric effects of intensity modulated radiotherapy (IMRT) vs. conformal treatments were compared in a static case. Results show that the Monte Carlo simulation framework can model tumor tracking in deformable anatomy with high accuracy, providing absolute doses for IMRT and conformal radiation therapy. A target underdosage of up to 3.67 Gy (lower lung) was highlighted in the composite dose distribution mapped at exhale. Such effects depend on tumor location and treatment margin and are affected by lung deformation and ribcage motion. In summary, the complexity in the irradiation of moving targets has been reduced to a controlled simulation environment, where several treatment options can be accurately modeled and quantified The implemented tools will be utilized for extensive motion study in lung/liver irradiation.

A method of calculating a lung clinical target volume DVH for IMRT with intrafractional motion.

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.