AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Article Link
Collect
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Review | Open Access

A review of proton therapy – Current status and future directions

Department of Radiation Physics, MD Anderson Cancer Center, Houston, Texas, USA
Show Author Information

Abstract

The original rationale for proton therapy was its highly conformal depth-dose distributions compared to photons, which allow greater sparing of normal tissues and escalation of tumor doses, thus potentially improving outcomes. Additionally, recent research has revealed previously unrecognized advantages of proton therapy. For instance, the higher relative biological effectiveness (RBE) near the end of the proton range can be exploited to increase the difference in biologically effective dose in tumors versus normal tissues. Moreover, the smaller “dose bath,” that is, the compact nature of proton dose distributions, has been found to reduce the exposure of circulating lymphocytes and the immune organs at risk. There is emerging evidence that the resulting sparing of the immune system has the potential to improve outcomes.

Protons accelerated to energies ranging from 70 to 250 MeV enter the treatment head mounted typically on a rotating gantry. Initially, the beams of protons are narrow and, to be suitable for treatments, must be spread laterally and longitudinally and shaped appropriately. Such spreading and shaping may be accomplished electromechanically for the “passively scattered proton therapy” (PSPT) mode; or it may be achieved through magnetic scanning of thin “beamlets” of protons. Intensities of scanning beamlets are optimized to deliver intensity-modulated proton therapy (IMPT), which optimally balances tumor dose and the sparing of normal tissues. IMPT is presumably the most powerful form of proton therapy.

The planning and evaluation of proton dose distributions require substantially different techniques compared to photon therapy. This is mainly due to the fact that proton dose distributions are highly sensitive to inter- and intra-fractional variations in anatomy. In addition, for the same physical dose, the biological effectiveness of protons is different from photons. In the current practice of proton therapy, the RBE is simplistically assumed to have a constant value of 1.1. In reality, the RBE is variable and a highly complex function of numerous variables including energy of protons, dose per fraction, tissue and its environment, cell type, end point, and possibly other factors.

While the theoretical potential of proton therapy is high, the clinical evidence in support of its use has so far been mixed. The uncertainties and assumptions mentioned above and the limitations of the still evolving technology of proton therapy may have diminished its true clinical potential. Although promising results have been reported for many types of cancers, they are often based on small studies. At the same time, there have been reports of unforeseen toxicities. Furthermore, because of the high cost of proton therapy, questions are often raised about its value. The general consensus is that there is a need for continued improvement in the state of the art of proton therapy. There is also a need to generate high level evidence of the potential of protons.

Fortuitously, such efforts are taking place currently. Current research, aimed at enhancing the therapeutic potential of proton therapy, includes the determination and mitigation of the impact of the physical uncertainties on proton dose distributions through advanced image-guidance and adaptive radiotherapy techniques. Since residual uncertainties will remain, robustness evaluation and robust optimization techniques are being developed to render dose distributions more resilient and to improve confidence in them. The ongoing research also includes improving our understanding of the biological and immunomodulatory effects of proton therapy. Such research and continuing technological advancements in planning and delivery methods are likely to help demonstrate the superiority of protons.

References

1

Wilson RR. Radiological use of fast protons. Radiology. 1946; 47: 487-491. http://www.ncbi.nlm.nih.gov/pubmed/20274616

2

Lawrence JH, Tobias CA, Born JL, et al. Pituitary irradiation with high-energy proton beams: a preliminary report. Cancer Res. 1958; 18: 121-134. http://www.ncbi.nlm.nih.gov/pubmed/13511365

3

Coutrakon G, Hubbard J, Johanning J, et al. A performance study of the loma linda proton medical accelerator. Med Phys. 1994; 21: 1691-1701. http://www.ncbi.nlm.nih.gov/pubmed/7891629

4

Gillin MT, Sahoo N, Bues M, et al. Commissioning of the discrete spot scanning proton beam delivery system at the university of Texas MD Anderson Cancer Center, Proton Therapy Center, Houston. Med Phys. 2010; 37: 154-163. http://www.ncbi.nlm.nih.gov/pubmed/20175477

5

Smith AR. Vision 20/20: proton therapy. Med Phys. 2009; 36: 556-568. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19291995

6

Smith A, Gillin M, Bues M, et al. The MD Anderson proton therapy system. Med Phys. 2009; 36: 4068-4083. http://www.ncbi.nlm.nih.gov/pubmed/19810479

