Development of an automated treatment planning approach for lattice radiation therapy
Background: Lattice radiation therapy (LRT) alternates regions of high and low doses within the target. The heterogeneous dose distribution is delivered to a geometrical structure of vertices segmented inside the tumor. LRT is typically used to treat patients with large tumor volumes with cytoreduction intent. Due to the geometric complexity of the target volume and the required dose distribution, LRT treatment planning demands additional resources, which may limit clinical integration. Purpose: We introduce a fully automated method to (1) generate an ordered lattice of vertices with various sizes and center-to-center distances and (2) perform dose optimization and calculation. We aim to report the dosimetry associated with these lattices to help clinical decision-making. Methods: Sarcoma cancer patients with tumor volume between 100 cm3 and 1500 cm3 who received radiotherapy treatment between 2010 and 2018 at our institution were considered for inclusion. Automated segmentation and dose optimization/calculation were performed by using the Eclipse Scripting Application Programming Interface (ESAPI, v16, Varian Medical Systems, Palo Alto, USA). Vertices were modeled by spheres segmented within the gross tumor volume (GTV) with 1 cm/1.5 cm/2 cm diameters (LRT-1 cm/1.5 cm/2 cm) and 2 to 5 cm center-to-center distance on square lattices alternating along the superior-inferior direction. Organs at risk were modeled by subtracting the GTV from the body structure (body-GTV). The prescription dose was that 50% of the vertice volume should receive at least 20 Gy in one fraction. The automated dose optimization included three stages. The vertices optimization objectives were refined during optimization according to their values at the end of the first and second stages. Lattices were classified according to a score based on the minimization of body-GTV max dose and the maximization of GTV dose uniformity (measured with the equivalent uniform dose [EUD]), GTV dose heterogeneity (measured with the GTV D90%/D10% ratio), and the number of patients with more than one vertex inserted in the GTV. Plan complexity was measured with the modulation complexity score (MCS). Correlations were assessed with the Spearman correlation coefficient (r) and its associated p-value. Results: Thirty-three patients with GTV volumes between 150 and 1350 cm3 (median GTV volume = 494 cm3, IQR = 272–779 cm3 were included. The median time required for segmentation/planning was 1 min/21 min. The number of vertices was strongly correlated with GTV volume in each LRT lattice for each center-to-center distance (r > 0.85, p-values < 0.001 in each case). Lattices with center-to-center distance = 2.5 cm/3 cm/3.5 cm in LRT-1.5 cm and center-to-center distance = 4 cm in LRT-1 cm had the best scores. These lattices were characterized by high heterogeneity (median GTV D90%/D10% between 0.06 and 0.19). The generated plans were moderately complex (median MCS ranged between 0.19 and 0.40). Conclusions: The automated LRT planning method allows for the efficacious generation of vertices arranged in an ordered lattice and the refinement of planning objectives during dose optimization, enabling the systematic evaluation of LRT dosimetry from various lattice geometries.
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