Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system. Issue 7 (29th May 2019)

• Record Type: Journal Article
• Authors: Zarepisheh, Masoud; Hong, Linda; Zhou, Ying; Oh, Jung Hun; Mechalakos, James G.; Hunt, Margie A.; Mageras, Gig S.; Deasy, Joseph O.
• Is Part Of: Medical physics. Volume 46:Issue 7(2019)
• Page Start: 2944
• Page End: 2954
• Publication Date: 2019-05-29
• Subjects: automated planning -- hierarchical optimization -- IMRT; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.13572
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning. Method: The optimization algorithm is developed based on a hierarchical constrained optimization technique and is referred internally at our institution as expedited constrained hierarchical optimization (ECHO). Beamlet contributions to regions‐of‐interest are precomputed and captured in the influence matrix. Planning goals are of two classes: hard constraints that are strictly enforced from the first step (e.g., maximum dose to spinal cord), and desirable goals that are sequentially introduced in three constrained optimization problems (better planning target volume (PTV) coverage, lower organ at risk (OAR) doses, and smoother fluence map). After solving the optimization problems using external commercial optimization engines, the optimal fluence map is imported into an FDA‐approved treatment planning system (TPS) for leaf sequencing and accurate full dose calculation. The dose‐discrepancy between the optimization and TPS dose calculation is then calculated and incorporated into optimization by a novel dose correction loop technique using Lagrange multipliers. The correction loop incorporates the leaf sequencing and scattering effects into optimization to improve the plan quality and reduce the calculation time. The resultant optimal fluence map is again imported into TPS for leaf sequencing and final dose calculation for plan evaluation and delivery. The workflow is automated using application program interface (API) scripting, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug‐in from the TPS. For each site, parameters and objective functions are chosen to represent clinical priorities. The first site chosen for clinical implementation was metastatic paraspinal lesions treated with stereotactic body radiotherapy (SBRT). As a first step, 75 ECHO paraspinal plans were generated retrospectively and compared with clinically treated plans generated by planners using VMAT (volumetric modulated arc therapy) with 4 to 6 partial arcs. Subsequently, clinical deployment began in April, 2017. Results: In retrospective study, ECHO plans were found to be dosimetrically superior with respect to tumor coverage, plan conformity, and OAR sparing. For example, the average PTV D95%, cord and esophagus max doses, and Paddick Conformity Index were improved, respectively, by 1%, 6%, 14%, and 15%, at a negligible 3% cost of the average skin D10cc dose. Conclusion: Hierarchical constrained optimization is a powerful and flexible tool for automated IMRT treatment planning. The dosimetric correction step accurately accounts for detailed dosimetric multileaf collimator and scattering effects. The system produces high‐quality, Pareto optimal plans and avoids the time‐consuming trial‐and‐error planning process.