<abstract xmlns="http://www.w3.org/1999/xhtml"><bold>Background.</bold> The aim of this study was to use various theoretical methods derived from the Linear Quadratic (LQ) model to calculate the effects of number of subfractions, time intervals between subfractions, dose per subfraction, and overall fraction time on the cells’ survival. Comparison of the results with experimental outcomes of melanoma and breast adenocarcinoma cells was also performed. Finally, the best matched method with experimental outcomes is introduced as the most accurate method in predicting the cell response.<bold>Materials and methods.</bold> The most widely used theoretical methods in the literature, presented by Keall <italic>et al</italic>., Brenner, and Mu <italic>et al</italic>., were used to calculate the cells’ survival following radiotherapy with different treatment schemes. The overall treatment times were ranged from 15 to 240 minutes. To investigate the effects of number of subfractions and dose per subfraction, the cells’ survival after different treatment delivery scenarios were calculated through fixed overall treatment times of 30, 60 and 240 minutes. The experimental tests were done for dose of 4 Gy. The results were compared with those of the theoretical outcomes.<bold>Results.</bold> The most affective parameter on the cells’ survival was the overall treatment time. However, the number of subfractions per fractions was another effecting parameter in the theoretical models. This parameter showed no significant effect on the cells’ survival in experimental schemes. The variations in number of subfractions per each fraction showed different results on the cells’ survival, calculated by Keall <italic>et al</italic>. and Brenner methods (P&lt;0.05).<bold>Conclusions.</bold> Mu <italic>et al</italic>. method can predict the cells’ survival following fractionation radiotherapy more accurately than the other models. Using Mu <italic>et al</italic>. method, as an accurate and simple method to predict the cell response after fractionation radiotherapy, is suggested for clinical applications.</abstract>

Background. The aim of this study was to use various theoretical methods derived from the Linear Quadratic (LQ) model to calculate the effects of number of subfractions, time intervals between subfractions, dose per subfraction, and overall fraction time on the cells’ survival. Comparison of the results with experimental outcomes of melanoma and breast adenocarcinoma cells was also performed. Finally, the best matched method with experimental outcomes is introduced as the most accurate method in predicting the cell response.Materials and methods. The most widely used theoretical methods in the literature, presented by Keall et al., Brenner, and Mu et al., were used to calculate the cells’ survival following radiotherapy with different treatment schemes. The overall treatment times were ranged from 15 to 240 minutes. To investigate the effects of number of subfractions and dose per subfraction, the cells’ survival after different treatment delivery scenarios were calculated through fixed overall treatment times of 30, 60 and 240 minutes. The experimental tests were done for dose of 4 Gy. The results were compared with those of the theoretical outcomes.Results. The most affective parameter on the cells’ survival was the overall treatment time. However, the number of subfractions per fractions was another effecting parameter in the theoretical models. This parameter showed no significant effect on the cells’ survival in experimental schemes. The variations in number of subfractions per each fraction showed different results on the cells’ survival, calculated by Keall et al. and Brenner methods (P<0.05).Conclusions. Mu et al. method can predict the cells’ survival following fractionation radiotherapy more accurately than the other models. Using Mu et al. method, as an accurate and simple method to predict the cell response after fractionation radiotherapy, is suggested for clinical applications.

Estimation of cell response in fractionation radiotherapy using different methods derived from linear quadratic model

Department of Medical Physics, Faculty of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran

Department of Medical Physics, Tarbiat Modares University, Tehran, Iran

Department of Medical Physics, School of Medicine, Sabzevar University of Medical Sciences, Sabzevar, Iran

Department of Medical Physics and Medical Engineering & Medical Student’s Research Center, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Department of Medical Radiation Engineering, Faculty of Advanced Sciences & Technologies, Isfahan University, Isfahan, Iran

Radiology and Oncology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Background. The aim of this study was to use various theoretical methods derived from the Linear Quadratic (LQ) model to calculate the effects of number of...

Estimation of cell response in fractionation radiotherapy using different methods derived from linear quadratic model

Publié en ligne: 27 nov. 2015

Pages: 347 - 356

Reçu: 05 mai 2015

Accepté: 12 août 2015

DOI: https://doi.org/10.1515/raon-2015-0040

Mots clés
fractionation radiotherapy, survival, dose per fraction, number of fractions, linear quadratic model

© 2015 Safoora Nikzad et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Estimation of cell response in fractionation radiotherapy using different methods derived from linear quadratic model

Publié en ligne: 27 nov. 2015

Pages: 347 - 356

Reçu: 05 mai 2015

Accepté: 12 août 2015

DOI: https://doi.org/10.1515/raon-2015-0040

Mots clésfractionation radiotherapy, survival, dose per fraction, number of fractions, linear quadratic model

© 2015 Safoora Nikzad et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
fractionation radiotherapy, survival, dose per fraction, number of fractions, linear quadratic model