A Novel Definition of Equivalent Uniform Dose Based on Volume Dose Curve

With the improvement of mobile device performance, the requirement of equivalent dose description in intensity-modulated radiation therapy is increasing in mobile multimedia for healthcare. The emergence of mobile cloud computing will provide cloud servers and storage for intensity-modulated radiotherapy (IMRT) mobile applications, thus realizing visualized radiotherapy in a real sense. Equivalent uniform dose (EUD) is a biomedical indicator based on the dose measure. In this paper, the dose volume histogram is used to describe the dose distribution of different tissues in target and nontarget regions. The traditional definition of EUD, such as the exponential form and the linear form, has only a few parameters in the model for fast calculation. However, there is no close relationship between this traditional definition and the dose volume histogram. In order to establish the consistency between the EUD and the dose volume histogram, this paper proposes a novel definition of EUD based on the volume dose curve, called VD-EUD. By using a unique organic volume weight curve, it is easy to calculate VD-EUD for different dose distributions. In definition, different weight curves are used to represent the biological effects of different organs. For the target area, we should be more careful about those voxels with a low dose (cold point); thus, the weight curve is monotonically decreasing. While for the nontarget area, the curve is monotonically increasing. Furthermore, we present the curves for parallel, serial, and mixed organs of nontarget areas separately, and we define the weight curve form with only two parameters. Medical doctors can adjust the curve interactively according to different patients and organs. We also propose a fluence map optimization model with the VD-EUD constraint, which means that the proposed EUD constraint will lead to a large feasible solution space. We compare the generalized EUD (gEUD) and the proposed VD-EUD by experiments, which show that the VD-EUD has a closer relationship with the dose volume histogram. If the biological survival probability is equivalent to the VD-EUD, the feasible solution space would be large, and the target areas can be covered. By establishing a personalized organic weight curve, medical doctors can have a unique VD-EUD for each patient. By using the flexible and adjustable EUD definition, we can establish the VD-EUD-based fluence map optimization model, which will lead to a larger solution space than the traditional dose volume constraint-based model. The VD-EUD is a new definition; thus, we need more clinical testing and verification.