ESTRO 2024 - Abstract Book

S4177

Physics - Intra-fraction motion management and real-time adaptive radiotherapy

ESTRO 2024

13 26 39 65 91

-0.90 ± 0.01 -1.64 ± 0.01 -2.38 ± 0.01 -2.90 ± 0.01 -3.33 ± 0.01 -3.59 ± 0.01 -3.89 ± 0.01

-0.86 ± 0.03 -1.34 ± 0.02 -1.75 ± 0.02 -2.25 ± 0.03 -2.93 ± 0.02 -3.23 ± 0.02 -3.76 ± 0.02

-0.78 ± 0.07 -1.46 ± 0.07 -2.18 ± 0.15 -2.55 ± 0.09 -3.08 ± 0.07 -3.44 ± 0.09 -3.67 ± 0.08

104 130

Longitudinal table sag (position, weight) couch position Sag-52 kg

Sag-78 kg

Sag-104 kg

100 %

100 % 86.4 % 72.91 % 62.64 % 47.16 % 32.92 % 22.26 %

100 %

1 A 2 B 3 C 4

86.93 % 73.05 % 66.07 % 52.54 % 37.39 % 30.18 %

86.19 % 72.83 % 60.76 % 44.21 % 30.46 % 17.91 %

Conclusion:

We found severe couch movement and sag artifacts for breathing curves by different surrogate systems in respiratory guided CT. In several patient cases, we saw that visual breathing coaching signals drifted out of the set threshold limits. Adaptation of the calibration workflow led to compensation of the baseline drift and thus visual coaching being more stable during breath-holds. A modern 4DCT algorithm accounts for baseline drift [4], but problems may arise with conventional 4DCT amplitude-sorted reconstruction [5]. Correction for couch movement artifacts is crucial when using respiratory curves, whether for retrospective analysis, reconstruction, or prospective 4DCT.

Keywords: table movement, table sag, respiratory guided ct

References:

[1] M. F. Spadea, G. Baroni, D. P. Gierga, J. C. Turcotte, G. T. Y. Chen, and G. C. Sharp, “Evaluation and commissioning of a surface based system for respiratory sensing in 4D CT,” J Appl Clin Med Phys, vol. 12, no. 1, pp. 162–169, 2011, doi: 10.1120/jacmp.v12i1.3288.

[2] A. Qubala et al., “Comparative evaluation of a surface ‐ based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms,” J Appl Clin Med Phys, Oct. 2023, doi: 10.1002/acm2.14174.

[3] P. Schick, H. Gottschlag, O. Fielitz, W. Budach, and I. Simiantonakis, “Performance evaluation and first clinical experience with the Varian RGSC module for breath detection of 15 lung cancer patients,” Z Med Phys, vol. 29, no. 3, pp. 229–238, Aug. 2019, doi: 10.1016/j.zemedi.2018.09.001. [4] J. Szkitsak, A. Karius, C. Hofmann, R. Fietkau, C. Bert, and S. Speer, “Quality assurance of a breathing controlled four-dimensional computed tomography algorithm,” Phys Imaging Radiat Oncol, vol. 23, pp. 85–91, Jul. 2022, doi: 10.1016/j.phro.2022.06.007.