Performance of a Knowledge-Based Model for Optimization of Volumetric Modulated Arc Therapy Plans for Single and Bilateral Breast Irradiation

Purpose To evaluate the performance of a model-based optimisation process for volumetric modulated arc therapy, VMAT, applied to whole breast irradiation. Methods and Materials A set of 150 VMAT dose plans with simultaneous integrated boost were selected to train a model for the prediction of dose-volume constraints. The dosimetric validation was done on different groups of patients from three institutes for single (50 cases) and bilateral breast (20 cases). Results Quantitative improvements were observed between the model-based and the reference plans, particularly for heart dose. Of 460 analysed dose-volume objectives, 13% of the clinical plans failed to meet the constraints while the respective model-based plans succeeded. Only in 5 cases did the reference plans pass while the respective model-based failed the criteria. For the bilateral breast analysis, the model-based plans resulted in superior or equivalent dose distributions to the reference plans in 96% of the cases. Conclusions Plans optimised using a knowledge-based model to determine the dose-volume constraints showed dosimetric improvements when compared to earlier approved clinical plans. The model was applicable to patients from different centres for both single and bilateral breast irradiation. The data suggests that the dose-volume constraint optimisation can be effectively automated with the new engine and could encourage its application to clinical practice.

[1]  Fang-Fang Yin,et al.  Impact of volumetric modulated arc therapy technique on treatment with partial breast irradiation. , 2010, International journal of radiation oncology, biology, physics.

[2]  Pietro Mancosu,et al.  Phase I-II study of hypofractionated simultaneous integrated boost using volumetric modulated arc therapy for adjuvant radiation therapy in breast cancer patients: a report of feasibility and early toxicity results in the first 50 treatments , 2012, Radiation Oncology.

[3]  Sasa Mutic,et al.  Predicting dose-volume histograms for organs-at-risk in IMRT planning. , 2012, Medical physics.

[4]  J. Lo,et al.  A knowledge-based approach to improving and homogenizing intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning. , 2013, International journal of radiation oncology, biology, physics.

[5]  Tonghai Liu,et al.  Dosimetric research on intensity-modulated arc radiotherapy planning for left breast cancer after breast-preservation surgery. , 2012, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[6]  Luca Cozzi,et al.  Assessment of a model based optimization engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer , 2014, Radiation Oncology.

[7]  Y. Ge,et al.  Quantitative analysis of the factors which affect the interpatient organ-at-risk dose sparing variation in IMRT plans. , 2012, Medical physics.

[8]  Luca Cozzi,et al.  Simultaneous integrated boost radiotherapy for bilateral breast: a treatment planning and dosimetric comparison for volumetric modulated arc and fixed field intensity modulated therapy , 2009, Radiation oncology.

[9]  Vorakarn Chanyavanich,et al.  Knowledge-based IMRT treatment planning for prostate cancer , 2010, Medical physics.

[10]  D. Gaffney,et al.  Volumetric modulated arc therapy improves dosimetry and reduces treatment time compared to conventional intensity-modulated radiotherapy for locoregional radiotherapy of left-sided breast cancer and internal mammary nodes , 2010 .

[11]  J. Gibbons,et al.  Evaluation of volumetric modulated arc therapy for postmastectomy treatment , 2014, Radiation oncology.

[12]  Richard Shaffer,et al.  Volumetric modulated arc therapy improves dosimetry and reduces treatment time compared to conventional intensity-modulated radiotherapy for locoregional radiotherapy of left-sided breast cancer and internal mammary nodes. , 2010, International journal of radiation oncology, biology, physics.

[13]  Fang-Fang Yin,et al.  A planning quality evaluation tool for prostate adaptive IMRT based on machine learning. , 2011, Medical physics.

[14]  L. Cozzi,et al.  A planning comparison of dose patterns in organs at risk and predicted risk for radiation induced malignancy in the contralateral breast following radiation therapy of primary breast using conventional, IMRT and Volumetric modulated arc treatment techniques , 2009, Acta oncologica.

[15]  Luca Cozzi,et al.  On the pre-clinical validation of a commercial model-based optimisation engine: application to volumetric modulated arc therapy for patients with lung or prostate cancer. , 2014, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[16]  Max Dahele,et al.  Flattening filter free vs flattened beams for breast irradiation. , 2013, International journal of radiation oncology, biology, physics.

[17]  P. Mancosu,et al.  Chest wall radiotherapy with volumetric modulated arcs and the potential role of flattening filter free photon beams , 2012, Strahlentherapie und Onkologie.

[18]  Klaus Nordhausen,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman , 2009 .

[19]  B. Slotman,et al.  Evaluation of a knowledge-based planning solution for head and neck cancer. , 2015, International journal of radiation oncology, biology, physics.

[20]  D. Low,et al.  Experience-based quality control of clinical intensity-modulated radiotherapy planning. , 2011, International Journal of Radiation Oncology, Biology, Physics.

[21]  Ashutosh Kumar Singh,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2010 .

[22]  Yaorong Ge,et al.  Modeling the dosimetry of organ-at-risk in head and neck IMRT planning: an intertechnique and interinstitutional study. , 2013, Medical physics.

[23]  L. Cozzi,et al.  Boosting the tumor bed from deep-seated tumors in early-stage breast cancer: a planning study between electron, photon, and proton beams. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.