7

Smith AR. Proton therapy. Phys Med Biol. 2006; 51: R491-R504. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16790919

8
Jones DTL. Present status and future trends of heavy particle radiotherapy. In: Baron E, Lieuvin M, eds. Cyclotrons and Their Applications 1998. Institute of Physics Publishing; 1999: 13-20.
9

Paganetti H, Niemierko A, Ancukiewicz M, et al. Relative biological effectiveness (RBE) values for proton beam therapy. Int J Radiat Oncol Biol Phys. 2002; 53: 407-421. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12023146

10

Paganetti H. Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer. Phys Med Biol. 2014; 59: R419-R472. http://www.ncbi.nlm.nih.gov/pubmed/25361443

11

Mohan R, Grosshans D. Proton therapy – present and future. Adv Drug Deliv Rev. 2017; 109: 26-44. https://www.ncbi.nlm.nih.gov/pubmed/27919760

12

Lomax A. Intensity modulation methods for proton radiotherapy. Phys Med Biol. 1999; 44: 185-205. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=10071883

13

Lomax AJ, Bortfeld T, Goitein G, et al. A treatment planning inter-comparison of proton and intensity modulated photon radiotherapy. Radiother Oncol. 1999; 51: 257-271. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=10435821

14

Mohan R, Das IJ, Ling CC. Empowering intensity modulated proton therapy through physics and technology: an overview. Int J Radiat Oncol Biol Phys. 2017; 99: 304-316. https://www.ncbi.nlm.nih.gov/pubmed/28871980

15

Hyer DE, Hill PM, Wang D, et al. A dynamic collimation system for penumbra reduction in spot-scanning proton therapy: proof of concept. Med Phys. 2014; 41:091701. http://www.ncbi.nlm.nih.gov/pubmed/25186376

16

Hyer DE, Hill PM, Wang D, et al. Effects of spot size and spot spacing on lateral penumbra reduction when using a dynamic collimation system for spot scanning proton therapy. Phys Med Biol. 2014; 59: N187-N196. http://www.ncbi.nlm.nih.gov/pubmed/25330783

17

Lomax AJ, Pedroni E, Rutz H, et al. The clinical potential of intensity modulated proton therapy. Z Med Phys. 2004; 14: 147-152. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15462415

18

Zhu XR, Sahoo N, Zhang X, et al. Intensity modulated proton therapy treatment planning using single-field optimization: the impact of monitor unit constraints on plan quality. Med Phys. 2010; 37: 1210-1219. https://www.ncbi.nlm.nih.gov/pubmed/20384258

19

Frank SJ, Cox JD, Gillin M, et al. Multifield optimization intensity modulated proton therapy for head and neck tumors: a translation to practice. Int J Radiat Oncol Biol Phys. 2014; 89: 846-853. https://www.ncbi.nlm.nih.gov/pubmed/24867532

20

Chang JY, Li H, Zhu XR, et al. Clinical implementation of intensity modulated proton therapy for thoracic malignancies. Int J Radiat Oncol Biol Phys. 2014; 90: 809-818. https://www.ncbi.nlm.nih.gov/pubmed/25260491

21

Goitein M, Abrams M. Multi-dimensional treatment planning: Ⅰ. Delineation of anatomy. Int J Radiat Oncol Biol Phys. 1983; 9: 777-787.

22

Goitein M, Abrams M, Rowell D, et al. Multi-dimensional treatment planning: Ⅱ. Beam's eye-view, back projection, and projection through CT sections. Int J Radiat Oncol Biol Phys. 1983; 9: 789-797.

23

Lomax AJ, Boehringer T, Coray A, et al. Intensity modulated proton therapy: a clinical example. Med Phys. 2001; 28: 317-324. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11318312

24

Pedroni E, Bohringer T, Coray A, et al. Initial experience of using an active beam delivery technique at PSI. Strahlenther Onkol 1999; 175(2): 18-20. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=10394388

25

Cella L, Lomax A, Miralbell R. New techniques in hadrontherapy: intensity modulated proton beams. Phys Med. 2001; 17(1): 100-102. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11770521

26

Lomax AJ, Bohringer T, Bolsi A, et al. Treatment planning and verification of proton therapy using spot scanning: initial experiences. Med Phys. 2004; 31: 3150-3157. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15587667

