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Title: SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy

Abstract

Purpose: The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work. Methods: The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones. Results: The requirements for the use of the SMmore » in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined. Conclusion: The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. Princeton Radiation Oncology, Princeton Radiation Oncology (United States)
  2. Theoretical and Computational Methods Working Group of IMAG, Santiago de Cuba (Cuba)
  3. National Cancer Institute, Rockville, MD (United States)
  4. MD Anderson Cancer Center, Houston, TX (United States)
  5. Northwestern University, Chicago, IL (United States)
  6. Provincial Hospital of Santiago de Cuba, Santiago de Cuba (Cuba)
  7. Faculty of Electrics of the University of Oriente, Santiago de Cuba (Cuba)
Publication Date:
OSTI Identifier:
22634783
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANIMAL TISSUES; COMPLEMENT; IRRADIATION; NEOPLASMS; PROBABILISTIC ESTIMATION; PROTON BEAMS; RADIATION DOSES; RADIOTHERAPY; SIMULATION; STOCHASTIC PROCESSES; VALIDATION

Citation Formats

Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, and Ocana, K. SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4956095.
Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, & Ocana, K. SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy. United States. doi:10.1118/1.4956095.
Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, and Ocana, K. Wed . "SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy". United States. doi:10.1118/1.4956095.
@article{osti_22634783,
title = {SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy},
author = {Jang, S and Frometa, T and Pyakuryal, A and Sio, T and Piseaux, R and Acosta, S and Ocana, K},
abstractNote = {Purpose: The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work. Methods: The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones. Results: The requirements for the use of the SM in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined. Conclusion: The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.},
doi = {10.1118/1.4956095},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}