Application of optimization model with piecewise penalty to intensity-modulated radiation therapy

Abstract Purpose: Both maximum-dose-based and generalized equivalent uniform dose (gEUD)-based quadratic sub-scores, which penalize doses higher than the prescribed dose, exhibit the shortcomings of semi-deviation and a vanishing gradient in the feasible solution space. To address these drawbacks, this study proposes new sub-scores for the maximum dose criterion and the gEUD criterion. Methods: In new sub-scores, a dosage lower than the prescribed dose is assigned a linear penalty function, and one higher than the prescribed dose is assigned an extra quadratic penalty function. To test their efficiency, they were incorporated into a physical model and a hybrid physical–biological model, respectively, and were tested on a phantom TG119 and two types of clinic cases. The improved methods were compared with their original methods and the dose-volume (DV)-based optimization method. Additionally, the improved gEUD-based method was compared with another gEUD-based quadratic optimization method. The gradient-based optimization algorithm was applied to solve these large-scale optimization problems. Results: For similar or better PTV coverage, optimization based on our proposed quadratic models is capable of improving the OARs sparing. In practice, by using multiple DV constraints for each optimized structures, the DV based optimization may be able to arrive at similar plan, whereas greater trial-and-error is performed to adjust parameters of optimization model. Although the optimal prescribed dose remains unclear, at the same prescribed dose, our proposed optimization method can obtain better plan. Conclusion: Our proposed optimization method has the potential to expand the solution space and improve the quality of radiotherapy plan.

[1]  Joseph O Deasy,et al.  The generalized equivalent uniform dose function as a basis for intensity-modulated treatment planning. , 2002, Physics in medicine and biology.

[2]  Minsun Kim,et al.  A hierarchical evolutionary algorithm for multiobjective optimization in IMRT. , 2010, Medical physics.

[3]  Joseph O Deasy,et al.  CERR: a computational environment for radiotherapy research. , 2003, Medical physics.

[4]  D. Mihailidis,et al.  Superiority of equivalent uniform dose (EUD)-based optimization for breast and chest wall. , 2010, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[5]  D Baltas,et al.  A multiobjective gradient-based dose optimization algorithm for external beam conformal radiotherapy. , 2001, Physics in medicine and biology.

[6]  Moyed Miften,et al.  Biological-based optimization and volumetric modulated arc therapy delivery for stereotactic body radiation therapy. , 2011, Medical physics.

[7]  Peter Ziegenhein,et al.  Physically constrained voxel‐based penalty adaptation for ultra‐fast IMRT planning , 2016, Journal of applied clinical medical physics.

[8]  Radhe Mohan,et al.  Effectiveness of noncoplanar IMRT planning using a parallelized multiresolution beam angle optimization method for paranasal sinus carcinoma. , 2005, International journal of radiation oncology, biology, physics.

[9]  Xun Jia,et al.  A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization. , 2014, Medical physics.

[10]  Ludwig Bogner,et al.  Investigation of intensity-modulated radiotherapy optimization with gEUD-based objectives by means of simulated annealing. , 2008, Medical physics.

[11]  R. Li,et al.  Optimization of inverse treatment planning using a fuzzy weight function. , 2000, Medical physics.

[12]  R Mohan,et al.  Algorithms and functionality of an intensity modulated radiotherapy optimization system. , 2000, Medical physics.

[13]  Anders Brahme,et al.  Treatment Optimization Using Physical and Radiobiological Objective Functions , 1995 .

[14]  E. Yorke,et al.  Use of normal tissue complication probability models in the clinic. , 2010, International journal of radiation oncology, biology, physics.

[15]  Jorge Nocedal,et al.  On the limited memory BFGS method for large scale optimization , 1989, Math. Program..

[16]  Lei Dong,et al.  Speed and convergence properties of gradient algorithms for optimization of IMRT. , 2004, Medical physics.

[17]  R. Jeraj,et al.  Treatment plan modification using voxel-based weighting factors/dose prescription. , 2003, Physics in medicine and biology.

[18]  T. Hellebust,et al.  Modeling normal tissue complication probability from repetitive computed tomography scans during fractionated high-dose-rate brachytherapy and external beam radiotherapy of the uterine cervix. , 2000, International journal of radiation oncology, biology, physics.

[19]  Joos V Lebesque,et al.  Rectal bleeding, fecal incontinence, and high stool frequency after conformal radiotherapy for prostate cancer: normal tissue complication probability modeling. , 2006, International journal of radiation oncology, biology, physics.

[20]  D M Shepard,et al.  Direct aperture optimization: a turnkey solution for step-and-shoot IMRT. , 2002, Medical physics.

[21]  E. B. Butler,et al.  Smart (simultaneous modulated accelerated radiation therapy) boost: a new accelerated fractionation schedule for the treatment of head and neck cancer with intensity modulated radiotherapy. , 1999, International journal of radiation oncology, biology, physics.

[22]  Shiva K. Das,et al.  A role for biological optimization within the current treatment planning paradigm. , 2009, Medical physics.

[23]  Albin Fredriksson,et al.  Automated improvement of radiation therapy treatment plans by optimization under reference dose constraints , 2012, Physics in medicine and biology.

[24]  M. C. Pressello,et al.  Role of the parameters involved in the plan optimization based on the generalized equivalent uniform dose and radiobiological implications , 2008, Physics in medicine and biology.

[25]  R. Mohan,et al.  Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose. , 2002, International journal of radiation oncology, biology, physics.

[26]  T. Bortfeld,et al.  From physical dose constraints to equivalent uniform dose constraints in inverse radiotherapy planning. , 2003, Medical physics.

[27]  Thomas Dirscherl,et al.  Advantage of biological over physical optimization in prostate cancer? , 2011, Zeitschrift fur medizinische Physik.

[28]  Joos V Lebesque,et al.  Sensitivity of treatment plan optimisation for prostate cancer using the equivalent uniform dose (EUD) with respect to the rectal wall volume parameter. , 2004, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[29]  Dávid Papp,et al.  Shared data for intensity modulated radiation therapy (IMRT) optimization research: the CORT dataset , 2014, GigaScience.

[30]  X Allen Li,et al.  Improved critical structure sparing with biologically based IMRT optimization. , 2009, Medical physics.

[31]  Guido Jenster,et al.  CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy , 2014, GigaScience.

[32]  C-S Shieh,et al.  Dosimetric advantages of generalised equivalent uniform dose-based optimisation on dose-volume objectives in intensity-modulated radiotherapy planning for bilateral breast cancer. , 2012, The British journal of radiology.

[33]  Radhe Mohan,et al.  A sensitivity-guided algorithm for automated determination of IMRT objective function parameters. , 2006, Medical physics.