Gaudreault Mathieu, Yu Kelvin K, Chang David, Kron Tomas, Hardcastle Nicholas, Chander Sarat, Yeo Adam
Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia; Sir Peter MacCallum, Department of Oncology, the University of Melbourne, Victoria 3000, Australia.
Division of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia; Benavides Cancer Institute - University of Santo Tomas Hospital, Manila, Philippines.
Phys Med. 2024 Sep;125:104490. doi: 10.1016/j.ejmp.2024.104490. Epub 2024 Aug 13.
Lattice radiation therapy (LRT) alternates regions of high and low doses inside the tumour. Whilst this technique reported positive results in tumour size reduction, optimal lattice parameters are still unknown. We introduce an automated LRT planning method personalised to tumour shape and designed to allow investigation of lattice geometry.
Patients with retroperitoneal sarcoma were considered for inclusion. Automation was performed with the Eclipse Scripting Application Interface (v16, Varian Medical Systems, Palo Alto). By iterating over vertex size (V) and centre-to-centre distance (D), vertices were segmented within the gross tumour volume (GTV) in an alternating square pattern. Iterations stopped when the number of inserted vertices was contained between a prespecified lower and upper bound. Forty sets of lattices were considered, produced by varying V and D in five lower/upper bound pairs. Best-scoring sets were determined with a score favouring the maximization of GTV dose uniformity and heterogeneity whilst minimizing the maximum dose to organs at risk.
Fifty patients with tumour volumes between 150 cm and 10,000 cm were included. Best-scoring sets were characterised by a low number of vertices (<15). Based on the best-scoring set, the predicted parameters to use for new patients were V = 0.19 (GTV volume) and D = 2V, in centimetres. The number of vertices (N) to insert in the GTV can be estimated with N ≤ (24 × 3% GTV volume)/(4πV).
The automated LRT treatment planning personalised to tumour size allows investigation of lattice geometry over a large range of GTV volumes.
点阵放射治疗(LRT)可在肿瘤内部交替设置高剂量区和低剂量区。尽管该技术在肿瘤体积缩小方面取得了积极成果,但最佳点阵参数仍不明确。我们引入了一种针对肿瘤形状进行个性化设计的自动化LRT计划方法,旨在研究点阵几何结构。
纳入腹膜后肉瘤患者。利用Eclipse脚本应用程序接口(v16,瓦里安医疗系统公司,帕洛阿尔托)实现自动化。通过迭代顶点大小(V)和中心距(D),以交替的方形模式在大体肿瘤体积(GTV)内分割顶点。当插入的顶点数量介于预先指定的下限和上限之间时,迭代停止。考虑了40组点阵,通过在五对下限/上限中改变V和D生成。通过一个分数来确定得分最高的组,该分数有利于最大化GTV剂量均匀性和异质性,同时最小化危及器官的最大剂量。
纳入了50例肿瘤体积在150 cm³至10000 cm³之间的患者。得分最高的组的特点是顶点数量较少(<15个)。基于得分最高的组,预测新患者使用的参数为V = 0.19(GTV体积),D = 2V,单位为厘米。可使用N ≤ (24 × 3% GTV体积)/(4πV)来估计在GTV中插入的顶点数量(N)。
针对肿瘤大小进行个性化的自动化LRT治疗计划能够在大范围的GTV体积上研究点阵几何结构。