27

Chang JY, Komaki R, Lu C, et al. Phase 2 study of high-dose proton therapy with concurrent chemotherapy for unresectable stage Ⅲ nonsmall cell lung cancer. Cancer. 2011; 117: 4707-4713. http://www.ncbi.nlm.nih.gov/pubmed/21437893

28

Cao W, Lim G, Li X, et al. Incorporating deliverable monitor unit constraints into spot intensity optimization in IMPT treatment planning. Phys Med Biol. 2013; 58: 5113-5125. https://www.ncbi.nlm.nih.gov/pubmed/23835656

29

Jimenez RB, Sethi R, Depauw N, et al. Proton radiation therapy for pediatric medulloblastoma and supratentorial primitive neuroectodermal tumors: outcomes for very young children treated with upfront chemotherapy. Int J Radiat Oncol Biol Phys. 2013; 21: 017.

30

Bishop AJ, Greenfield B, Mahajan A, et al. Proton beam therapy versus conformal photon radiation therapy for childhood craniopharyngioma: multi-institutional analysis of outcomes, cyst dynamics, and toxicity. Int J Radiat Oncol Biol Phys. 2014; 90: 354-361. https://doi.org/10.1016/j.ijrobp.2014.05.051

31

Ladra MM, Szymonifka JD, Mahajan A, et al. Preliminary results of a phase Ⅱ trial of proton radiotherapy for pediatric rhabdomyosarcoma. J Clin Oncol. 2014; 32: 3762-3770. https://doi.org/10.1200/JCO.2014.56.1548

32

McGovern SL, Okcu MF, Munsell MF, et al. Outcomes and acute toxicities of proton therapy for pediatric atypical teratoid/rhabdoid tumor of the central nervous system. Int J Radiat Oncol Biol Phys. 2014; 90: 1143-1152. https://doi.org/10.1016/j.ijrobp.2014.08.354

33

Sethi RV, Giantsoudi D, Raiford M, et al. Patterns of failure after proton therapy in medulloblastoma; linear energy transfer distributions and relative biological effectiveness associations for relapses. Int J Radiat Oncol Biol Phys. 2014; 88: 655-663. http://www.ncbi.nlm.nih.gov/pubmed/24521681

34

Gunther JR, Sato M, Chintagumpala M, et al. Imaging changes in pediatric intracranial ependymoma patients treated with proton beam radiation therapy compared to intensity modulated radiation therapy. Int J Radiat Oncol Biol Phys. 2015; 93: 54-63. http://www.ncbi.nlm.nih.gov/pubmed/26279024

35

Peeler CR, Mirkovic D, Titt U, et al. Clinical evidence of variable proton biological effectiveness in pediatric patients treated for ependymoma. Radiother Oncol. 2016; 121: 395-401. https://www.ncbi.nlm.nih.gov/pubmed/27863964

36

Indelicato DJ, Flampouri S, Rotondo RL, et al. Incidence and dosimetric parameters of pediatric brainstem toxicity following proton therapy. Acta Oncol. 2014; 53: 1298-1304. http://www.ncbi.nlm.nih.gov/pubmed/25279957

37

Haas-Kogan D, Indelicato D, Paganetti H, et al. National cancer institute workshop on proton therapy for children: considerations regarding brainstem injury. Int J Radiat Oncol Biol Phys. 2018; 101: 152-168. https://www.ncbi.nlm.nih.gov/pubmed/29619963

38

Debus J, Hug EB, Liebsch NJ, et al. Brainstem tolerance to conformal radiotherapy of skull base tumors. Int J Radiat Oncol Biol Phys. 1997; 39: 967-975. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=9392533

39

Fagundes MA, Hug EB, Liebsch NJ, et al. Radiation therapy for chordomas of the base of skull and cervical spine: patterns of failure and outcome after relapse. Int J Radiat Oncol Biol Phys. 1995; 33: 579-584.

40

Ares C, Hug EB, Lomax AJ, 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: 1111-1118. https://doi.org/10.1016/j.ijrobp.2008.12.055.

41

Grosshans DR, Zhu XR, Melancon A, et al. Spot scanning proton therapy for malignancies of the base of skull: treatment planning, acute toxicities, and preliminary clinical outcomes. Int J Radiat Oncol Biol Phys. 2014; 90: 540-546. https://doi.org/10.1016/j.ijrobp.2014.07.005.

