BACKGROUND AND PURPOSE: Many dose-limiting normal tissues in radiotherapy (RT) display considerable internal motion between fractions over a course of treatment, potentially reducing the appropriateness of using planned dose distributions to predict morbidity. Accounting explicitly for rectal motion could improve the predictive power of modelling rectal morbidity. To test this, we simulated the effect of motion in two cohorts. MATERIALS AND METHODS: The included patients (232 and 159 cases) received RT for prostate cancer to 70 and 74 Gy. Motion-inclusive dose distributions were introduced as simulations of random or systematic motion to the planned dose distributions. Six rectal morbidity endpoints were analysed. A probit model using the QUANTEC recommended parameters was also applied to the cohorts. RESULTS: The differences in associations using the planned over the motion-inclusive dose distributions were modest. Statistically significant associations were obtained with four of the endpoints, mainly at high doses (55-70 Gy), using both the planned and the motion-inclusive dose distributions, primarily when simulating random motion. The strongest associations were observed for GI toxicity and rectal bleeding (Rs=0.12-0.21; Rs=0.11-0.20). Applying the probit model, significant associations were found for tenesmus and rectal bleeding (Rs=0.13, p=0.02). CONCLUSION: Equally strong associations with rectal morbidity were observed at high doses (>55 Gy), for the planned and the simulated dose distributions including in particular random rectal motion. Future studies should explore patient-specific descriptions of rectal motion to achieve improved predictive power. Published by Elsevier Ireland Ltd.
BACKGROUND AND PURPOSE: Many dose-limiting normal tissues in radiotherapy (RT) display considerable internal motion between fractions over a course of treatment, potentially reducing the appropriateness of using planned dose distributions to predict morbidity. Accounting explicitly for rectal motion could improve the predictive power of modelling rectal morbidity. To test this, we simulated the effect of motion in two cohorts. MATERIALS AND METHODS: The included patients (232 and 159 cases) received RT for prostate cancer to 70 and 74 Gy. Motion-inclusive dose distributions were introduced as simulations of random or systematic motion to the planned dose distributions. Six rectal morbidity endpoints were analysed. A probit model using the QUANTEC recommended parameters was also applied to the cohorts. RESULTS: The differences in associations using the planned over the motion-inclusive dose distributions were modest. Statistically significant associations were obtained with four of the endpoints, mainly at high doses (55-70 Gy), using both the planned and the motion-inclusive dose distributions, primarily when simulating random motion. The strongest associations were observed for GI toxicity and rectal bleeding (Rs=0.12-0.21; Rs=0.11-0.20). Applying the probit model, significant associations were found for tenesmus and rectal bleeding (Rs=0.13, p=0.02). CONCLUSION: Equally strong associations with rectal morbidity were observed at high doses (>55 Gy), for the planned and the simulated dose distributions including in particular random rectal motion. Future studies should explore patient-specific descriptions of rectal motion to achieve improved predictive power. Published by Elsevier Ireland Ltd.
Entities:
Keywords:
Morbidity; Organ motion; Prostate cancer; Radiotherapy; Rectum
Authors: Florian Buettner; Sarah L Gulliford; Steve Webb; Matthew R Sydes; David P Dearnaley; Mike Partridge Journal: Radiother Oncol Date: 2012-04-18 Impact factor: 6.280
Authors: I El Naqa; G Suneja; P E Lindsay; A J Hope; J R Alaly; M Vicic; J D Bradley; A Apte; J O Deasy Journal: Phys Med Biol Date: 2006-10-19 Impact factor: 3.609
Authors: Stephanie T H Peeters; Joos V Lebesque; Wilma D Heemsbergen; Wim L J van Putten; Annerie Slot; Michel F H Dielwart; Peter C M Koper Journal: Int J Radiat Oncol Biol Phys Date: 2006-01-18 Impact factor: 7.038
Authors: Sarah L Gulliford; Mike Partridge; Matthew R Sydes; Steve Webb; Philip M Evans; David P Dearnaley Journal: Radiother Oncol Date: 2011-11-25 Impact factor: 6.280
Authors: Mitchell Liu; Tom Pickles; Alexander Agranovich; Eric Berthelet; Graeme Duncan; Mira Keyes; Winkle Kwan; Michael McKenzie; James Morris; Howard Pai; Scott Tyldesley; Jonn Wu Journal: Int J Radiat Oncol Biol Phys Date: 2004-01-01 Impact factor: 7.038
Authors: Mirko Nitsche; Werner Brannath; Matthias Brückner; Dirk Wagner; Alexander Kaltenborn; Nils Temme; Robert M Hermann Journal: Br J Radiol Date: 2016-12-12 Impact factor: 3.039
Authors: Oscar Casares-Magaz; Ludvig Paul Muren; Vitali Moiseenko; Stine E Petersen; Niclas Johan Pettersson; Morten Høyer; Joseph O Deasy; Maria Thor Journal: Acta Oncol Date: 2017-09-08 Impact factor: 4.089
Authors: Vittoria D'Avino; Giuseppe Palma; Raffaele Liuzzi; Manuel Conson; Francesca Doria; Marco Salvatore; Roberto Pacelli; Laura Cella Journal: Radiat Oncol Date: 2015-04-08 Impact factor: 3.481
Authors: Calyn R Moulton; Michael J House; Victoria Lye; Colin I Tang; Michele Krawiec; David J Joseph; James W Denham; Martin A Ebert Journal: Radiat Oncol Date: 2016-10-31 Impact factor: 3.481
Authors: M R Ferreira; K Thomas; L Truelove; A Khan; C Parker; D P Dearnaley; S Gulliford Journal: Clin Oncol (R Coll Radiol) Date: 2019-03-20 Impact factor: 4.126
Authors: Calyn R Moulton; Michael J House; Victoria Lye; Colin I Tang; Michele Krawiec; David J Joseph; James W Denham; Martin A Ebert Journal: Radiat Oncol Date: 2015-12-14 Impact factor: 3.481