Optimization of combined proton-photon treatments.

PURPOSE Proton treatment slots are a limited resource. Therefore, we consider combined proton-photon treatments in which most fractions are delivered with photons and only a few with protons. We demonstrate how both modalities can be combined to optimally capitalize on the proton's ability to reduce normal tissue dose. METHODS An optimal combined treatment must account for fractionation effects. We therefore perform simultaneous optimization of intensity-modulated proton (IMPT) and photon (IMRT) plans based on their cumulative biologically effective dose (BED). We demonstrate the method for a sacral chordoma patient, in whom the gross tumor volume (GTV) abuts bowel and rectum. RESULTS In an optimal combination, proton and photon fractions deliver similar doses to bowel and rectum to protect these dose-limiting normal tissues through fractionation. However, proton fractions deliver, on average, higher doses to the GTV. Thereby, the photon dose bath is reduced. An optimized 30-fraction treatment with 10 IMPT fractions achieved more than 50% of the integral dose reduction in the gastrointestinal tract that is possible with 30 IMPT fractions (compared to 33% for a simple proton-photon combination in which both modalities deliver the same target dose). CONCLUSIONS A limited number of proton fractions can best be used if protons hypofractionate parts of the GTV while maintaining near-uniform fractionation in dose-limiting normal tissues.

[1]  Harald Paganetti,et al.  Predicting Patient-specific Dosimetric Benefits of Proton Therapy for Skull-base Tumors Using a Geometric Knowledge-based Method. , 2017, International journal of radiation oncology, biology, physics.

[2]  Johannes A Langendijk,et al.  Selection of patients for radiotherapy with protons aiming at reduction of side effects: the model-based approach. , 2013, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[3]  Alfred R. Smith,et al.  Vision 20/20: proton therapy. , 2009, Medical physics.

[4]  Timothy C Y Chan,et al.  Accounting for range uncertainties in the optimization of intensity modulated proton therapy , 2007, Physics in medicine and biology.

[5]  A. Lühr,et al.  NTCP reduction for advanced head and neck cancer patients using proton therapy for complete or sequential boost treatment versus photon therapy , 2015, Acta oncologica.

[6]  J. Wunder,et al.  Chordoma: long-term follow-up after radical photon irradiation. , 1996, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[7]  Lei Xing,et al.  Optimization approaches to volumetric modulated arc therapy planning. , 2015, Medical physics.

[8]  Non-uniform spatiotemporal fractionation schemes in photon radiotherapy , 2015 .

[9]  Radhe Mohan,et al.  Proton therapy - Present and future. , 2017, Advanced drug delivery reviews.

[10]  Anders Forsgren,et al.  Minimax optimization for handling range and setup uncertainties in proton therapy. , 2011, Medical physics.

[11]  B. Yeap,et al.  Long‐term results of Phase II study of high dose photon/proton radiotherapy in the management of spine chordomas, chondrosarcomas, and other sarcomas , 2014, Journal of surgical oncology.

[12]  Radhe Mohan,et al.  Robust optimization of intensity modulated proton therapy. , 2012, Medical physics.

[13]  Thomas Bortfeld,et al.  Evolution of technology to optimize the delivery of proton therapy: the third generation. , 2013, Seminars in radiation oncology.

[14]  J. Régis,et al.  Stereotactic body radiotherapy for de novo spinal metastases: systematic review. , 2017, Journal of neurosurgery. Spine.

[15]  Max Dahele,et al.  Using a knowledge-based planning solution to select patients for proton therapy. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[16]  Katia Parodi,et al.  Development of the open‐source dose calculation and optimization toolkit matRad , 2017, Medical physics.

[17]  Oliver Jäkel,et al.  matRad - a multi-modality open source 3D treatment planning toolkit , 2015 .

[18]  T. Delaney,et al.  Chordomas and chondrosarcomas—The role of radiation therapy , 2016, Journal of surgical oncology.

[19]  Jan Unkelbach,et al.  Simultaneous optimization of dose distributions and fractionation schemes in particle radiotherapy. , 2013, Medical physics.

[20]  U Oelfke,et al.  Worst case optimization: a method to account for uncertainties in the optimization of intensity modulated proton therapy , 2008, Physics in medicine and biology.

[21]  Dan T. L. Jones,et al.  Bioeffect modeling and equieffective dose concepts in radiation oncology--terminology, quantities and units. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[22]  Philipp Hennig,et al.  Analytical probabilistic modeling for radiation therapy treatment planning , 2013, Physics in medicine and biology.

[23]  Thomas Bortfeld,et al.  Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning. , 2008, Medical physics.

[24]  J. Debus,et al.  Treatment with heavy charged particles: Systematic review of clinical data and current clinical (comparative) trials , 2013, Acta oncologica.

[25]  Jan Unkelbach,et al.  Spatiotemporal Fractionation Schemes for Irradiating Large Cerebral Arteriovenous Malformations. , 2016, International journal of radiation oncology, biology, physics.

[26]  J F Fowler,et al.  21 years of biologically effective dose. , 2010, The British journal of radiology.

[27]  Dávid Papp,et al.  The emergence of nonuniform spatiotemporal fractionation schemes within the standard BED model. , 2015, Medical physics.

[28]  T. Delaney,et al.  Sacral chordomas: Impact of high-dose proton/photon-beam radiation therapy combined with or without surgery for primary versus recurrent tumor. , 2006, International journal of radiation oncology, biology, physics.