Automated Lattice Technique-Based Algorithm for High-Dose Sphere Distribution in Radiotherapy

The treatment of bulky tumors with conventional radiotherapy is limited by the need for higher therapeutic doses, which can increase toxicity to healthy tissues and fail to exploit tumor heterogeneity. In this context, Lattice radiotherapy emerges as an innovative approach, focusing on heterogeneous partial irradiation that alternates areas of high dose, known as vertices, with lower dose zones. This method promotes immunogenic cell death in the vertices, releasing antigens and inflammatory cytokines that enhance immune system activation while reducing radiation exposure to at-risk organs and modulating the dose in areas of the tumor that are less radio-sensitive, such as hypoxic or necrotic zones. To facilitate the implementation of this technique, a Lattice-based algorithm has been developed to automate the generation and three-dimensional distribution of the vertices within the tumor volume, using DICOM RT files that contain CT images and anatomical segmentations. The developed algorithm allows for the adjustment of parameters such as the diameter and spacing of the vertices, as well as the ability to remove or modify their locations, thus optimizing the protection of surrounding organs. All of this is presented in an intuitive and interoperable graphical user interface, enabling the integration of the generated spheres into radiotherapy planning systems.Clinical RelevanceThis Lattice-based algorithm offers radiation oncologists a clinically significant tool for optimizing treatment by tailoring high-dose sphere distributions within the target tumor volume. It determines sphere diameters, defines boundaries between spheres and the target contour, and allows for adjustments such as redistributing, resizing, or removing spheres. Notably, the algorithm facilitates these adjustments not only in two-dimensional planes, where such modifications are relatively straightforward, but also in three-dimensional space, addressing the complexities that arise when working across multiple axes. This enhanced precision enables more effective tumor coverage while sparing healthy tissue, leading to improved therapeutic outcomes and enhanced patient quality of life.