Abstract

<h3>Purpose/Objective(s)</h3> Treatment planning for locally advanced non-small cell lung cancer (NSCLC) has always been challenging due to the variabilities of the planning target volume (PTV) and competing constraints of organs at risk such as lung, cord, esophagus, and heart. We share our experience in developing a fully automatic treatment planning solution for NSCLC. <h3>Materials/Methods</h3> Automated plans for NSCLC radiotherapy patients with static IMRT fields were designed using an in-house-developed automated planning system named Expedited Constrained Hierarchical Optimization (ECHO) which is integrated into the treatment planning system (TPS) using API scripting. ECHO does not use TPS optimization algorithms, but utilizes TPS leaf sequencing and final dose calculation. ECHO applies advanced optimization tools (such as hierarchical constrained optimization, convex approximations and Lagrangian methods) to produce Pareto optimal plans that meet clinical constraints and improve desired clinical objectives as much as possible. ECHO optimization parameters were tuned with 29 NSCLC patients and validated retrospectively using 113 NSCLC patients treated with prescription doses including conventional (1.8Gy-2Gy x 25-35 fractions) and hypofractionation (2.75Gy-4Gy x 10-20 fractions). Clinically treated plans were created manually using either static IMRT or VMAT. Automated plans were created using static IMRT fields with beam templates based on the location of PTV within the lung. Dosimetric metrics were evaluated with respect to tumor coverage and normal tissue sparing. <h3>Results</h3> PTV sizes ranged from 64cc to 2297cc (median 292cc). Median planning time for ECHO was 23 minutes (range: 8min-78min). Both manual and ECHO plans met all established clinical criteria. Compared with manual plans, ECHO plans produced significantly improved and more consistent PTV coverage and better sparing of esophagus, heart and cord while maintaining similar lung doses (Table 1). <h3>Conclusion</h3> An automated and clinical-criteria-driven treatment planning system has been validated and clinically implemented in our institution for NSCLC radiotherapy. Use of automation improves efficiency, plan consistency and quality for NSCLC treatment planning.

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