42

Patel SH, Wang Z, Wong WW, et al. Charged particle therapy versus photon therapy for paranasal sinus and nasal cavity malignant diseases: a systematic review and meta-analysis. Lancet Oncol. 2014; 15: 1027-1038. https://doi.org/10.1016/S1470-2045(14)70268-2.

43

Fitzek MM, Thornton AF, Harsh Gt, et al. Dose-escalation with proton/photon irradiation for daumas-duport lower-grade glioma: results of an institutional phase Ⅰ/Ⅱ trial. Int J Radiat Oncol Biol Phys. 2001; 51: 131-137.

44

Hauswald H, Rieken S, Ecker S, et al. First experiences in treatment of low-grade glioma grade Ⅰ and Ⅱ with proton therapy. Radiat Oncol. 2012; 7:189. https://doi.org/10.1186/1748-717X-7-189.

45

Shih HA, Sherman JC, Nachtigall LB, et al. Proton therapy for low-grade gliomas: results from a prospective trial. Cancer. 2015:29237.

46

Brown PD, Chung C, Liu DD, et al. A prospective phase ii randomized trial of proton radiotherapy vs intensity-modulated radiotherapy for patients with newly diagnosed glioblastoma. Neuro Oncol. 2021; 23: 1337-1347. https://www.ncbi.nlm.nih.gov/pubmed/33647972

47

Kralik SF, Ho CY, Finke W, et al. Radiation necrosis in pediatric patients with brain tumors treated with proton radiotherapy. AJNR Am J Neuroradiol. 2015; 36: 1572-1578. https://www.ncbi.nlm.nih.gov/pubmed/26138138

48

Niemierko A, Schuemann J, Niyazi M, et al. Brain necrosis in adult patients after proton therapy: is there evidence for dependency on linear energy transfer? Int J Radiat Oncol Biol Phys. 2021; 109: 109-119. https://www.ncbi.nlm.nih.gov/pubmed/32911019

49

Eulitz J, Troost EGC, Raschke F, et al. Predicting late magnetic resonance image changes in glioma patients after proton therapy. Acta Oncol. 2019; 58: 1536-1539. https://www.ncbi.nlm.nih.gov/pubmed/31303083

50

Bahn E, Bauer J, Harrabi S, et al. Late contrast enhancing brain lesions in proton-treated patients with low-grade glioma: clinical evidence for increased periventricular sensitivity and variable RBE. Int J Radiat Oncol Biol Phys. 2020; 107: 571-578. https://www.ncbi.nlm.nih.gov/pubmed/32234554

51

Bush DA, Slater JD, Shin BB, et al. Hypofractionated proton beam radiotherapy for stage Ⅰ lung cancer. Chest. 2004; 126: 1198-1203. http://journal.publications.chestnet.org/data/Journals/CHEST/22017/1198.pdf

52

Koay EJ, Lege D, Mohan R, et al. Adaptive/nonadaptive proton radiation planning and outcomes in a phase Ⅱ trial for locally advanced non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2012; 84: 1093-1100. https://doi.org/10.1016/j.ijrobp.2012.02.041

53

Nakayama H, Sugahara S, Tokita M, et al. Proton beam therapy for patients with medically inoperable stage Ⅰ non-small-cell lung cancer at the University of Tsukuba. Int J Radiat Oncol Biol Phys. 2010; 78: 467-471. https://doi.org/10.1016/j.ijrobp.2009.07.1707

54

Liao Z, Lee JJ, Komaki R, et al. Bayesian adaptive randomization trial of passive scattering proton therapy and intensity-modulated photon radiotherapy for locally advanced non-small-cell lung cancer. J Clin Oncol. 2018; 36: 1813-1822. https://www.ncbi.nlm.nih.gov/pubmed/29293386

55

Tucker SL, Xu T, Paganetti H, et al. Validation of effective dose as a better predictor of radiation pneumonitis risk than mean lung dose: secondary analysis of a randomized trial. Int J Radiat Oncol Biol Phys. 2019; 103: 403-410. https://www.ncbi.nlm.nih.gov/pubmed/30291994

56

Xu T, Meng QH, Gilchrist SC, et al. Assessment of prognostic value of high-sensitivity cardiac troponin t for early prediction of chemoradiation therapy-induced cardiotoxicity in patients with non-small cell lung cancer: a secondary analysis of a prospective randomized trial. Int J Radiat Oncol Biol Phys. 2021; 111: 907-916. https://www.ncbi.nlm.nih.gov/pubmed/34302893

