- •The Dose Response Analysis Program (DREAP) is developed for biological modeling.
- •DREAP predicts radiation-induced cell population and organ biological responses.
- •DREAP allows the comparison of the treatment plan quality through DVH analysis.
- •DREAP provides a convenient environment for evaluating radiation-induced effects.
To develop a user-friendly program for biological modeling to analyze radiation-induced responses at the scales of the cell population and organ.
The program offers five established cell population surviving fraction (SF) models to estimate the SF and the relative biological effectiveness (RBE) from clonogenic assay data, and two established models to calculate the normal tissue complication probability (NTCP) and tumor control probability (TCP) from radiation treatment plans. Users can also verify the results with multiple types of quantitative analyses and graphical representation tools.
Users can verify the estimated SF, model parameters, RBE, and the respective uncertainties in the calculations of the SF and RBE modes. The qualities of the treatment plans can also be compared with at most three rival plans in terms of the NTCP, TCP, uncomplicated TCP (UCP), and user-dependent weight-based UCP (UUCP), in the calculation of the NTCP and TCP modes. Based on the validation study on accuracy and speed, the averaged mean relative errors (MREs) of the estimated parameters for all tested cell lines were not higher than 0.3% in each of the studied SF models, and the averaged MREs of the calculated NTCP and TCP for all tested treatment plans were not higher than 0.1%. The computation times for SF, RBE, NTCP, and TCP were less than 1.5 s.
The dose response analysis program can provide a trustworthy and convenient environment for researchers to analyze radiation-induced biological effects.
To read this article in full you will need to make a payment
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:Subscribe to Physica Medica: European Journal of Medical Physics
Already a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
- The linear-quadratic model is an appropriate methodology for determining isoeffective doses at large doses per fraction.Semin Radiat Oncol. 2008; 18: 234-239https://doi.org/10.1016/j.semradonc.2008.04.004
- Universal survival curve and single fraction equivalent dose: useful tools in understanding potency of ablative radiotherapy.Int J Radiat Oncol Biol Phys. 2008; 70: 847-852https://doi.org/10.1016/j.ijrobp.2007.10.059
- The repair-misrepair model in radiobiology: comparison to other models.Radiat Res Suppl. 2006; 8: S77https://doi.org/10.2307/3583515
- Lethal and potentially lethal lesions induced by radiation – A unified repair model.Radiat Res. 2006; 106: 252https://doi.org/10.2307/3576798
- Mathematical models of radiation action on living cells: from the target theory to the modern approaches. A historical and critical review.J Theor Biol. 2016; 394: 93-101https://doi.org/10.1016/j.jtbi.2016.01.018
- Repairable-conditionally repairable damage model based on dual poisson processes.Radiat Res. 2006; 160: 366-375https://doi.org/10.1667/0033-7587(2003) 160[0366:rrdmbo]2.0.co;2
- Combined use of monte carlo DNA damage simulations and deterministic repair models to examine putative mechanisms of cell killing.Radiat Res. 2008; 169: 447-459https://doi.org/10.1667/rr1046.1
- Modeling cell survival after photon irradiation based on double-strand break clustering in megabase pair chromatin loops.Radiat Res. 2012; 178: 385-394https://doi.org/10.1667/rr2964.1
- Complication probability as assessed from dose-volume histograms.Radiat Res Suppl. 2006; 8: S13https://doi.org/10.2307/3583506
- Fitting of normal tissue tolerance data to an analytic function.Int J Radiat Oncol Biol Phys. 1991; 21: 123-135https://doi.org/10.1016/0360-3016(91)90172-Z
- Tumor and Normal Tissue Responses To fractionated non uniform dose delivery.Int J Radiat Biol. 1992; 62: 249-262
- Implementation of a model for estimating tumor control probability for an inhomogeneously irradiated tumor.Radiother Oncol. 1993; 29: 140-147https://doi.org/10.1016/0167-8140(93)90239-5
- Radiation dose-response of human tumors.Int J Radiat Oncol Biol Phys. 1995; 32: 1227-1237https://doi.org/10.1016/0360-3016(94)00475-Z
- Bioplan: software for the biological evaluation of radiotherapy treatment plans b. s.Med Dosim. 2000; 25: 71-76
- Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose-volume outcome relationships.Phys Med Biol. 2006; 51: 5719-5735https://doi.org/10.1088/0031-9155/51/22/001
- A free program for calculating EUD-based NTCP and TCP in external beam radiotherapy.Phys Medica. 2007; 23: 115-125https://doi.org/10.1016/j.ejmp.2007.07.001
- Radiobiologically guided optimisation of the prescription dose and fractionation scheme in radiotherapy using BioSuite.Br J Radiol. 2012; 85: 1279-1286https://doi.org/10.1259/bjr/20476567
- RADBIOMOD: a simple program for utilising biological modelling in radiotherapy plan evaluation.Phys Medica. 2016; 32: 248-254https://doi.org/10.1016/j.ejmp.2015.10.091
- CERR: a computational environment for radiotherapy research.Med Phys. 2003; 30: 979-985https://doi.org/10.1118/1.1568978
- Statistical error propagation.J Phys Chem A. 2011; 105: 3917-3921https://doi.org/10.1021/jp003484u
Li XA, Alber M, Deasy JO, Jackson A, Jee K-WK, Marks LB, et al. The Use and QA of Biologically Related Models for Treatment Planning Report of AAPM Task Group 166. 2012. doi:10.1118/1.3685447.
- The linear-quadratic transformation of dose-volume histograms in fractionated radiotherapy.Radiother Oncol. 1998; 46: 285-295https://doi.org/10.1016/S0167-8140(97)00162-X
van der Kogel A, Basic Clinical Radiobiology Fourth Edition. 2012. doi:10.1201/b13224.
- Peschke. RBE and related modeling in carbon-ion therapy.Phys Med Biol. 2018; 63: 1-2
- A genetic algorithms based technique for computing the nonlinear least squares estimates of the parameters of sum of exponentials model.Expert Syst Appl. 2012; 39: 6370-6379https://doi.org/10.1016/j.eswa.2011.12.033
Published online: July 11, 2019
Accepted: June 25, 2019
Received in revised form: June 18, 2019
Received: April 30, 2019
© 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.