ArticleJournal of biomedical physics & engineering2016
Performance Evaluation of Algorithms in Lung IMRT: A comparison of Monte Carlo, Pencil Beam, Superposition, Fast Superposition and Convolution Algorithms.
Article in Journal of biomedical physics & engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Evaluation of radiation treatment plan quality in head and neck cancer: a comparative analysis of RapidArc technique with flattening filter and flattening filter-free photon beams.Ecancermedicalscience · 2025Article
- Dosimetric Evaluation of Different Algorithms on Heterogeneous Slab Phantom Using CMS XiO and MONACO Treatment Planning System for 4MV, 6MV and 15MV Beam Energy: An Institutional Study.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Evaluation of Radiation Treatment Planning Algorithms in IMRT and VMAT: A Comparative Dosimetric Study in Lung Equivalent Heterogeneous Medium.Journal of biomedical physics & engineering · 2023Article
- Advanced radiation techniques for locally advanced non-small cell lung cancer: intensity-modulated radiation therapy and proton therapy.Journal of thoracic disease · 2018Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInclusion of inhomogeneity corrections in intensity modulated small fields always makes conformal irradiation of lung tumor very complicated in accurate dose delivery.
objectiveIn the present study, the performance of five algorithms via Monte Carlo, Pencil Beam, Convolution, Fast Superposition and Superposition were evaluated in lung cancer Intensity Modulated Radiotherapy planning. MATERIALS AND
methodsTreatment plans for ten lung cancer patients previously planned on Monte Carlo algorithm were re-planned using same treatment planning indices (gantry angel, rank, power etc.) in other four algorithms.
resultsThe values of radiotherapy planning parameters such as Mean dose, volume of 95% isodose line, Conformity Index, Homogeneity Index for target, Maximum dose, Mean dose; %Volume receiving 20Gy or more by contralateral lung; % volume receiving 30 Gy or more; % volume receiving 25 Gy or more, Mean dose received by heart; %volume receiving 35Gy or more; %volume receiving 50Gy or more, Mean dose to Easophagous; % Volume receiving 45Gy or more, Maximum dose received by Spinal cord and Total monitor unit, Volume of 50 % isodose lines were recorded for all ten patients. Performance of different algorithms was also evaluated statistically.
conclusionMC and PB algorithms found better as for tumor coverage, dose distribution homogeneity in Planning Target Volume and minimal dose to organ at risks are concerned. Superposition algorithms found to be better than convolution and fast superposition. In the case of tumors located centrally, it is recommended to use Monte Carlo algorithms for the optimal use of radiotherapy.
Indexed as
Identifiers
27853720PMC5106545What OpenQuestion holds
Registered trials
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