57

Xie X, Lin SH, Welsh JW, et al. Radiation-induced lymphopenia during chemoradiation therapy for non-small cell lung cancer is linked with age, lung v5, and xrcc1 rs25487 genotypes in lymphocytes. Radiother Oncol. 2021; 154: 187-193. https://www.ncbi.nlm.nih.gov/pubmed/32916236

58

Palma G, Monti S, Conson M, et al. NTCP models for severe radiation induced dermatitis after IMRT or proton therapy for thoracic cancer patients. Front Oncol. 2020; 10: 344. https://www.ncbi.nlm.nih.gov/pubmed/32257950

59

McNamara AL, Hall DC, Shusharina N, et al. Perspectives on the model-based approach to proton therapy trials: a retrospective study of a lung cancer randomized trial. Radiother Oncol. 2020; 147: 8-14. https://www.ncbi.nlm.nih.gov/pubmed/32224318

60

Yang P, Xu T, Gomez DR, et al. Patterns of local-regional failure after intensity modulated radiation therapy or passive scattering proton therapy with concurrent chemotherapy for non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2019; 103: 123-131. https://www.ncbi.nlm.nih.gov/pubmed/30165127

61

Palma G, Monti S, Xu T, et al. Spatial dose patterns associated with radiation pneumonitis in a randomized trial comparing intensity-modulated photon therapy with passive scattering proton therapy for locally advanced non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2019; 104: 1124-1132. https://www.ncbi.nlm.nih.gov/pubmed/30822531

62

Shusharina N, Liao Z, Mohan R, et al. Differences in lung injury after IMRT or proton therapy assessed by (18)FDG PET imaging. Radiother Oncol. 2018; 128: 147-153. https://www.ncbi.nlm.nih.gov/pubmed/29352608

63

Yang P, Liao Z, Gomez DR, et al. Prospective study of marginal recurrence in patients with non-small cell lung cancer after proton or photon chemoradiation therapy. Int J Radiat Oncol Biol Phys. 2017; 98: 234. https://www.ncbi.nlm.nih.gov/pubmed/28587001

64

Xi M, Xu C, Liao ZX, et al. Comparative outcomes after definitive chemoradiotherapy using proton beam therapy versus intensity modulated radiation therapy for esophageal cancer: a retrospective, single-institutional analysis. Int J Radiat Oncol. 2017; 99: 667-676.

65

Deist TM, Yang P, Oberije C, et al. Dosimetric analysis of randomized proton and photon plans with respect to radiation toxicity: the importance of high dose regions in lung and esophagus. Int J Radiat Oncol Biol Phys. 2017; 98: 246. https://www.ncbi.nlm.nih.gov/pubmed/28587033

66

Lin SH, Hobbs BP, Verma V, et al. Randomized phase IIB trial of proton beam therapy versus intensity-modulated radiation therapy for locally advanced esophageal cancer. J Clin Oncol. 2020; 38: 1569-1579. https://www.ncbi.nlm.nih.gov/pubmed/32160096

67

Manzar GS, Lester SC, Routman DM, et al. Comparative analysis of acute toxicities and patient reported outcomes between intensity-modulated proton therapy (impt) and volumetric modulated arc therapy (vmat) for the treatment of oropharyngeal cancer. Radiother Oncol. 2020; 147: 64-74. https://www.ncbi.nlm.nih.gov/pubmed/32234612

68

Sio TT, Lin HK, Shi Q, et al. Intensity modulated proton therapy versus intensity modulated photon radiation therapy for oropharyngeal cancer: First comparative results of patient-reported outcomes. Int J Radiat Oncol Biol Phys. 2016; 95: 1107-1114. https://www.ncbi.nlm.nih.gov/pubmed/27354125

69

Matney J, Park PC, Bluett J, et al. Effects of respiratory motion on passively scattered proton therapy versus intensity modulated photon therapy for stage Ⅲ lung cancer: are proton plans more sensitive to breathing motion? Int J Radiat Oncol Biol Phys. 2013; 87: 576-582. http://www.ncbi.nlm.nih.gov/pubmed/24074932

