BACKGROUND AND PURPOSE: Deformation and correlated target motion remain challenges for margin recipes in radiotherapy (RT). This study presents a statistical deformable motion model for multiple targets and applies it to margin evaluations for locally advanced prostate cancer i.e. RT of the prostate (CTV-p), seminal vesicles (CTV-sv) and pelvic lymph nodes (CTV-ln). MATERIAL AND METHODS: The 19 patients included in this study, all had 7-10 repeat CT-scans available that were rigidly aligned with the planning CT-scan using intra-prostatic implanted markers, followed by deformable registrations. The displacement vectors from the deformable registrations were used to create patient-specific statistical motion models. The models were applied in treatment simulations to determine probabilities for adequate target coverage, e.g. by establishing distributions of the accumulated dose to 99% of the target volumes (D99) for various CTV-PTV expansions in the planning-CTs. RESULTS: The method allowed for estimation of the expected accumulated dose and its variance of different DVH parameters for each patient. Simulations of inter-fractional motion resulted in 7, 10, and 18 patients with an average D99 >95% of the prescribed dose for CTV-p expansions of 3mm, 4mm and 5mm, respectively. For CTV-sv and CTV-ln, expansions of 3mm, 5mm and 7 mm resulted in 1, 11 and 15 vs. 8, 18 and 18 patients respectively with an average D99 >95% of the prescription. CONCLUSIONS: Treatment simulations of target motion revealed large individual differences in accumulated dose mainly for CTV-sv, demanding the largest margins whereas those required for CTV-p and CTV-ln were comparable.
BACKGROUND AND PURPOSE: Deformation and correlated target motion remain challenges for margin recipes in radiotherapy (RT). This study presents a statistical deformable motion model for multiple targets and applies it to margin evaluations for locally advanced prostate cancer i.e. RT of the prostate (CTV-p), seminal vesicles (CTV-sv) and pelvic lymph nodes (CTV-ln). MATERIAL AND METHODS: The 19 patients included in this study, all had 7-10 repeat CT-scans available that were rigidly aligned with the planning CT-scan using intra-prostatic implanted markers, followed by deformable registrations. The displacement vectors from the deformable registrations were used to create patient-specific statistical motion models. The models were applied in treatment simulations to determine probabilities for adequate target coverage, e.g. by establishing distributions of the accumulated dose to 99% of the target volumes (D99) for various CTV-PTV expansions in the planning-CTs. RESULTS: The method allowed for estimation of the expected accumulated dose and its variance of different DVH parameters for each patient. Simulations of inter-fractional motion resulted in 7, 10, and 18 patients with an average D99 >95% of the prescribed dose for CTV-p expansions of 3mm, 4mm and 5mm, respectively. For CTV-sv and CTV-ln, expansions of 3mm, 5mm and 7 mm resulted in 1, 11 and 15 vs. 8, 18 and 18 patients respectively with an average D99 >95% of the prescription. CONCLUSIONS: Treatment simulations of target motion revealed large individual differences in accumulated dose mainly for CTV-sv, demanding the largest margins whereas those required for CTV-p and CTV-ln were comparable.
Authors: Luiza Bondar; Laura Velema; Jan Willem Mens; Ellen Zwijnenburg; Ben Heijmen; Mischa Hoogeman Journal: Strahlenther Onkol Date: 2014-08-27 Impact factor: 3.621
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Authors: Sabine Levegrün; Christoph Pöttgen; Konstantinos Xydis; Maja Guberina; Jehad Abu Jawad; Martin Stuschke Journal: J Appl Clin Med Phys Date: 2020-12-30 Impact factor: 2.102
Authors: Andreas Gravgaard Andersen; Yang-Kyun Park; Ulrik Vindelev Elstrøm; Jørgen Breede Baltzer Petersen; Gregory C Sharp; Brian Winey; Lei Dong; Ludvig Paul Muren Journal: Phys Imaging Radiat Oncol Date: 2020-10-27
Authors: Thomas Berger; Lars U Fokdal; Marianne S Assenholt; Nina B K Jensen; Jørgen B B Petersen; Lars Nyvang; Stine Korreman; Jacob C Lindegaard; Kari Tanderup Journal: Phys Imaging Radiat Oncol Date: 2019-06-26