OBJECTIVE: Tumor treating fields (TTFields) with concurrent radiation therapy (RT) might improve the outcome of patients with newly diagnosed glioblastoma. Several trials, including that conducted in our center, have allowed patients to wear TTFields during RT. We aimed to evaluate the setup uncertainty introduced by TTFields and calculate the planning target volume (PTV) margin for clinical reference.
METHODS: We collected and analyzed 201 cone beam computed tomography images of 22 patients in our center. Patients with or without TTFields were divided into the control and TTFields groups. We evaluated the setup errors in 6 degrees of freedom and 3 degrees of freedom and the magnitudes in the 3-dimensional vectors. An estimated PTV margin for patients requiring nonimaging-guided RT was recommended.
RESULTS: A significant difference was observed in the longitudinal axis between the TTFields and control groups (P < .05). These results were consistent with that of the intragroup comparison of the TTFields group. The position error of the longitudinal axis (from head to feet) was -0.51 ± 2.05 mm in the TTFields group.
CONCLUSIONS: Wearing TTFields during RT increased the uncertainty, especially in the longitudinal axis, with a system error of 1.40 mm and a random error of 1.28 mm. Daily image guided RT for TTFields patients seems necessary. However, the recommended expansion margin of the PTV is 5 mm for patients requiring nonimage-guided RT to enhance the safety and efficacy of treatment.

OBJECTIVE: The single isocenter for multiple-target (SIMT) technique has become a popular treatment technique for multiple brain metastases. We have implemented a method to obtain a nonuniform margin for SIMT technique. In this study, we further propose a method to determine the isocenter position so that the total expanded margin volume is minimal.
METHODS: Based on a statistical model, the relationship between nonuniform margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. Due to the existence of rotational error, there is a nonlinear relationship between the margin volume and the isocenter position. Using numerical simulation, we study the relationship between optimal isocenter position and translational error, rotational error, and target size. In order to find the optimal isocenter position quickly, adaptive simulated annealing (ASA) algorithm was used. This method was implemented in the Pinnacle3 treatment planning system and compared with isocenter at center-of-geometric (COG), center-of-volume (COV), and center-of-surface (COS). Ten patients with multiple brain metastasis targets treated with the SIMT technique was selected for evaluation.
RESULTS: When the size of tumors is equal, the optimal isocenter obtained by ASA and numerical simulation coincides with COG, COV, and COS. When the size of tumors is different, the optimal isocenter is close to the large tumor. The position of COS point is closer to the optimal point than the COV point for nearly all cases. Moreover, in some cases the COS point can be approximately selected as the optimal point. The ASA algorithm can reduce the calculating time from several hours to tens of seconds for three or more tumors. Using multiple brain metastases targets, a series of volume difference and calculating time were obtained for various tumor number, tumor size, and separation distances. Compared with the margin volume with isocenter at COG, the margin volume for optimal point can be reduced by up to 27.7%.
CONCLUSIONS: Optimal treatment isocenter selection of multiple targets with large differences could reduce the total margin volume. ASA algorithm can significantly improve the speed of finding the optimal isocenter. This method can be used for clinical isocenter selection and is useful for the protection of normal tissue nearby.

OBJECTIVE: In this work, we implemented a method to obtain a nonuniform clinical target volume (CTV) to planning target volume (PTV) margin caused by both rotational and translational uncertainties and evaluated it in the treatment planning system (TPS).
METHODS: Based on a previously published statistical model, the relationship between a target margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. For a single CTV, it can be thought as a combination of many small volume elements or target points. The margin of each point could be obtained using the suggested statistical model. The whole nonuniform CTV-PTV margin was determined by the union of all possible margins of the CTV boundary points. This method was implemented in the Pinnacle3 treatment planning system and compared with uniform margin algorithm. Ten vertebral metastases targets and multiple brain metastases targets were chosen for evaluation.
RESULTS: The combined CTV-PTV margin as a function of d for various initial translational margin and rotational uncertainties was calculated. The combined margin increases as d, rotational uncertainties and translational margin increase. For the same rotational uncertainty, a smaller initial translational margin requires a larger rotational margin to compensate for the rotational error. Compared with the uniform margin algorithm, the advantage of this method is that it could minimize the PTVs volume for given CTVs to obtain same significance level. Using vertebral metastases targets and multiple brain metastases targets, a series of volume difference was obtained for various translational margins and rotational uncertainties. The volume difference of PTV could be more than 17% when translational margin is 2 mm and rotational uncertainty is 1.4°.
CONCLUSIONS: Nonuniform margin algorithm could avoid excessive compensation for the CTV boundary points near isocenter. This method could be used for clinical margin determination and might be useful for the protection of risk organs.