Jennifer Dhont1, Jef Vandemeulebroucke2, Manuela Burghelea3, Kenneth Poels4, Tom Depuydt4, Robbe Van Den Begin3, Cyril Jaudet3, Christine Collen3, Benedikt Engels3, Truus Reynders3, Marlies Boussaer3, Thierry Gevaert3, Mark De Ridder3, Dirk Verellen5. 1. Vrije Universiteit Brussel (VUB), Department of Electronics and Informatics (ETRO), Pleinlaan 2, B-1050 Brussels, Belgium; imec, Kapeldreef 75, B-3001 Leuven, Belgium; Vrije Universiteit Brussel (VUB), Faculty of Medicine and Farmacy, Brussels, Belgium; Department of Radiotherapy, Universitair Ziekenhuis Brussel, Brussels, Belgium. Electronic address: jennifer.dhont@uzbrussel.be. 2. Vrije Universiteit Brussel (VUB), Department of Electronics and Informatics (ETRO), Pleinlaan 2, B-1050 Brussels, Belgium; imec, Kapeldreef 75, B-3001 Leuven, Belgium. 3. Department of Radiotherapy, Universitair Ziekenhuis Brussel, Brussels, Belgium. 4. Department of Radiotherapy, Universitair Ziekenhuis Leuven, Leuven, Belgium. 5. Vrije Universiteit Brussel (VUB), Faculty of Medicine and Farmacy, Brussels, Belgium; Department of Radiotherapy, GZA Ziekenhuizen - Sint Augustinus, Iridium Kankernetwerk, Antwerp, Belgium.
Abstract
PURPOSE: To evaluate the short and long-term variability of breathing induced tumor motion. MATERIALS AND METHODS: 3D tumor motion of 19 lung and 18 liver lesions captured over the course of an SBRT treatment were evaluated and compared to the motion on 4D-CT. An implanted fiducial could be used for unambiguous motion information. Fast orthogonal fluoroscopy (FF) sequences, included in the treatment workflow, were used to evaluate motion during treatment. Several motion parameters were compared between different FF sequences from the same fraction to evaluate the intrafraction variability. To assess interfraction variability, amplitude and hysteresis were compared between fractions and with the 3D tumor motion registered by 4D-CT. Population based margins, necessary on top of the ITV to capture all motion variability, were calculated based on the motion captured during treatment. RESULTS: Baseline drift in the cranio-caudal (CC) or anterior-poster (AP) direction is significant (ie. >5 mm) for a large group of patients, in contrary to intrafraction amplitude and hysteresis variability. However, a correlation between intrafraction amplitude variability and mean motion amplitude was found (Pearson's correlation coefficient, r = 0.72, p < 10-4). Interfraction variability in amplitude is significant for 46% of all lesions. As such, 4D-CT accurately captures the motion during treatment for some fractions but not for all. Accounting for motion variability during treatment increases the PTV margins in all directions, most significantly in CC from 5 mm to 13.7 mm for lung and 8.0 mm for liver. CONCLUSION: Both short-term and day-to-day tumor motion variability can be significant, especially for lesions moving with amplitudes above 7 mm. Abandoning passive motion management strategies in favor of more active ones is advised.
PURPOSE: To evaluate the short and long-term variability of breathing induced tumor motion. MATERIALS AND METHODS: 3D tumor motion of 19 lung and 18 liver lesions captured over the course of an SBRT treatment were evaluated and compared to the motion on 4D-CT. An implanted fiducial could be used for unambiguous motion information. Fast orthogonal fluoroscopy (FF) sequences, included in the treatment workflow, were used to evaluate motion during treatment. Several motion parameters were compared between different FF sequences from the same fraction to evaluate the intrafraction variability. To assess interfraction variability, amplitude and hysteresis were compared between fractions and with the 3D tumor motion registered by 4D-CT. Population based margins, necessary on top of the ITV to capture all motion variability, were calculated based on the motion captured during treatment. RESULTS: Baseline drift in the cranio-caudal (CC) or anterior-poster (AP) direction is significant (ie. >5 mm) for a large group of patients, in contrary to intrafraction amplitude and hysteresis variability. However, a correlation between intrafraction amplitude variability and mean motion amplitude was found (Pearson's correlation coefficient, r = 0.72, p < 10-4). Interfraction variability in amplitude is significant for 46% of all lesions. As such, 4D-CT accurately captures the motion during treatment for some fractions but not for all. Accounting for motion variability during treatment increases the PTV margins in all directions, most significantly in CC from 5 mm to 13.7 mm for lung and 8.0 mm for liver. CONCLUSION: Both short-term and day-to-day tumor motion variability can be significant, especially for lesions moving with amplitudes above 7 mm. Abandoning passive motion management strategies in favor of more active ones is advised.
Authors: Hua-Chieh Shao; Jing Wang; Ti Bai; Jaehee Chun; Justin C Park; Steve Jiang; You Zhang Journal: Phys Med Biol Date: 2022-05-24 Impact factor: 4.174