Amy Yuan1, Jie Wei2, Carl P Gaebler1, Hailiang Huang1, Devin Olek1, Guang Li3. 1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. 2. Department of Computer Science, City College of New York, New York, New York. 3. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. Electronic address: lig2@mskcc.org.
Abstract
PURPOSE: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. METHODS AND MATERIALS: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. RESULTS: The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm3 (-26% to 61%), and the ΔBP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. CONCLUSIONS: A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.
PURPOSE: To develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities. METHODS AND MATERIALS: A novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used. RESULTS: The average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm3 (-26% to 61%), and the ΔBP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model. CONCLUSIONS: A novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.
Authors: H Omar Wooten; Vivian Rodriguez; Olga Green; Rojano Kashani; Lakshmi Santanam; Kari Tanderup; Sasa Mutic; H Harold Li Journal: Radiother Oncol Date: 2015-03-04 Impact factor: 6.280
Authors: Daniel A Low; Parag J Parikh; Wei Lu; James F Dempsey; Sasha H Wahab; James P Hubenschmidt; Michelle M Nystrom; Maureen Handoko; Jeffrey D Bradley Journal: Int J Radiat Oncol Biol Phys Date: 2005-11-01 Impact factor: 7.038
Authors: Erik Tryggestad; Aaron Flammang; Russell Hales; Joseph Herman; Junghoon Lee; Todd McNutt; Teboh Roland; Steven M Shea; John Wong Journal: Med Phys Date: 2013-09 Impact factor: 4.071
Authors: Qinghui Zhang; Alex Pevsner; Agung Hertanto; Yu-Chi Hu; Kenneth E Rosenzweig; C Clifton Ling; Gig S Mageras Journal: Med Phys Date: 2007-12 Impact factor: 4.071
Authors: Ahmad Esmaili Torshabi; Marco Riboldi; Abbas Ali Imani Fooladi; Seyed Mehdi Modarres Mosalla; Guido Baroni Journal: J Appl Clin Med Phys Date: 2013-01-07 Impact factor: 2.102
Authors: Guang Li; Jie Wei; Devin Olek; Mo Kadbi; Neelam Tyagi; Kristen Zakian; James Mechalakos; Joseph O Deasy; Margie Hunt Journal: Int J Radiat Oncol Biol Phys Date: 2016-11-09 Impact factor: 7.038
Authors: Guang Li; Jie Wei; Mo Kadbi; Jason Moody; August Sun; Shirong Zhang; Svetlana Markova; Kristen Zakian; Margie Hunt; Joseph O Deasy Journal: Int J Radiat Oncol Biol Phys Date: 2017-02-17 Impact factor: 7.038
Authors: Sang Kyu Lee; Sheng Huang; Lei Zhang; Ase M Ballangrud; Michalis Aristophanous; Laura I Cervino Arriba; Guang Li Journal: J Appl Clin Med Phys Date: 2021-03-31 Impact factor: 2.102