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Improved critical structure sparing with biologically based IMRT optimization

1. Improved critical structure sparing with biologically based IMRT optimization. X.Sharon Qi, Vladimir A. Semenenko and X. Allen Li Department of Radiation Oncology, Medical College of Wisconsin. Introduction.

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Improved critical structure sparing with biologically based IMRT optimization

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  1. 1 Improved critical structure sparing with biologically based IMRT optimization • X.Sharon Qi, Vladimir A. Semenenko and X. Allen Li • Department of Radiation Oncology, Medical College of Wisconsin

  2. Introduction • DVH based algorithm ignore the nonlinear dose response of both tumor and normal structure • Dose-based optimization is insufficient to predict any biological end point of radiotherapy • Biologically based radiation treatment planning can substantially improve the quality of the plan generated

  3. Purpose • to study the impact of using biological models on plan quality by evaluating commercially available treatment planning systems

  4. Methods and materials

  5. A. TPS • TPS: CMS (Monaco, XiO) • Philips Pinnacle • Tomotherapy

  6. Biological objective functions in TPS

  7. Physical objective functions

  8. B. Study design • Five clinical cases: brain, H&N, lung, pancreas and prostate • The original treatment plans were generated by using XiO or Tomotherapy • Two physically based IMRT(pIMRT) and two biologically based (bIMRT) plans were generated for each cases utilizing different TPSs • Same planning CT and structure set • Same beam numbers and orientations

  9. Fix angles: • pIMRT: XiO (XiO) • pIMRT: Pinnacle (Pinn_phy) • bIMRT: Monaco (Monaco) • bIMRT: Pinnacle (Pinn_bio) • Rotation: • Tomotherapy (Tomo)

  10. C. Plan comparison (pIMRT vs. bIMRT) • DVH • Heterogeneity index (HI): the ratio of the minimum dose delivered to the hottest 5% of the PTV to the minimum dose delivered to the hottest 95% of the PTV • Conformity index (CI): the ratio of volume inside the isodose surface corresponding to the prescription dose compared to the volume of the target • Overall plan ranking index (fEUD)

  11. EUD • The uniform dose that gives the same biological effect as a given nonuniform dose distribution • a: the tumor or normal tissue specific parameter • a=1/n for the relationship of Lyman model • Malignant tumor targets general have large negative values • serial-type organ has a large positive value (penalize hot spots) • parallel structure organ use a small positive value

  12. fEUD: EUD-based figure-of-merit Weighting factors, correspond to the complication probability (for ith OAR) and/or control probability for jth target The relative importance factor between the weighted sums of EUDs for all targets and OARs

  13. Results • A. Dose distributions and DVHs

  14. Head and Neck case in target: Similar target coverage

  15. Head and Neck case: DVH of OARs

  16. Prostate case

  17. Prostate case

  18. Comparison of the dose ranges from the minimum to maximum doses and the mean doses for the five cases(1)

  19. Comparison of the dose ranges from the minimum to maximum doses and the mean doses for the five cases(2)

  20. bIMRT plans offer improved OAR sparing • The target coverage for both pIMRT and bIMRT plans are comparable; Tomo plans are slightly more uniform • Monaco plans show slightly more heterogeneous dose distributions in targets compared with other plans

  21. B. Dose conformity and hetergenetiy Monaco plans and Pinn_bio plans: more conformal Monaco: similar or higher HI Pinn_phy and Pinn_bio: similar HI Tomo: similar or lower values of CI and HI

  22. C: The equivalent uniform dose

  23. All five plans give similar EUDs • Monaco plan results in slightly greater EUDs values in 11 out of 12 targets in all five cases • Compared to Pinn_phy plans, Pinn_bio plans lead to 7 out of 12 targets receiving higher EUDs, while 32 out of 37 OARs receive lower EUDs • The Monaco and Pinn_bio plans yield similar OAR sparing

  24. D. Overall plan figure-of-merit(fEUD)

  25. E. DVH dependence of parameter a cord Right parotid

  26. Conclusion • 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 target • 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

  27. Thank you!

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