Click here to


Are you sure ?

Yes, do it No, cancel

Automated IMRT Treatment Planning Using Expedited Constrained Hierarchical Optimization (ECHO): Retrospective Study and Clinical Implementation

M Zarepisheh*, L Hong , Y Zhou , J Oh , J Mechalakos , M Hunt , G Mageras , J Deasy , Memorial Sloan-Kettering Cancer Center, New York, NY


(Wednesday, 8/1/2018) 10:15 AM - 12:15 PM

Room: Davidson Ballroom A

Purpose: To develop and clinically implement a fully automated approach to IMRT treatment planning using in-house-developed optimization algorithm and the Eclipse API scripting.

Methods: Eclipse API serves to pull patient data needed for optimization. An optimization algorithm is developed based on the well-known hierarchical constrained optimization technique and is reffered to internally at our institution as ECHO. The clinical criteria requirements are formulated as hard constraints so they are strictly enforced by the optimization. Other clinical criteria defined as desirable (e.g., better PTV coverage, lower critical organs’ doses) are optimized as much as possible by solving three sequential constrained optimization problems. The algorithm is equipped with a novel correction loop technique using Lagrangian multipliers to speed up the optimization process and incorporate leaf sequencing and scattering impacts. After solving the optimization problems using a commercial optimization engine (knitro), the optimal fluence map is imported back into Eclipse using API for leaf sequencing and final dose calculation. The entire aforementioned workflow is automated, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug-in from Eclipse. For each site, parameters and objective functions are chosen to represent clinical priorities. We have first implemented ECHO for paraspinal metastatic lesion patients.

Results: ECHO plans for 63 paraspinal patients were generated retrospectively and they were more consistent and dosimetrically superior compared to the manually created plans. After a successfull retrospicive study, we have implemented ECHO clinically since April 2017 and generated clinical plans for over 300 patients in 9 months. ECHO required ~1-2 hours to generate a plan and all ECHO plans met or exceeded our institution’s planning criteria.

Conclusion: ECHO, provided as an Eclipse API plug-in, enables fully automated IMRT treatment planning that is Pareto optimal. ECHO saves time and resources and improves plan quality and consistency.


Optimization, Inverse Planning, Target Localization


TH- External beam- photons: IMRT dose optimization algorithms

Contact Email