SU-E-T-85: Comparison of Treatment Plans Calculated Using Ray Tracing and Monte Carlo Algorithms for Lung Cancer Patients Having Undergone Radiotherapy with Cyberknife

2014 ◽  
Vol 41 (6Part12) ◽  
pp. 241-241
Author(s):  
A Pennington ◽  
R Selvaraj ◽  
T Leventouri ◽  
S Kirkpatrick ◽  
S Oliveira
Keyword(s):  
Lung Cancer ◽  
Monte Carlo ◽  
Cancer Patients ◽  
Ray Tracing ◽  
Lung Cancer Patients ◽  
Monte Carlo Algorithms ◽  
Treatment Plans

scholarly journals Evaluation on lung cancer patients’ adaptive planning of TomoTherapy utilising radiobiological measures and Planned Adaptive module

2009 ◽  
Vol 8 (4) ◽  
pp. 185-194 ◽  
Author(s):  
Fan-Chi Su ◽  
Chengyu Shi ◽  
Panayiotis Mavroidis ◽  
Prema Rassiah-Szegedi ◽  
Niko Papanikolaou
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Clinical Effect ◽  
Planning System ◽  
Adaptive Planning ◽  
Tumour Control ◽  
Lung Cancer Patients ◽  
Megavoltage Computed Tomography ◽  
Treatment Plans ◽  
Dynamic Treatment

AbstractAdaptive radiation therapy is a promising concept that allows individualised, dynamic treatment planning based on feedback of measurements. The TomoTherapy Planned Adaptive application, integrated to the helical TomoTherapy planning system, enables calculation of actual dose delivered to the patient for each treatment fraction according to the pretreatment megavoltage computed tomography (MVCT) scan and image registration. As a result, new fractionation treatment plans are available if correction is necessary. In order to evaluate the real clinical effect, biological dose is preferred to physical dose. A biological parameter, biologically effective uniform dose ($\overline{\overline D}$), has the advantages of not only reporting delivered dose but also facilitating the analysis of dose–response relations, which link radiation dose to the clinical effect. Therefore, in this study, four lung patients’ adaptive plans were evaluated using the $\overline{\overline D}$ in addition to physical doses estimated from the TomoTherapy Planned Adaptive module. Higher complication-free tumour control probability (P+) (of about 8%) was observed in patients treated with larger dose-per-fraction by using the $\overline{\overline D}$ in addition to the physical dose. Moreover, a significant increase of 13.2% in the P+ for the adaptive TomoTherapy plan in one of the lung cancer patients was also observed, which indicates the clinical benefit of adaptive TomoTherapy.

SU-E-T-517: Ray Tracing and Mote Carlo Based Dose Computation for Chest Wall and Ribs for Lung Cancer Patients Treated with Cyberknife

2013 ◽  
Vol 40 (6Part18) ◽  
pp. 324-324
Author(s):  
T Podder ◽  
T Biswas ◽  
M Yao ◽  
S Lo ◽  
M Machtay
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Ray Tracing ◽  
Chest Wall ◽  
Lung Cancer Patients

scholarly journals Comparison of treatment plans calculated by Ray Tracing and Monte Carlo algorithms for head and thorax radiotherapy with Cyberknife

2017 ◽  
Vol 3 (2) ◽  
pp. 647-650 ◽  
Author(s):  
Kirsten Galonske ◽  
Martin Thiele ◽  
Iris Ernst ◽  
Ralph Lehrke ◽  
Waldemar Zylka
Keyword(s):  
Monte Carlo ◽  
Ray Tracing ◽  
Stereotactic Radiotherapy ◽  
Calculation Algorithm ◽  
Monte Carlo Algorithms ◽  
Body Regions ◽  
Calculation Algorithms ◽  
Treatment Plans ◽  
Homogeneous Regions ◽  
Tumor Types

AbstractThis study investigates differences between treatment plans generated by Ray Tracing (RT) and Monte Carlo (MC) calculation algorithms in homogeneous and heterogeneous body regions. Particularly, we focus on the head and on the thorax, respectively, for robotic stereotactic radiotherapy and radiosurgery with Cyberknife. Radiation plans for tumors located in the head and in the thorax region have been calculated and compared to each other in 47 cases and several tumor types.Assuming MC as the algorithm of highest accuracy it is shown that based on selected dose parameters, RT slightly underestimates the dose in homogeneous regions and overestimates in heterogeneous regions. In addition, deviations occur due to tumor size rendering large differences for small tumors. We conclude that dose prescriptions for radiotherapy treatments should differentiate between RT and MC calculation algorithm. This is especially important for small tumors in heterogeneous body regions.

Local Correlation Between Monte-Carlo Dose and Radiation-Induced Fibrosis in Lung Cancer Patients

2008 ◽  
Vol 70 (3) ◽  
pp. 921-930 ◽  
Author(s):  
Gabriela Stroian ◽  
Chandra Martens ◽  
Luis Souhami ◽  
D. Louis Collins ◽  
Jan Seuntjens
Keyword(s):  
Lung Cancer ◽  
Monte Carlo ◽  
Cancer Patients ◽  
Local Correlation ◽  
Lung Cancer Patients ◽  
Radiation Induced
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