Treatment planning optimisation in proton therapy.
Journal: 2013/February - British Journal of Radiology
ISSN: 1748-880X
Abstract:
The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions.
Relations:
Content
Citations
(7)
References
(56)
Diseases
(1)
Chemicals
(1)
Organisms
(1)
Affiliates
(1)
Similar articles
Articles by the same authors
Discussion board
Br J Radiol 86(1021): 20120288

Treatment planning optimisation in proton therapy

Department of Oncology, University of Cambridge, Cambridge, UK
Oncology Centre, Addenbrooke's Hospital, Cambridge, UK
Centre for Proton Radiotherapy, Paul Scherrer Institute, Villigen PSI, Switzerland
Correspondence: Miss Stacey E McGowan, Selwyn College, University of Cambridge, Grange Road, Cambridge CB3 9DQ, UK. E-mail: ku.ca.mac@98mes
Received 2012 May 29; Revised 2012 Sep 6; Accepted 2012 Oct 1.

ABSTRACT.

The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions.

ABSTRACT.

The ability to create and deliver the ideal treatment plan, where the target volume receives 100% of the prescribed dose and normal tissue receives 0%, is the holy grail of radiation therapy [1]. It is, however, impossible to achieve this perfect balance. Instead, multiple trade-offs are required to achieve a clinically acceptable plan, so the problem becomes one of optimisation. There are many factors that can affect how “optimised” a patient's treatment can be. This review focuses on the challenges of proton therapy plan optimisation, particularly in regard to range uncertainties, and how to incorporate them into the plan evaluation and verification process.

The nature of proton therapy makes the aim of cure without complications potentially more achievable, owing to the highly localised deposition of dose in the characteristic Bragg peak [2]. This relates predominantly to the ability to deliver high doses of radiation close to normal tissue structures, which would be dose limiting in conventional X-ray treatments, and to the finite range of protons, which results in a reduced integral dose to surrounding normal tissues.

From a clinical perspective, the exact role of proton therapy has yet to be defined. However, for childhood cancers, proton therapy delivers a lower dose to tissues around the tumour than X-rays, resulting in less growth disturbance and lower risk of secondary malignancies. There is also the suggestion that the use of proton therapy can reduce impairment of neuropsychological and intelligence quotient development [3]. In adults, proton therapy seems particularly effective in the treatment of radio-resistant tumours close to critical structures such as the brain stem and spinal cord. For example, outstanding results have been published for the use of proton therapy in the treatment of chordoma and chondrosarcoma [4]. The current evidence for the use of proton therapy at different sites has been extensively reviewed [5-8]. However, it will also be important to consider expanding potential indications where logic and dosimetry indicate that proton therapy can confer an advantage [7]. Although clinical results comparing proton therapy with the most modern X-ray therapy are currently lacking, overall clinical outcomes are promising for both delivery options and support the rationale for proton therapy [8]. The reader is referred to the literature [9-11] for more clinical data. Nevertheless, substantial opportunity for further clinical research development and evaluation remains.

The choice of treatment delivery can have a large impact on the ability both to produce conformal dose distributions and to produce a plan which is robust to uncertainties. There are three main treatment delivery techniques used clinically: passive scattering [12], uniform scanning and active scanning [13,14] (Table 1). These techniques are used to broaden the narrow proton beam created by the accelerator into one that can achieve a uniform dose coverage of the target at all depths. This is achieved for passive scattering and uniform scanning through the delivery of so-called spread-out Bragg peaks (Figure 1).

An external file that holds a picture, illustration, etc.
Object name is bjr-86-D12288-g001.jpg

Schematic of Bragg peak delivery along a single profile through a target. (a) A flat spread-out Bragg peak (SOBP) is achieved by placing spots with increasing weights throughout the target to produce a uniform field, as used in passive scattering and single-field uniform dose. (b) Only the most distal single pristine Bragg peak (BP) is used for distal-edge tracking. (c) Optimally weighted spots are positioned throughout the volume to achieve fields with non-uniform doses for three-dimensional intensity-modulated particle therapy.

