Improved critical structure sparing with biologically based IMRT optimization. Med Phys 2009 May;36(5):1790-9
Date
06/24/2009Pubmed ID
19544798DOI
10.1118/1.3116775Scopus ID
2-s2.0-65449178789 (requires institutional sign-in at Scopus site) 47 CitationsAbstract
The impact of using biological models in treatment planning on plan quality is studied by comparing IMRT plans generated using selected commercially available treatment planning systems (TPSs) employing biological models/quantities in IMRT optimization (bIMRT) and the conventional physically (dose-volume) based optimization (pIMRT). A total of 25 IMRT plans, generated for five cases of different anatomic sites (brain, head and neck, lung, pancreas, and prostate) using five TPSs, two bIMRT (CMS Monaco and Phillips Pinnacle3 P3IMRT) and three pIMRT (CMS Xio, Phillips Pinnacle3, and Tomotherapy) systems, were compared. Dose-volume histograms, maximum, minimum, and mean doses, target heterogeneity and conformity indices, equivalent uniform dose (EUD), and an overall plan-ranking index (fEUD) were used in the comparison. It is clear from the comparison that the use of biological models in treatment planning optimization can generate IMRT plans with significantly improved normal tissue sparing with similar or slightly increased dose heterogeneity in the target, as compared to the conventional dose-volume based optimization for the same beam arrangement. For example, the bIMRT plans lead to smaller EUDs in 32 out of 37 normal structures in all five cases combined, as compared to the pIMRT plans. Caution should be exercised in choosing appropriate models and/or model parameters and in evaluating the plan obtained when using the biologically based treatment planning system.
Author List
Qi XS, Semenenko VA, Li XAMESH terms used to index this publication - Major topics in bold
Computer SimulationHumans
Models, Biological
Neoplasms
Radiation Injuries
Radiation Protection
Radiometry
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Conformal
Reproducibility of Results
Sensitivity and Specificity
