Pre‐treatment analysis of non‐rigid variations can assist robust intensity‐modulated proton therapy plan selection for head and neck patients

Abstract Purpose To incorporate small non‐rigid variations of head and neck patients into the robust evaluation of intensity‐modulated proton therapy (IMPT) for the selection of robust treatment plans. Methods A cohort of 20 nasopharynx cancer patients with weekly kilovoltage CT (kVCT) and 15 oropharynx cancer patients with weekly cone‐beam CT (CBCT) were retrospectively included. Anatomical variations between week 0/week 1 of treatment were acquired using deformable image registration (DIR) for all 35 patients and then applied to the planning CT of four patients who have kVCT scanned each week to simulate potential small non‐rigid variations (sNRVs). The robust evaluations were conducted on IMPT plans with: (1) different number of beam fields from 3‐field to 5‐field; (2) different beam angles. The robust evaluation before treatment, including the sNRVs and setup uncertainty, referred to as sNRV+R evaluation was compared with the conventional evaluation (without sNRVs) in terms of robustness consistency with the gold standard evaluation based on weekly CT. Results Among four patients (490 scenarios), we observed a maximum difference in the sNRV+R evaluation to the nominal dose of: 9.37% dose degradation on D 95 of clinical target volumes (CTVs), increase in mean dose (D mean) of parotid 11.87 Gy, increase in max dose (D max) of brainstem 20.82 Gy. In contrast, in conventional evaluation, we observed a maximum difference to the nominal dose of: 7.58% dose degradation on D 95 of the CTVs, increase in parotid Dmean by 4.88 Gy, increase in brainstem D max by 13.5 Gy. In the measurement of the robustness ranking consistency with the gold standard evaluation, the sNRV+R evaluation was better or equal to the conventional evaluation in 77% of cases, particularly, better on spinal cord, parotid glands, and low‐risk CTV. Conclusion This study demonstrated the additional dose discrepancy that sNRVs can make. The inclusion of sNRVs can be beneficial to robust evaluation, providing information on clinical uncertainties additional to the conventional rigid isocenter shift.

[1]  G. Royle,et al.  Improving workflow for adaptive proton therapy with predictive anatomical modelling: A proof of concept. , 2022, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[2]  G. Royle,et al.  DIR-based models to predict weekly anatomical changes in head and neck cancer proton therapy , 2022, Physics in medicine and biology.

[3]  M. Gaze,et al.  Atlas construction and spatial normalisation to facilitate radiation-induced late effects research in childhood cancer , 2021, Physics in medicine and biology.

[4]  G. Sharp,et al.  Anatomic changes in head and neck intensity-modulated proton therapy: comparison between robust optimization and online adaptation. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[5]  A. Lomax,et al.  Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy , 2021, Physics in medicine and biology.

[6]  Ana Vaniqui,et al.  What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans. , 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[7]  R. Onimaru,et al.  Potential benefits of adaptive intensity-modulated proton therapy in nasopharyngeal carcinomas. , 2020, Journal of applied clinical medical physics.

[8]  Xiaodong Zhang,et al.  Multiple-CT optimization: An adaptive optimization method to account for anatomical changes in intensity-modulated proton therapy for head and neck cancers. , 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[9]  Lei Dong,et al.  Inter-fraction robustness of Intensity-Modulated proton therapy in the Post-operative treatment of oropharyngeal and oral cavity squamous cell carcinomas. , 2019, The British journal of radiology.

[10]  Christian Richter,et al.  Quantification of plan robustness against different uncertainty sources for classical and anatomical robust optimized treatment plans in head and neck cancer proton therapy. , 2019, The British journal of radiology.

[11]  A. Lomax,et al.  Intensity modulated proton therapy plan generation in under ten seconds , 2019, Acta oncologica.

[12]  N. Lester-Coll,et al.  Modeling the Potential Benefits of Proton Therapy for Patients With Oropharyngeal Head and Neck Cancer. , 2019, International journal of radiation oncology, biology, physics.

[13]  Christian Richter,et al.  Including anatomical variations in robust optimization for head and neck proton therapy can reduce the need of adaptation. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[14]  J. Lagendijk,et al.  Intrafraction motion quantification and planning target volume margin determination of head-and-neck tumors using cine magnetic resonance imaging. , 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[15]  Radhe Mohan,et al.  Comparison of Monte Carlo and analytical dose computations for intensity modulated proton therapy , 2018, Physics in medicine and biology.

[16]  Radhe Mohan,et al.  Intensity-Modulated Proton Therapy Adaptive Planning for Patients with Oropharyngeal Cancer. , 2017, International journal of particle therapy.

[17]  S M Holloway,et al.  A method for acquiring random range uncertainty probability distributions in proton therapy , 2017, Physics in medicine and biology.

[18]  Steffen Löck,et al.  Potential proton and photon dose degradation in advanced head and neck cancer patients by intratherapy changes , 2017, Journal of applied clinical medical physics.

[19]  A. van der Schaaf,et al.  Selection of head and neck cancer patients for adaptive radiotherapy to decrease xerostomia. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[20]  A. Lomax,et al.  Evaluation of Robustness to Setup and Range Uncertainties for Head and Neck Patients Treated With Pencil Beam Scanning Proton Therapy. , 2016, International journal of radiation oncology, biology, physics.

[21]  A J Lomax,et al.  Defining robustness protocols: a method to include and evaluate robustness in clinical plans , 2015, Physics in medicine and biology.

[22]  Hanne M Kooy,et al.  Dose uncertainties in IMPT for oropharyngeal cancer in the presence of anatomical, range, and setup errors. , 2013, International journal of radiation oncology, biology, physics.

[23]  Y. Li,et al.  Target volume and position variations during intensity-modulated radiotherapy for patients with nasopharyngeal carcinoma , 2013, OncoTargets and therapy.

[24]  Zhongjie Lu,et al.  Predictors for replanning in loco-regionally advanced nasopharyngeal carcinoma patients undergoing intensity-modulated radiation therapy: a prospective observational study , 2013, BMC Cancer.

[25]  Johannes A Langendijk,et al.  Potential benefits of scanned intensity-modulated proton therapy versus advanced photon therapy with regard to sparing of the salivary glands in oropharyngeal cancer. , 2011, International journal of radiation oncology, biology, physics.

[26]  Johannes A Langendijk,et al.  The potential benefit of radiotherapy with protons in head and neck cancer with respect to normal tissue sparing: a systematic review of literature. , 2011, The oncologist.

[27]  Kevin J Harrington,et al.  Weekly volume and dosimetric changes during chemoradiotherapy with intensity-modulated radiation therapy for head and neck cancer: a prospective observational study. , 2010, International journal of radiation oncology, biology, physics.

[28]  Weiguo Lu,et al.  Evaluation of geometric changes of parotid glands during head and neck cancer radiotherapy using daily MVCT and automatic deformable registration. , 2008, Radiotherapy and Oncology.

[29]  Brian B. Avants,et al.  Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..

[30]  Uwe Schneider,et al.  Intensity modulated photon and proton therapy for the treatment of head and neck tumors. , 2006, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[31]  Ping Xia,et al.  Repeat CT imaging and replanning during the course of IMRT for head-and-neck cancer. , 2006, International journal of radiation oncology, biology, physics.

[32]  Radhe Mohan,et al.  Quantification of volumetric and geometric changes occurring during fractionated radiotherapy for head-and-neck cancer using an integrated CT/linear accelerator system. , 2004, International journal of radiation oncology, biology, physics.

[33]  A J Lomax,et al.  Treatment planning optimisation in proton therapy. , 2013, The British journal of radiology.