70

Ge S, Wang X, Liao Z, et al. Potential for improvements in robustness and optimality of intensity-modulated proton therapy for lung cancer with 4-dimensional robust optimization. Cancers (Basel) 2019; 11: 35. https://www.ncbi.nlm.nih.gov/pubmed/30609652

71

Liu Q, Ghosh P, Magpayo N, et al. Lung cancer cell line screen links fanconi anemia/BRCA pathway defects to increased relative biological effectiveness of proton radiation. Int J Radiat Oncol Biol Phys. 2015; 91: 1081-1089. https://www.ncbi.nlm.nih.gov/pubmed/25832698

72

Carabe-Fernandez A, Dale RG, Jones B. The incorporation of the concept of minimum RBE (RbEmin) into the linear-quadratic model and the potential for improved radiobiological analysis of high-let treatments. Int J Radiat Biol. 2007; 83: 27-39. https://www.ncbi.nlm.nih.gov/pubmed/17357437

73

Frese MC, Yu VK, Stewart RD, et al. A mechanism-based approach to predict the relative biological effectiveness of protons and carbon ions in radiation therapy. Int J Radiat Oncol Biol Phys. 2012; 83: 442-450. http://www.ncbi.nlm.nih.gov/pubmed/22099045

74

Carlson DJ, Stewart RD, Semenenko VA, et al. Combined use of Monte Carlo DNA damage simulations and deterministic repair models to examine putative mechanisms of cell killing. Radiat Res. 2008; 169: 447-459. http://www.ncbi.nlm.nih.gov/pubmed/18363426

75

McNamara AL, Schuemann J, Paganetti H. A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data. Phys Med Biol. 2015; 60: 8399-8416. http://www.ncbi.nlm.nih.gov/pubmed/26459756

76

Chen Y, Ahmad S. Empirical model estimation of relative biological effectiveness for proton beam therapy. Radiat Prot Dosimetry. 2012; 149: 116-123. https://www.ncbi.nlm.nih.gov/pubmed/21593038

77

Wedenberg M, Lind BK, Hardemark B. A model for the relative biological effectiveness of protons: the tissue specific parameter alpha/beta of photons is a predictor for the sensitivity to let changes. Acta Oncol. 2013; 52: 580-588. https://www.ncbi.nlm.nih.gov/pubmed/22909391

78

Wilkens JJ, Oelfke U. A phenomenological model for the relative biological effectiveness in therapeutic proton beams. Phys Med Biol. 2004; 49: 2811-2825. http://www.ncbi.nlm.nih.gov/pubmed/15285249

79

Cao W, Khabazian A, Yepes PP, et al. Linear energy transfer incorporated intensity modulated proton therapy optimization. Phys Med Biol. 2017; 63:015013. https://www.ncbi.nlm.nih.gov/pubmed/29131808

80

Unkelbach J, Botas P, Giantsoudi D, et al. Reoptimization of intensity modulated proton therapy plans based on linear energy transfer. Int J Rad Onc Biol Phys. 2016; 96: 1097– 1106. https://www.ncbi.nlm.nih.gov/pubmed/27869082

81

Lomax AJ. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 1: the potential effects of calculational uncertainties. Phys Med Biol. 2008; 53: 1027-1042. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18263956

82

Lomax AJ. 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: 1043-1056. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18263957

83

Park PC, Cheung JP, Zhu XR, et al. Statistical assessment of proton treatment plans under setup and range uncertainties. Int J Radiat Oncol Biol Phys. 2013; 86: 1007-1013. http://www.ncbi.nlm.nih.gov/pubmed/23688812

84

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: 1689-1700. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18367797

85

Unkelbach J, Chan TC, Bortfeld T. Accounting for range uncertainties in the optimization of intensity modulated proton therapy. Phys Med Biol. 2007; 52: 2755-2773. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17473350

86

Liu W, Frank SJ, Li X, et al. Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers. Med Phys. 2013; 40:051711. http://www.ncbi.nlm.nih.gov/pubmed/23635259

87

Liu W, Frank SJ, Li X, et al. PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization. Med Phys. 2013; 40:021709. http://www.ncbi.nlm.nih.gov/pubmed/23387732

88

Liu W, Li Y, Li X, et al. Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques. Med Phys. 2012; 39: 3089-3101. http://www.ncbi.nlm.nih.gov/pubmed/22755694

89

Liu W, Liao Z, Schild SE, et al. Impact of respiratory motion on worst-case scenario optimized intensity modulated proton therapy for lung cancers. Pract Radiat Oncol 2015; 5: e77-86. http://www.ncbi.nlm.nih.gov/pubmed/25413400

90

Liu W, Mohan R, Park P, et al. Dosimetric benefits of robust treatment planning for intensity modulated proton therapy for base-of-skull cancers. Pract Radiat Oncol. 2014; 4: 384-391. http://www.ncbi.nlm.nih.gov/pubmed/25407859

91

Liu W, Zhang X, Li Y, et al. Robust optimization in intensity-modulated proton therapy. Med Phys. 2012; 39: 1079-1091.

