Reduced-order constrained optimization (ROCO): Clinical application to head-and-neck IMRT Journal Article


Authors: Rivera, L.; Yorke, E.; Kowalski, A.; Yang, J.; Radke, R. J.; Jackson, A.
Article Title: Reduced-order constrained optimization (ROCO): Clinical application to head-and-neck IMRT
Abstract: Purpose: The authors present the application of the reduced order constrained optimization (ROCO) method, previously successfully applied to the prostate and lung sites, to the head-and-neck (HN) site, demonstrating that it can quickly and automatically generate clinically competitive IMRT plans. We provide guidelines for applying ROCO to larynx, oropharynx, and nasopharynx cases, and report the results of a live experiment that demonstrates how an expert planner can save several hours of trial-and-error interaction using the proposed approach. Methods: The ROCO method used for HN IMRT planning consists of three major steps. First, the intensity space of treatment plans is sampled by solving a series of unconstrained optimization problems with a parameter range based on previously treated patient data. Second, the dominant modes in the intensity space are estimated by dimensionality reduction using principal component analysis (PCA). Third, a constrained optimization problem over this basis is quickly solved to find an IMRT plan that meets organ-at-risk (OAR) and target coverage constraints. The quality of the plan is assessed using evaluation tools within Memorial Sloan-Kettering Cancer Center (MSKCC)'s treatment planning system (TPS). Results: The authors generated ten HN IMRT plans for previously treated patients using the ROCO method and processed them for deliverability by a dynamic multileaf collimator (DMLC). The authors quantitatively compared the ROCO plans to the previously achieved clinical plans using the TPS tools used at MSKCC, including DVH and isodose contour analysis, and concluded that the ROCO plans would be clinically acceptable. In our current implementation, ROCO HN plans can be generated using about 1.6 h of offline computation followed by 5-15 min of semiautomatic planning time. Additionally, the authors conducted a live session for a plan designated by MSKCC performed together with an expert HN planner. A technical assistant set up the first two steps, which were performed without further human interaction, and then collaborated in a virtual meeting with the expert planner to perform the third (constrained optimization) step. The expert planner performed in-depth analysis of the resulting ROCO plan and deemed it to be clinically acceptable and in some aspects superior to the clinical plan. This entire process took 135 min including two constrained optimization runs, in comparison to the estimated 4 h that would have been required using traditional clinical planning tools. Conclusions: The HN site is very challenging for IMRT planning, due to several levels of prescription and a large, variable number (6-20) of OARs that depend on the location of the tumor. ROCO for HN shows promise in generating clinically acceptable plans both more quickly and with substantially less human interaction. © 2013 American Association of Physicists in Medicine.
Keywords: intensity modulated radiation therapy; treatment planning; cancer radiotherapy; radiation dose; methodology; head and neck cancer; imrt; head and neck neoplasms; radiotherapy, intensity-modulated; radiotherapy planning, computer-assisted; computer assisted radiotherapy; dose calculation; head and neck tumor; multileaf collimator; principal component analysis; radiological parameters; constrained optimization; dimensionality reduction; head-and-neck; reduced order constrained optimization method
Journal Title: Medical Physics
Volume: 40
Issue: 2
ISSN: 0094-2405
Publisher: American Association of Physicists in Medicine  
Date Published: 2013-02-01
Start Page: 021715
Language: English
DOI: 10.1118/1.4788653
PROVIDER: scopus
PUBMED: 23387738
PMCID: PMC3574081
DOI/URL:
Notes: --- - "Export Date: 1 March 2013" - "CODEN: MPHYA" - "Source: Scopus"
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MSK Authors
  1. Andrew Jackson
    253 Jackson
  2. Ellen D Yorke
    450 Yorke
  3. Jie Yang
    50 Yang