Influence of monte carlo variance with fluence smoothing in VMAT treatment planning with Monaco TPS

被引:11
作者
Sarkar, B. [1 ]
Manikandan, A. [2 ]
Nandy, M. [3 ]
Munshi, A. [4 ]
Sayan, P. [4 ]
Sujatha, N. [5 ]
机构
[1] AMRI Hosp, Dept Radiat Oncol, Kolkata, India
[2] Narayana Hrudayala, Dept Radiat Oncol, Bangalore, Karnataka, India
[3] Saha Inst Nucl Phys, Div Chem Sci, Guntur, Andhra Pradesh, India
[4] Fortis Mem Res Inst, Dept Radiat Oncol, Gurgaon, Haryana, India
[5] Guntur Med Coll, Dept Radiat Oncol, Guntur, Andhra Pradesh, India
关键词
Fluence smoothening factor; monte carlo; volumetric modulated arc therapy; VOLUMETRIC MODULATED ARC; RADIATION-THERAPY; IMRT; IMPLEMENTATION;
D O I
10.4103/0019-509X.180820
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
INTRODUCTION: The study aimed to investigate the interplay between Monte Carlo Variance (MCV) and fluence smoothing factor (FSF) in volumetric modulated arc therapy treatment planning by using a sample set of complex treatment planning cases and a X-ray Voxel Monte Carlo-based treatment planning system equipped with tools to tune fluence smoothness as well as MCV. MATERIALS AND METHODS: The dosimetric (dose to tumor volume, and organ at risk) and physical characteristic (treatment time, number of segments, and so on) of a set 45 treatment plans for all combinations of 1%, 3%, 5% MCV and 1, 3, 5 FSF were evaluated for five carcinoma esophagus cases under the study. RESULT: Increase in FSF reduce the treatment time. Variation of MCV and FSF gives a highest planning target volume (PTV), heart and lung dose variation of 3.6%, 12.8% and 4.3%, respectively. The heart dose variation was highest among all organs at risk. Highest variation of spinal cord dose was 0.6 Gy. CONCLUSION: Variation of MCV and FSF influences the organ at risk (OAR) doses significantly but not PTV coverage and dose homogeneity. Variation in FSF causes difference in dosimetric and physical parameters for the treatment plans but variation of MCV does not. MCV 3% or less do not improve the plan quality significantly (physical and clinical) compared with MCV greater than 3%. The use of MCV between 3% and 5% gives similar results as 1% with lesser calculation time. Minimally detected differences in plan quality suggest that the optimum FSF can be set between 3 and 5.
引用
收藏
页码:158 / 161
页数:4
相关论文
共 50 条
  • [1] Evaluation of the Minimum Segment Width and Fluence Smoothing Tools for Intensity-modulated Techniques in Monaco Treatment Planning System
    Jimenez-Puertas, Sara
    Rodriguez, Andrea Gonzalez
    Cordero, Sergio Lozares
    Gonzalez, Tomas Gonzalez
    Chamarro, Javier Diez
    Hernandez, Monica Hernandez
    Moreno, Raquel Castro
    Casi, Marta Sanchez
    Gazulla, David Carlos Villa
    Martinez, Almudena Gandia
    Bonel, Arantxa Campos
    Valino, Maria del Mar Puertas
    Gomez, Jose Antonio Font
    JOURNAL OF MEDICAL PHYSICS, 2024, 49 (02) : 250 - 260
  • [2] Development of a Geant4 based Monte Carlo Algorithm to evaluate the MONACO VMAT treatment accuracy
    Fleckenstein, Jens
    Jahnke, Lennart
    Lohr, Frank
    Wenz, Frederik
    Hesser, Juergen
    ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK, 2013, 23 (01): : 33 - 45
  • [3] Verification of the Elekta Monaco TPS Monte Carlo in modelling radiation transmission through metals in a water equivalent phantom
    Kurt Byrnes
    Andriana Ford
    Nick Bennie
    Australasian Physical & Engineering Sciences in Medicine, 2019, 42 : 639 - 645
  • [4] Verification of the Elekta Monaco TPS Monte Carlo in modelling radiation transmission through metals in a water equivalent phantom
    Byrnes, Kurt
    Ford, Andriana
    Bennie, Nick
    AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, 2019, 42 (02) : 639 - 645
  • [5] Treatment planning aspects and Monte Carlo methods in proton therapy
    Fix, Michael K.
    Manser, Peter
    MODERN PHYSICS LETTERS A, 2015, 30 (17)
  • [6] Monte Carlo Beamlets in Inverse Treatment Planning
    Popescu, I. A.
    Bush, K. K.
    WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2006, VOL 14, PTS 1-6, 2007, 14 : 1856 - +
  • [7] Monte Carlo treatment planning for stereotactic radiosurgery
    Solberg, TD
    DeMarco, JJ
    Holly, FE
    Smathers, JB
    DeSalles, AAF
    RADIOTHERAPY AND ONCOLOGY, 1998, 49 (01) : 73 - 84
  • [8] Monte Carlo as a tool for treatment planning verification
    Sánchez-Doblado, F
    Leal, A
    Perucha, A
    Arráns, R
    Rincón, A
    Sánchez-Nieto, B
    Carrasco, E
    Roselló, J
    Errazquin, L
    Sánchez-Calzado, JA
    PHYSICA MEDICA, 2001, 17 : 84 - 86
  • [9] A Monte Carlo evaluation of dose distribution of commercial treatment planning systems in heterogeneous media
    Hasani, Mohsen
    Mohammadi, Kheirollah
    Ghorbani, Mahdi
    Gholami, Soraya
    Knaup, Courtney
    JOURNAL OF CANCER RESEARCH AND THERAPEUTICS, 2019, 15 : S127 - S134
  • [10] Influence of smoothing algorithms in Monte Carlo dose calculations of cyberknife treatment plans: A lung phantom study
    Sudahar, H.
    Kurup, P. G. Gopalakrishna
    Murali, V.
    Velmurugan, J.
    JOURNAL OF CANCER RESEARCH AND THERAPEUTICS, 2012, 8 (03) : 367 - 372