PURPOSE: To calculate the linear energy transfer (LET) distributions in patients undergoing proton therapy. These distributions can be used to identify areas of elevated or diminished biological effect. The location of such areas might be influenced in intensity-modulated proton therapy (IMPT) optimization. METHODS AND MATERIALS: Because Monte Carlo studies to investigate the LET distribution in patients have not been undertaken so far, the code is first validated with simulations in water. The code was used in five patients, for each of them three planning and delivery techniques were simulated: passive scattering, three-dimensional modulation IMPT (3D-IMPT), and distal edge tracking IMPT (DET-IMPT). RESULTS: The inclusion of secondary particles led to significant differences compared with analytical techniques. In addition, passive scattering and 3D-IMPT led to largely comparable LET distributions, whereas the DET-IMPT plans resulted in considerably increased LET values in normal tissues and critical structures. In the brainstem, dose-averaged LET values exceeding 5 keV/μm were observed in areas with significant dose (>70% of prescribed dose). In noncritical normal tissues, even values >8 keV/μm occurred. CONCLUSION: This work demonstrates that active scanning offers the possibility of influencing the distribution of dose-averaged LET (i.e., the biological effect) without significantly altering the distribution of physical dose. On the basis of this finding, we propose a method to alter deliberately the LET distribution of a treatment plan in such a manner that the LET is maximized within certain target areas and minimized in normal tissues, while maintaining the prescribed target dose and dose constraints for organs at risk.
PURPOSE: To calculate the linear energy transfer (LET) distributions in patients undergoing proton therapy. These distributions can be used to identify areas of elevated or diminished biological effect. The location of such areas might be influenced in intensity-modulated proton therapy (IMPT) optimization. METHODS AND MATERIALS: Because Monte Carlo studies to investigate the LET distribution in patients have not been undertaken so far, the code is first validated with simulations in water. The code was used in five patients, for each of them three planning and delivery techniques were simulated: passive scattering, three-dimensional modulation IMPT (3D-IMPT), and distal edge tracking IMPT (DET-IMPT). RESULTS: The inclusion of secondary particles led to significant differences compared with analytical techniques. In addition, passive scattering and 3D-IMPT led to largely comparable LET distributions, whereas the DET-IMPT plans resulted in considerably increased LET values in normal tissues and critical structures. In the brainstem, dose-averaged LET values exceeding 5 keV/μm were observed in areas with significant dose (>70% of prescribed dose). In noncritical normal tissues, even values >8 keV/μm occurred. CONCLUSION: This work demonstrates that active scanning offers the possibility of influencing the distribution of dose-averaged LET (i.e., the biological effect) without significantly altering the distribution of physical dose. On the basis of this finding, we propose a method to alter deliberately the LET distribution of a treatment plan in such a manner that the LET is maximized within certain target areas and minimized in normal tissues, while maintaining the prescribed target dose and dose constraints for organs at risk.
Authors: Drosoula Giantsoudi; Clemens Grassberger; David Craft; Andrzej Niemierko; Alexei Trofimov; Harald Paganetti Journal: Int J Radiat Oncol Biol Phys Date: 2013-06-19 Impact factor: 7.038
Authors: Drosoula Giantsoudi; Joao Seco; Bree R Eaton; F Joseph Simeone; Hanne Kooy; Torunn I Yock; Nancy J Tarbell; Thomas F DeLaney; Judith Adams; Harald Paganetti; Shannon M MacDonald Journal: Int J Radiat Oncol Biol Phys Date: 2017-02-01 Impact factor: 7.038
Authors: Laura A Rechner; John G Eley; Rebecca M Howell; Rui Zhang; Dragan Mirkovic; Wayne D Newhauser Journal: Phys Med Biol Date: 2015-04-28 Impact factor: 3.609