Table 1

Proton beam delivery techniques, production methods and planning techniques (the further down the table, the more conformal the technique)
Methods of producing a clinical proton beam to treat entire target volumeDescriptions
Passive scatteringWorks on the principle that high atomic number materials, such as lead, scatter the beam with minimum energy loss and low atomic number materials, such as plastic, decrease proton energy with minimum scatter. Combining these materials to produce patient-specific collimators and compensators results in a conformal treatment beam with a spread-out Bragg peak
Uniform scanningThis is similar to passive scattering with the difference that the beam is spread in the lateral direction through magnetically deflecting the beam with constant fluence instead of using a scattering foil. Different spot weights are produced using a compensator, as in passive scattering
Active scanningThis uses magnetic fields to deflect the path of each proton beam towards the planned position in the target volume. Individual Bragg peaks are distributed within the target volume and the cumulative effect produces an effective SOBP without the need for compensators. This is achieved by either continuous magnetic scanning or spot scanning. The latter is analogous to the step-and-shoot mode in IMRT, i.e. a non-continuous delivery of dose, where the exact position is determined before the dose is delivered
Methods of achieving adequate dose distributionsDescriptions
SFUDSingle individually optimised proton fields that each deliver a homogeneous dose to a volume. If necessary, these can be combined by simple addition
Field patchingThe sharp distal edge dose gradient can be matched up to the lateral edges of another “patch” field to produce a continuous dose distribution. Where possible, equivalent opposite fields are also used to reduce the potential for dose variation at the abutting edges. Multiple fields in patch work can be used to achieve multiple dose gradients inside a treatment volume. Field patching is a 3D extension of matching lateral field edges. Therefore, if multiple fields are used, each one can deliver a homogeneous dose to part of the volume
IMPTIMPT is analogous to IMRT, and is a mode of treatment delivery achievable only with active scanning beams. IMPT uses narrow proton beams which are magnetically moved over the volume in the transverse plane while the energy and intensity are altered to control dose to a point and sculpt the dose at depth. Unlike SFUD treatments, IMPT can deliver a number of non-uniform fields to produce the desired dose distribution
“Flavours” of IMPTDescriptions
3D IMPTThis is most similar to IMRT. Bragg peaks are placed throughout the entire volume and their weights optimally adjusted
DETDET is a method by which pristine Bragg peaks of optimal weights are distributed only along the distal edge of the target and not throughout the target volume

3D, three-dimensional; DET, distal-edge tracking; IMPT, intensity-modulated particle therapy; IMRT, intensity-modulated radiotherapy treatment; SFUD, single-field uniform dose; SOBP, spread-out Bragg peak.

Orthogonal to the beam direction, the beam is spread using carefully designed scatterers (for passive scattering) or by continually deflecting the proton beam in a regular pattern orthogonal to the beam direction with constant intensity (uniform scanning). For both approaches, three-dimensional (3D) conformation of the final dose to the target is achieved through the additional use of patient- and field-specific collimators (which conform the dose in directions orthogonal to the beam) and compensators (which conform the dose in the beam direction) inserted in the beam nozzle [14]. Active scanning, on the other hand, also uses magnets to scan the proton beam across the target volume, but, in contrast to uniform scanning, allows the fluence (dose) applied at each Bragg position to be continuously varied. Active scanning can offer an advantage to the patient by allowing for greater flexibility in the delivered dose and a reduction in integral dose to healthy tissues. It also allows for the delivery of intensity-modulated particle therapy (IMPT) [15], which is analogous with intensity-modulated radiotherapy treatment (IMRT) in conventional radiotherapy. Although there is, in principle, a continuum of solutions to the IMPT problem, at its extremes, IMPT can be divided into two “flavours”: distal-edge tracking (DET) [16], where Bragg peaks are placed only at the edge of the target volume, and 3D IMPT [15], where Bragg peaks are optimally distributed and weighted throughout the target volume (Figure 1). IMPT allows for delivery of single inhomogeneous but optimised fields to produce a final inhomogeneous dose distribution in the target volume. This permits the planner to be more flexible in the placement of residual dose to healthy tissues. However, although IMPT offers greater optimisation of dose delivery at the planning stage, it has the potential to be sensitive to range uncertainties [17,18]. Table 1 summarises all these modes of producing and manipulating proton dose distributions.

Acknowledgments

We are grateful to Dr Simon Thomas for helpful discussions.

Acknowledgments

Footnotes

SEM's PhD is funded by the Medical Research Council. NGB is supported by the National Institute for Health Research (NIHR), Cambridge Biomedical Research Centre.

