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| 024 | 7 | _ | |a 10.1002/mp.13579 |2 doi |
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| 024 | 7 | _ | |a 2473-4209 |2 ISSN |
| 037 | _ | _ | |a DKFZ-2019-01197 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Freislederer, Philipp |b 0 |
| 245 | _ | _ | |a Comparison of Planned Dose on Different CT Image Sets to Four-dimensional Monte Carlo Dose Recalculation Using the Patients Actual Breathing Trace for Lung Stereotactic Body Radiation Therapy. |
| 260 | _ | _ | |a College Park, Md. |c 2019 |b AAPM |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1635928788_5222 |2 PUB:(DE-HGF) |
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| 520 | _ | _ | |a The need for four-dimensional treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workow on multiple CT datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning.We have developed a workow, which allows us to recalculate absorbed dose to a four-dimensional computed tomography (4DCT) dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For 5 lung patients, 3D-conformal radiation therapy (3D-CRT) and volumetric arc modulated treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing three-dimensional CT (3DCT), an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration.ΔD98% and ΔD2% between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in 3 patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort.We have developed a workow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out. This article is protected by copyright. All rights reserved. |
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| 700 | 1 | _ | |a von Münchow, Asmus |b 1 |
| 700 | 1 | _ | |a Kamp, Florian |b 2 |
| 700 | 1 | _ | |a Heinz, Christian |b 3 |
| 700 | 1 | _ | |a Gerum, Sabine |b 4 |
| 700 | 1 | _ | |a Corradini, Stefanie |b 5 |
| 700 | 1 | _ | |a SÖhn, Matthias |b 6 |
| 700 | 1 | _ | |a Reiner, Michael |b 7 |
| 700 | 1 | _ | |a Roeder, Falk |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Floca, Ralf |0 P:(DE-He78)f0ab09cfecf353f363bab4cc983de95d |b 9 |
| 700 | 1 | _ | |a Alber, Markus |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Belka, Claus |b 11 |
| 700 | 1 | _ | |a Parodi, Katia |b 12 |
| 773 | _ | _ | |a 10.1002/mp.13579 |g p. mp.13579 |0 PERI:(DE-600)1466421-5 |n 7 |p 3268-3277 |t Medical physics |v 46 |y 2019 |x 2473-4209 |
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