PURPOSE: To demonstrate the feasibility of a biologically adapted dose-escalation approach to brain tumors. MATERIAL AND METHODS: Due to the specific accumulation of fluoroethyltyrosine (FET) in brain tumors, (18)F-FET-PET imaging is used to derive a voxel-by-voxel dose distribution. Although the kinetics of (18)F-FET are not completely understood, the authors regard regions with high tracer uptake as vital and aggressive tumor and use a linear dose-escalation function between SUV (standard uptake value) 3 and SUV 5. The resulting dose distribution is then planned using the inverse Monte Carlo treatment- planning system IKO. In a theoretical study, the dose range is clinically adapted from 1.8 Gy to 2.68 Gy per fraction (with a total of 30 fractions). In a second study, the maximum dose of the model is increased step by step from 2.5 Gy to 3.4 Gy to investigate whether a significant dose escalation to tracer-accumulating subvolumes is possible without affecting the shell-shaped organ at risk (OAR). For all dose-escalation levels the dose difference Delta D of each voxel inside the target volume is calculated and the mean dose difference Delta D and their standard deviation sigma Delta D are determined. The dose to the OAR is evaluated by the dose values D OAR 50% and D OAR 5%, which are the dose values not exceeded by 50% and 5% of the volume, respectively. RESULTS: The inhomogeneous dose prescription is achieved with high accuracy (Delta D < 0.03 +/- 0.3 Gy/fraction). The maximum dose can be increased remarkably, without increasing the dose to the OAR (standard deviation of D OAR 50% < 0.02 Gy/fraction and of D OAR 5% < 0.05 Gy/fraction). CONCLUSION: Assuming that regions with high tracer uptake can be interpreted as target for radiotherapy, (18)F-FET-PET-based "dose painting by numbers" applied to brain tumors is a feasible approach. The dose, and therefore potentially the chance of tumor control, can be enhanced. The proposed model can easily be transferred to other tracers and tumor entities.
PURPOSE: To demonstrate the feasibility of a biologically adapted dose-escalation approach to brain tumors. MATERIAL AND METHODS: Due to the specific accumulation of fluoroethyltyrosine (FET) in brain tumors, (18)F-FET-PET imaging is used to derive a voxel-by-voxel dose distribution. Although the kinetics of (18)F-FET are not completely understood, the authors regard regions with high tracer uptake as vital and aggressive tumor and use a linear dose-escalation function between SUV (standard uptake value) 3 and SUV 5. The resulting dose distribution is then planned using the inverse Monte Carlo treatment- planning system IKO. In a theoretical study, the dose range is clinically adapted from 1.8 Gy to 2.68 Gy per fraction (with a total of 30 fractions). In a second study, the maximum dose of the model is increased step by step from 2.5 Gy to 3.4 Gy to investigate whether a significant dose escalation to tracer-accumulating subvolumes is possible without affecting the shell-shaped organ at risk (OAR). For all dose-escalation levels the dose difference Delta D of each voxel inside the target volume is calculated and the mean dose difference Delta D and their standard deviation sigma Delta D are determined. The dose to the OAR is evaluated by the dose values D OAR 50% and D OAR 5%, which are the dose values not exceeded by 50% and 5% of the volume, respectively. RESULTS: The inhomogeneous dose prescription is achieved with high accuracy (Delta D < 0.03 +/- 0.3 Gy/fraction). The maximum dose can be increased remarkably, without increasing the dose to the OAR (standard deviation of D OAR 50% < 0.02 Gy/fraction and of D OAR 5% < 0.05 Gy/fraction). CONCLUSION: Assuming that regions with high tracer uptake can be interpreted as target for radiotherapy, (18)F-FET-PET-based "dose painting by numbers" applied to brain tumors is a feasible approach. The dose, and therefore potentially the chance of tumor control, can be enhanced. The proposed model can easily be transferred to other tracers and tumor entities.
Authors: Nathalie L Jansen; Vera Graute; Lena Armbruster; Bogdana Suchorska; Juergen Lutz; Sabina Eigenbrod; Paul Cumming; Peter Bartenstein; Jörg-Christian Tonn; Friedrich Wilhelm Kreth; Christian la Fougère Journal: Eur J Nucl Med Mol Imaging Date: 2012-04-11 Impact factor: 9.236
Authors: Mark Rickhey; Zdenek Morávek; Christoph Eilles; Oliver Koelbl; Ludwig Bogner Journal: Strahlenther Onkol Date: 2010-05-21 Impact factor: 3.621
Authors: A K Due; I R Vogelius; M C Aznar; S M Bentzen; A K Berthelsen; S S Korreman; C A Kristensen; L Specht Journal: Strahlenther Onkol Date: 2012-05-13 Impact factor: 3.621
Authors: M D Piroth; M Pinkawa; R Holy; J Klotz; S Schaar; G Stoffels; N Galldiks; H H Coenen; H J Kaiser; K J Langen; M J Eble Journal: Strahlenther Onkol Date: 2012-02-22 Impact factor: 3.621
Authors: Guido Lammering; Dirk De Ruysscher; Angela van Baardwijk; Brigitta G Baumert; Jacques Borger; Ludy Lutgens; Piet van den Ende; Michel Ollers; Philippe Lambin Journal: Strahlenther Onkol Date: 2010-08-30 Impact factor: 3.621
Authors: Markus Hutterer; Martha Nowosielski; Daniel Putzer; Nathalie L Jansen; Marcel Seiz; Michael Schocke; Mark McCoy; Georg Göbel; Christian la Fougère; Irene J Virgolini; Eugen Trinka; Andreas H Jacobs; Günther Stockhammer Journal: Neuro Oncol Date: 2013-01-17 Impact factor: 12.300
Authors: Marc D Piroth; Michael Pinkawa; Richard Holy; Gabriele Stoffels; Cengiz Demirel; Charbel Attieh; Hans J Kaiser; Karl J Langen; Michael J Eble Journal: Radiat Oncol Date: 2009-11-23 Impact factor: 3.481