Footnotes

References

  • 1. Bortfeld T. Optimized planning using physical objectives and constraints.Semin Radat Oncol 1999;9:20–34. [[PubMed]
  • 2. Bragg WH. On absorption of alpha rays and on the classification of the alpha rays from radium.Phil Mag 1904;6:719–25. [PubMed]
  • 3. Merchant TE, Hua CH, Shukla H, Ying X, Nill S, Oelfke U. Proton versus photon radiotherapy for common pediatric brain tumors: comparison of models of dose characteristics and their relationship to cognitive function.Pediatr Blood Cancer 2008;51:110–17. [[PubMed]
  • 4. Ares C, Hug EB, Lomax AJ, Bolsi A, Timmermann B, Rutz HP, et al Effectiveness and safety of spot scanning proton radiation therapy for chordomas and chondrosarcomas of the skull base: first long-term report.Int J Radiat Oncol Biol Phys 2009;75:1111–18. [[PubMed][Google Scholar]
  • 5. De Ruysscher D, Lodge M, Jones B, Brada M, Munro A, Jefferson T, et al Charged particles in radiotherapy: a 5-year update of a systematic review.Radiother Oncol 2012;103:5–7. [[PubMed][Google Scholar]
  • 6. Allen AM, Pawlicki T, Dong L, Fourkal E, Buyyounouski M, Cengel K, et al An evidence based review of proton beam therapy: the report of ASTRO's emerging technology committee.Radiother Oncol 2012;103:8–11. [[PubMed][Google Scholar]
  • 7. Jones B. The potential clinical advantages of charged particle radiotherapy using protons or light ions.Clin Oncol (R Coll Radiol) 2008;20:555–63. [[PubMed]
  • 8. Durante M, Loeffler JS. Charged particles in radiation oncology.Nature 2010;7:37–43. [[PubMed]
  • 9. Lodge M, Pijls-Johannesma M, Stirk L, Munro AJ, De Ruysscher D, Jefferson T. A systematic literature review of the clinical and cost-effectiveness of hadron therapy in cancer.Radiother Oncol 2007;83:110–22. [[PubMed]
  • 10. van deWater T, Bijl HP, Schilstra C, Pijls-Johannesma M, Langendijk J. The potential benefit of radiotherapy with protons in head and neck cancer with respect to normal tissue sparing: a systematic review of literature.Oncologist 2011;16:366–77.
  • 11. Ramaekers BL, Pijls-Johannesma M, Joore MA, van denEnde P, Langendijk JA, Lambin P, et al Systematic review and meta-analysis of radiotherapy in various head and neck cancers: comparing photons, carbon-ions and protons.Cancer Treat Rev 2011;37:185–201. [[PubMed][Google Scholar]
  • 12. Haberer T, Becher W, Schardt D, Kraft G. Magnetic scanning system for heavy ion therapy.Nucl Instrum Methods Phys Res A 1993;330:296–305. [PubMed]
  • 13. Pedroni E, Bacher R, Blattmann H, Böhringer T, Coray A, Lomax A, et al The 200-MeV proton therapy project at the Paul Scherrer Institute: conceptual design and practical realization.Med Phys 1995;22:37–53. [[PubMed][Google Scholar]
  • 14. DeLaney TF, Hanne MK. Proton and charged particle radiotherapy. Philadelphia, PA: Lippincott Williams and Wilkins; 2009. [PubMed]
  • 15. Lomax A. Intensity modulation methods for proton radiotherapy.Phys Med Biol 1999;44:185–205. [[PubMed]
  • 16. Deasy J. A proton dose calculation algorithm for conformal therapy simulations based on Moliere theory of lateral deflections.Med Phys 1998;25:476–83. [[PubMed]
  • 17. Oelfke U, Bortfeld T. Intensity modulated radiotherapy with charged particle beams: studies of inverse treatment planning for rotation therapy.Med Phys 2000;27:1246–57. [[PubMed]
  • 18. Nill S, Bortfeld T, Oelfke U. Inverse planning of intensity modulated proton therapy.Z Med Phys 2004;14:35–40. [[PubMed]
  • 19. Lomax A. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 2: the potential effects of inter-fraction and inter-field motions.Phys Med Biol 2008;53:1043–56. [[PubMed]
  • 20. España S, Paganetti H. The impact of uncertainties in the CT conversion algorithm when predicting proton beam ranges in patients from dose and PET-activity distributions.Phys Med Biol 2010;55:7557–71. [[PubMed]
  • 21. International Commission on Radiation Units and Measurements: Prescribing, recording, and reporting photon beam therapy. ICRU Report no. 50. Bethesda, MD: ICRU; 1993. [PubMed]