92

Liu W, Zhang X, Li Y, et al. Robust optimization of intensity modulated proton therapy. Med Phys. 2012; 39: 1079-1091. http://www.ncbi.nlm.nih.gov/pubmed/22320818

93

Fredriksson A. A characterization of robust radiation therapy treatment planning methods-from expected value to worst case optimization. Med Phys. 2012; 39: 5169-5181. http://www.ncbi.nlm.nih.gov/pubmed/22894442

94

Fredriksson A, Bokrantz R. A critical evaluation of worst case optimization methods for robust intensity-modulated proton therapy planning. Med Phys. 2014; 41:081701. http://www.ncbi.nlm.nih.gov/pubmed/25086511

95

Fredriksson A, Forsgren A, Hardemark B. Minimax optimization for handling range and setup uncertainties in proton therapy. Med Phys. 2011; 38: 1672-1684. http://www.ncbi.nlm.nih.gov/pubmed/21520880

96

Stone HB, Peters LJ, Milas L. Effect of host immune capability on radiocurability and subsequent transplantability of a murine fibrosarcoma. J Natl Cancer Inst. 1979; 63: 1229-1235. https://www.ncbi.nlm.nih.gov/pubmed/291749

97
Dunst J, Neubauer S, Gebhart E. In-vitro radiosensitivity of lymphocytes and clinical radiation reaction. Eur J Cancer. 1997; 33: 441-441. ://WOS:A1997XX83000436
98

Yovino S, Kleinberg L, Grossman SA, et al. The etiology of treatment-related lymphopenia in patients with malignant gliomas: modeling radiation dose to circulating lymphocytes explains clinical observations and suggests methods of modifying the impact of radiation on immune cells. Cancer Invest. 2013; 31: 140-144. http://www.ncbi.nlm.nih.gov/pubmed/23362951

99

Grassberger C, Hong TS, Hato T, et al. Differential association between circulating lymphocyte populations with outcome after radiation therapy in subtypes of liver cancer. Int J Radiat Oncol. 2018; 101: 1222-1225.

100
Liu J, Zhao QQ, Deng WY, et al. Radiation-related lymphopenia is associated with spleen irradiation dose during radiotherapy in patients with hepatocellular carcinoma. Radiat Oncol. 2017; 12: 90. ://WOS:000402577100001
101

Grossman SA, Ellsworth S, Campian J, et al. Survival in patients with severe lymphopenia following treatment with radiation and chemotherapy for newly diagnosed solid tumors. J Natl Compr Canc Netw. 2015; 13: 1225-1231. https://www.ncbi.nlm.nih.gov/pubmed/26483062

102

Wild AT, Ye X, Ellsworth SG, et al. The association between chemoradiation-related lymphopenia and clinical outcomes in patients with locally advanced pancreatic adenocarcinoma. Am J Clin Oncol. 2015; 38: 259-265. https://www.ncbi.nlm.nih.gov/pubmed/23648440

103

Wild AT, Herman JM, Dholakia AS, et al. Lymphocyte-sparing effect of stereotactic body radiation therapy in patients with unresectable pancreatic cancer. Int J Radiat Oncol Biol Phys. 2016; 94: 571-579. https://www.ncbi.nlm.nih.gov/pubmed/26867885

104

Ku GY, Yuan J, Page DB, et al. Single-institution experience with ipilimumab in advanced melanoma patients in the compassionate use setting: lymphocyte count after 2 doses correlates with survival. Cancer. 2010; 116: 1767-1775. https://www.ncbi.nlm.nih.gov/pubmed/20143434

105

Fumagalli LA, Vinke J, Hoff W, et al. Lymphocyte counts independently predict overall survival in advanced cancer patients: a biomarker for il-2 immunotherapy. J Immunother. 2003; 26: 394-402. https://www.ncbi.nlm.nih.gov/pubmed/12973028

