Significance of intra-fractional motion for pancreatic patients treated with charged particles

BackgroundUncertainties associated with the delivery of treatment to moving organs might compromise the accuracy of treatment. This study explores the impact of intra-fractional anatomical changes in pancreatic patients treated with charged particles delivered using a scanning beam. The aim of this paper is to define the potential source of uncertainties, quantify their effect, and to define clinically feasible strategies to reduce them.MethodsThe study included 14 patients treated at our facility with charged particles (protons or 12C) using intensity modulated particle therapy (IMPT). Treatment plans were optimized using the Treatment Planning System (TPS) Syngo® RT Planning. The pre-treatment dose distribution under motion (4D) was simulated using the TPS TRiP4D and the dose delivered for some of the treatment fractions was reconstructed. The volume receiving at least 95% of the prescribed dose (V95CTV) and the target dose homogeneity were evaluated. The results from the 4D dose calculations were compared with dose distributions in the static case and its variation correlated with the internal motion amplitude and plan modulation, through the Pearson correlation coefficient, as well the significant p-value. The concept of the modulation index (MI) was introduced to assess the degree of modulation of IMPT plans, through the quantification of intensity gradients between neighboring pencil beams.ResultsThe induced breathing motion together with dynamic beam delivery results in an interplay effect, which affects the homogeneity and target coverage of the dose distribution. This effect is stronger (∆V95CTV > 10%) for patients with tumor motion amplitude above 5 mm and a highly modulated dose distribution between and within fields. The MI combined with the internal motion amplitude is shown to correlate with the target dose degradation and a lack of plan robustness against range and positioning uncertainties.ConclusionsUnder internal motion the use of inhomogeneous plans results in a decrease in the dose homogeneity and target coverage of dose distributions in comparison to the static case. Plan robustness can be improved by using multiple beams and avoiding beam entrance directions susceptible to density changes. 4D dose calculations support the selection of the most suitable plan for the specific patient’s anatomy.

[1]  G. Sharp,et al.  Comparison of respiratory-gated and respiratory-ungated planning in scattered carbon ion beam treatment of the pancreas using four-dimensional computed tomography. , 2010, International journal of radiation oncology, biology, physics.

[2]  S. Zucca,et al.  Free‐breathing conformal irradiation of pancreatic cancer , 2013, Journal of applied clinical medical physics.

[3]  A J Lomax,et al.  Comparative study of layered and volumetric rescanning for different scanning speeds of proton beam in liver patients , 2013, Physics in medicine and biology.

[4]  M. Durante,et al.  In silico comparison of photons versus carbon ions in single fraction therapy of lung cancer. , 2016, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[5]  S. Combs,et al.  Planning strategies for inter-fractional robustness in pancreatic patients treated with scanned carbon therapy , 2017, Radiation oncology.

[6]  Christoph Bert,et al.  Quantification of interplay effects of scanned particle beams and moving targets , 2008, Physics in medicine and biology.

[7]  S. Combs,et al.  Effective radiotherapeutic treatment intensification in patients with pancreatic cancer: higher doses alone, higher RBE or both? , 2017, Radiation oncology.

[8]  Wei Liu,et al.  Robust optimization in intensity-modulated proton therapy to account for anatomy changes in lung cancer patients. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[9]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[10]  D. Richter Treatment planning for tumors with residual motion in scanned ion beam therapy , 2012 .

[11]  Steve B. Jiang,et al.  Assessing residual motion for gated proton-beam radiotherapy. , 2007, Journal of radiation research.

[12]  X Allen Li,et al.  Management of respiration-induced motion with 4-dimensional computed tomography (4DCT) for pancreas irradiation. , 2013, International journal of radiation oncology, biology, physics.

[13]  C Bert,et al.  Motion in radiotherapy: particle therapy , 2011, Physics in medicine and biology.

[14]  N Kandasamy,et al.  On developing B-spline registration algorithms for multi-core processors , 2010, Physics in medicine and biology.

[15]  Marco Durante,et al.  Residual motion mitigation in scanned carbon ion beam therapy of liver tumors using enlarged pencil beam overlap. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[16]  E. Larsen,et al.  A method for incorporating organ motion due to breathing into 3D dose calculations. , 1999, Medical physics.

[17]  Hiroshi Honda,et al.  Carbon Ion Radiation Therapy With Concurrent Gemcitabine for Patients With Locally Advanced Pancreatic Cancer. , 2016, International journal of radiation oncology, biology, physics.

[18]  M. Durante,et al.  Assessment of uncertainties in treatment planning for scanned ion beam therapy of moving tumors. , 2013, International journal of radiation oncology, biology, physics.

[19]  Shinichiro Mori,et al.  Comparison of carbon-ion passive and scanning irradiation for pancreatic cancer. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[20]  Christoph Bert,et al.  4D optimization of scanned ion beam tracking therapy for moving tumors , 2014, Physics in medicine and biology.

[21]  C. Mathers,et al.  Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012 , 2015, International journal of cancer.

[22]  A. Jemal,et al.  Cancer statistics, 2017 , 2017, CA: a cancer journal for clinicians.

[23]  S Webb,et al.  Use of a quantitative index of beam modulation to characterize dose conformality: illustration by a comparison of full beamlet IMRT, few-segment IMRT (fsIMRT) and conformal unmodulated radiotherapy. , 2003, Physics in medicine and biology.

[24]  A. Zietman Particle Therapy at the "Tipping Point": An Introduction to the Red Journal's Special Edition. , 2016, International journal of radiation oncology, biology, physics.

[25]  A J Lomax,et al.  Intensity modulated proton therapy and its sensitivity to treatment uncertainties 2: the potential effects of inter-fraction and inter-field motions , 2008, Physics in medicine and biology.

[26]  Marco Durante,et al.  Four-dimensional patient dose reconstruction for scanned ion beam therapy of moving liver tumors. , 2014, International journal of radiation oncology, biology, physics.

[27]  Meinhard Kieser,et al.  Phase I study evaluating the treatment of patients with locally advanced pancreatic cancer with carbon ion radiotherapy: the PHOENIX-01 trial , 2013, BMC Cancer.

[28]  L. Court,et al.  TH‐C‐BRB‐07: Feasibility of Online Range Adaptive Spot Scanning Proton Therapy , 2012 .

[29]  Chiara Gianoli,et al.  MRI quantification of pancreas motion as a function of patient setup for particle therapy -a preliminary study. , 2016, Journal of applied clinical medical physics.

[30]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[31]  P. Steidl Gating for scanned ion beam therapy , 2011 .