  • 22. International Commission on Radiation Units and Measurements: A review of the new supplement to ICRU Report 50. ICRU Report no. 62. Bethesda, MD: ICRU; 1999. [PubMed]
  • 23. International Commission on Radiation Units and Measurements: Prescribing, recording, and reporting proton beam therapy. ICRU Report no. 78. Bethesda, MA: ICRU; 2007. [PubMed]
  • 24. Chvetsov AV, Paige SL. The influence of CT image noise on proton range calculation in radiotherapy planning.Phys Med Biol 2010;55:N141–9. [[PubMed]
  • 25. Schaffner B, Pedroni E. The precision of proton range calculations in proton radiotherapy treatment planning: experimental verification of the relationship between CT-HU and proton stopping power.Phys Med Biol 1998;43:1579–92. [[PubMed]
  • 26. Schulte R, Bashkirov V, Li T, Liang Z, Mueller K, Heimann J, et al Conceptual design of a proton computed tomography system for applications in proton therapy.IEEE Trans Nucl Sci 2004;51:866–72. [PubMed][Google Scholar]
  • 27. Moyers MF, Sardesai M, Sun S, Miller DW. Ion stopping powers and CT numbers.Med Dosim 2010;35:179–94. [[PubMed]
  • 28. Lomax A. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 1: the potential effects of calculational uncertainties.Phys Med Biol 2008;53:1027–42. [[PubMed]
  • 29. Burnet NG, Adams EJ, Fairfoul J, Tudor GS, Hoole AC, Routsis DS, et al Practical aspects of implementation of helical tomotherapy for intensity-modulated and image-guided radiotherapy.Clin Oncol 2010;22:294–312. [[PubMed][Google Scholar]
  • 30. Booth JT, Zavgorodni SF. Set-up error and organ motion uncertainty: a review.Australas Phys Eng Sci Med 1999;22:29–47. [[PubMed]
  • 31. Langen KM, Jones DT. Organ motion and its management.Int J Radiat Oncol Biol Phys 2001;50:265–78. [[PubMed]
  • 32. Rimmer YL, Burnet NG, Routsis DS, Twyman N, Hoole A, Treeby J, et al Practical issues in the implementation of image-guided radiotherapy for the treatment of prostate cancer within a UK department.Clin Oncol 2008;20:22–30. [[PubMed][Google Scholar]
  • 33. Lambert J, Suchowerska N, McKenzie DR, Jackson M. Intrafractional motion during proton beam scanning.Phys Med Biol 2005;50:4853–62. [[PubMed]
  • 34. Phillips MH, Pedroni E, Blattmann H, Boehringer T, Coray A, Scheib S. Effects of respiratory motion on dose uniformity with a charged particle scanning method.Phys Med Biol 1992;37:223–34. [[PubMed]
  • 35. Zenklusen SM, Pedroni E, Meer D. A study on repainting strategies for treating moving targets with proton pencil beam scanning at the new Gantry 2 at PSI.Phys Med Biol 2010;55:5103–21. [[PubMed]
  • 36. Knopf AC, Hong TS, Lomax AJ. Scanned proton radiotherapy for mobile targets—the effectiveness of re-scanning in the context of different treatment planning approaches and for different motion characteristics.Phys Med Biol 2011;56:7257–71. [[PubMed]
  • 37. Seco J, Robertson D, Trofimov A, Paganetti H. Breathing interplay effects during proton beam scanning: simulation and statistical analysis.Phys Med Biol 2009;54:N283–94. [[PubMed]
  • 38. Grözinger SO, Rietzel E, Li Q, Bert C, Haberer T, Kraft G. Simulations to design an online motion compensation system for scanned particle beams.Phys Med Biol 2006;51:3517–31. [[PubMed]
  • 39. Bert C, Grözinger SO, Rietzel E. Quantification of interplay effects of scanned particle beams and moving targets.Phys Med Biol 2008;53:2253–65. [[PubMed]
  • 40. Carabe A, Moteabbed M, Depauw N, Schuemann J, Paganetti H. Range uncertainty in proton therapy due to variable biological effectiveness.Phys Med Biol 2012;57:1159–72. [[PubMed]
  • 41. Robertson J, Williams J, Schimdt R, Little J, Flynn D, Suit H. Radiobiological studies of high energy modulated proton beam utilizing cultured mammalian cells.Cancer 1975;35:1664–77. [[PubMed]
  • 42. Matsuura T, Egashira Y, Nishio T, Matsumoto Y, Wada M, Koike S, et al Apparent absence of a proton beam dose rate effect and possible differences in RBE between Bragg peak and plateau.Med Phys 2010;37:5376. [[PubMed][Google Scholar]