106

Davuluri R, Jiang W, Fang P, et al. Lymphocyte nadir and esophageal cancer survival outcomes after chemoradiation therapy. Int J Radiat Oncol Biol Phys. 2017; 99: 128-135. https://www.ncbi.nlm.nih.gov/pubmed/28816138

107

Cao W, Lim GJ, Li Y, et al. Improved beam angle arrangement in intensity modulated proton therapy treatment planning for localized prostate cancer. Cancers (Basel) 2015; 7: 574-584. https://www.ncbi.nlm.nih.gov/pubmed/25831258

108

Cao W, Lim GJ, Lee A, et al. Uncertainty incorporated beam angle optimization for impt treatment planning. Med Phys. 2012; 39: 5248-5256.

109

Gu W, Ruan D, Zou W, et al. Linear energy transfer weighted beam orientation optimization for intensity-modulated proton therapy. Med Phys. 2021; 48: 57-70. https://www.ncbi.nlm.nih.gov/pubmed/32542711

110

Gu W, Ruan D, O'Connor D, et al. Robust optimization for intensity-modulated proton therapy with soft spot sensitivity regularization. Med Phys. 2019; 46: 1408-1425. https://www.ncbi.nlm.nih.gov/pubmed/30570164

111

Gu W, Neph R, Ruan D, et al. Robust beam orientation optimization for intensity-modulated proton therapy. Med Phys. 2019; 46: 3356-3370. https://www.ncbi.nlm.nih.gov/pubmed/31169917

112

Gu W, O'Connor D, Nguyen D, et al. Integrated beam orientation and scanning-spot optimization in intensity-modulated proton therapy for brain and unilateral head and neck tumors. Med Phys. 2018; 45: 1338-1350. https://www.ncbi.nlm.nih.gov/pubmed/29394454

113

Brodin NP, Kabarriti R, Schechter CB, et al. Individualized quality of life benefit and cost-effectiveness estimates of proton therapy for patients with oropharyngeal cancer. Radiat Oncol. 2021; 16: 19. https://www.ncbi.nlm.nih.gov/pubmed/33478544

114

Thaker NG, Frank SJ, Feeley TW. Comparative costs of advanced proton and photon radiation therapies: lessons from time-driven activity-based costing in head and neck cancer. J Comp Eff Res. 2015; 4: 297-301. http://www.ncbi.nlm.nih.gov/pubmed/26274791

115

Huang D, Frank SJ, Verma V, et al. Cost-effectiveness models of proton therapy for head and neck: evaluating quality and methods to date. Int J Part Ther. 2021; 8: 339-353. https://www.ncbi.nlm.nih.gov/pubmed/34285960

116

Langendijk JA, Hoebers FJP, de Jong MA, et al. National protocol for model-based selection for proton therapy in head and neck cancer. Int J Part Ther. 2021; 8: 354-365. https://www.ncbi.nlm.nih.gov/pubmed/34285961

117

Boersma LJ, Sattler MGA, Maduro JH, et al. Model-based selection for proton therapy in breast cancer: development of the national indication protocol for proton therapy and first clinical experiences. Clin Oncol (R Coll Radiol). 2022; 34: 247-257. https://www.ncbi.nlm.nih.gov/pubmed/34996684

118

Widder J, van der Schaaf A, Lambin P, et al. The quest for evidence for proton therapy: model-based approach and precision medicine. Int J Radiat Oncol Biol Phys. 2016; 95: 30-36. https://www.ncbi.nlm.nih.gov/pubmed/26684410

119

Langendijk JA, Lambin P, De Ruysscher D, et al. Selection of patients for radiotherapy with protons aiming at reduction of side effects: the model-based approach. Radiother Oncol. 2013; 107: 267-273. https://www.ncbi.nlm.nih.gov/pubmed/23759662

Precision Radiation Oncology
Pages 164-176
Cite this article:
Mohan R. A review of proton therapy – Current status and future directions. Precision Radiation Oncology, 2022, 6(2): 164-176. https://doi.org/10.1002/pro6.1149

495

Views

73

Crossref

63

Scopus

Altmetrics

Received: 24 February 2022
Accepted: 03 March 2020
Published: 27 April 2022
© 2022 The Authors. Precision Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of Shandong Cancer Hospital & Institute.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Return