  • 43. Grassberger C, Trofimov A, Lomax A, Paganetti H. Variations in linear energy transfer within clinical proton therapy fields and the potential for biological treatment planning.Int J Radiat Oncol Biol Phys 2011;80:1559–66.
  • 44. Bert C, Durante M. Motion in radiotherapy: particle therapy.Phys Med Biol 2011;56:R113–44. [[PubMed]
  • 45. Furukawa T, Inaniwa T, Sato S, Tomitani T, Minohara S, Noda K, et al Design study of a raster scanning system for moving target irradiation in heavy-ion radiotherapy.Med Phys 2007;34:1085–97. [[PubMed][Google Scholar]
  • 46. Bert C, Saito N, Schmidt A, Chaudhri N, Schardt D, Rietzel E. Target motion tracking with a scanned particle beam.Med Phys 2007;34:4768–71. [[PubMed]
  • 47. Saito N, Bert C, Chaudhri N, Gemmel A, Schardt D, Durante M, et al Speed and accuracy of a beam tracking system for treatment of moving targets with scanned ion beams.Phys Med Biol 2009;54:4849–62. [[PubMed][Google Scholar]
  • 48. Keall PJ, Kini VR, Vedam SS, Mohan R. Motion adaptive x-ray therapy: a feasibility study.Phys Med Biol 2001;46:1–10. [[PubMed]
  • 49. Grözinger SO, Li Q, Rietzel E, Haberer T, Kraft G. 3D online compensation of target motion with scanned particle beam.Radiother Oncol 2004;73(Suppl. 2)S77–9. [[PubMed]
  • 50. van Herk M. Errors and margins in radiotherapy.Semin Radiat Oncol 2004;14:52–64. [[PubMed]
  • 51. Grözinger SO, Bert C, Haberer T, Kraft G, Rietzel E. Motion compensation with a scanned ion beam: a technical feasibility study.Radiat Oncol 2008;3:34.
  • 52. Thomas SJ. Margins for treatment planning of proton therapy.Phys Med Biol 2006;51:1491. [[PubMed]
  • 53. Albertini F, Hug EB, Lomax AJ. Is it necessary to plan with safety margins for actively scanned proton therapy?Phys Med Biol 2011;56:4399. [[PubMed]
  • 54. Unkelbach J, Chan T, Bortfield T. Accounting for range uncertainties in the optimisation of intensity modulated proton therapy.Phys Med Biol 2007;52:2755–73. [[PubMed]
  • 55. Pflugfelder D, Wilkens JJ, Oelfke U. Worst case optimization: a method to account for uncertainties in the optimization of intensity modulated proton therapy.Phys Med Biol 2008;53:1689–700. [[PubMed]
  • 56. Lomax AJ, Pedroni E, Rutz H, Goitein G. The clinical potential of intensity modulated proton therapy.Z Med Phys 2004;14:147–52. [[PubMed]
  • 57. Chen W, Unkelbach J, Tromfimov A, Madden T, Kooy H, Bortfeld T. Including robustness in multi-criteria optimization for intensity-modulated proton therapy.Phys Med Biol 2012;57:591–608.
  • 58. Thieke C, Küfer K, Monz M, Scherrer A, Alonso F, Oelfke U, et al A new concept for interactive radiotherapy planning with multicriteria optimization: first clinical evaluation.Radiother Oncol 2007;85:292–8. [[PubMed][Google Scholar]
  • 59. Cotrutz C, Lahanas M, Kappas C, Baltas D. A multiobjective gradient-based dose optimization algorithm for external beam conformal radiotherapy.Phys Med Biol 2001;46:2161–75. [[PubMed]
  • 60. Craft D, Halabi T, Bortfeld T. Exploration of tradeoffs in intensity-modulated radiotherapy.Phys Med Biol 2005;50:5857–68. [[PubMed]
  • 61. Albertini F, Casiraghi M, Lorentini S, Rombi B, Lomax AJ. Experimental verification of IMPT treatment plans in an anthropomorphic phantom in the presence of delivery uncertainties.Phys Med Biol 2011;56:4415. [[PubMed]
  • 62. Safai S, Shixiong L, Pedroni E. Development of an inorganic scintillating mixture for proton beam verification dosimetry.Phys Med Biol 2004;49:4637–55. [[PubMed]
  • 63. Dosanjh M. Development of hadron therapy for cancer treatment in Europe.AIP Conf Proc 2008;1032:12–16. [PubMed]
  • 64. [homepage on the internet]. London, UK: NHS Specialised Services; 2011. [cited May 2011]. Available from: . [PubMed]
  • 65. [homepage on the internet]. London, UK: Department of Health; 2012. [cited May 2011]. Available from: [PubMed]
  • 66. Burnet N, Taylor E, Kirkby K, Thorp N, Mackay R, McKenna G. Proton beam therapy for cancer: an important development for patients with an explicit agenda.BMJ 2012;344:e2488. [PubMed]
Collaboration tool especially designed for Life Science professionals.Drag-and-drop any entity to your messages.