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Free Breathing Motion Model: First Report of Patient Model Parameters
Proceedings of the 51st Annual ASTRO Meeting
47
Free Breathing Motion Model: First Report of Patient Model Parameters 1
D. Low , T. Zhao1, D. Yang1, W. Lu1, S. Mutic1, C. Noel1, J. Hubenschmidt2, P. Parikh1, J. Bradley1 1
Washington University, St. Louis, MO, 2Philips, Cleveland, OH
Purpose/Objective(s): To determine the free breathing lung motion model parameters for lung cancer and non-lung cancer radiation therapy patients. Materials/Methods: Our group has developed a lung and lung tumor breathing motion model that is based on tidal volume and airflow rather than the traditional amplitude or phase approaches. This model equates the position X of a piece of tissue with the tidal volume v and airflow f as X = X0 + av + bf, where a and b are vector fields. The breathing motion model reconstructs the complex hysteresis motion in time through the cyclic behavior of the tidal volume and the fact that airflow is the time derivative of tidal volume. We have applied this motion model to 4D-CT datasets of 49 patients, 27 with lung cancer, and 22 without. The CT datasets were acquired using a 16-slice CT scanner operating in cine´ mode using 25 acquisitions. Simultaneous spirometry measurements were made to record the tidal volume and airflow during acquisition. A cross-correlation registration technique was applied in small (10.6 10.6 15.0 mm3) cuboid blocks to determine the position of tissues as a function of tidal volume and airflow. In this study, the fifth percentile tidal volume was defined as exhalation (0 mL). The 25 registered positions were correlated against the tidal volume and airflow to fit the a, b, and X0 vectors, which when computed for all tissue blocks provided vector fields that described the breathing motion and hysteresis throughout the lungs. The maps of a and b were examined to characterize them and determine if there were differences between different patient populations. Results: For the 49 patients, the mean peak-to-peak breathing amplitude was 593 mL ± 294 mL and the mean airflow was 286 mL/ second ± 66 mL/second. For most patients, the 85th percentile value of jaj was between 20 mm/L and 40 mm/L, and 15 mm/L and 35 mm/L, for the right and left lungs, respectively. The 85th percentile value of jbj was between 2 mm/l/second and 6 mm/l/second for both lungs. For most patients the maximum values of jaj lay in the inferior-posterior regions of the lungs, while the maximum values of jbj lay in the inferior and lateral portions of the lungs. Only 5 patients diverged from this behavior, 3 with and 2 without lung cancer. Conclusions: This is the first report of a patient-specific, free-breathing motion model results for a large cohort of patients. The motion model provides a patient-specific prediction of the complex 3D motion of lung tumors and lung tumor tissues that can be used for treatment planning. This study showed that most patients exhibited similar motion patterns but with motion magnitudes that varied within a factor of two and that intrapatient variations are large and patient-specific models will be necessary to model free-breathing lung motion. This work supported in part by NIHR01CA96679 and R01CA166712. Author Disclosure: D. Low, Tomotherapy, B. Research Grant; Varian, B. Research Grant; Viewray, F. Consultant/Advisory Board; T. Zhao, None; D. Yang, None; W. Lu, None; S. Mutic, None; C. Noel, None; J. Hubenschmidt, Philips, A. Employment; P. Parikh, Philips, B. Research Grant; Calypso, B. Research Grant; J. Bradley, None.
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Does Respiration-induced Tumor Motion and its Relationship with Respiratory Surrogates Change during a Treatment Fraction?
K. T. Malinowski1,2, T. J. McAvoy2, R. George1, S. Dietrich3, W. D. D’Souza1,2 University of Maryland School of Medicine, Baltimore, MD, 2University of Maryland, College Park, MD, 3Stanford University Cancer Center, Stanford, CA 1
Purpose/Objective(s): To determine whether (1) tumor motion and (2) the spatial relationship between the tumor and respiratory surrogates change during the course of a treatment fraction in lung, liver, or pancreas cancers. Materials/Methods: Fiducial markers were implanted in or near tumors and three external respiratory surrogate markers were tracked. The CyberKnife Synchrony system localized the centroid of the fiducial markers in 3D using a pair of stereoscopic radiographs and simultaneously tracked the external markers. Data corresponding to 128, 10, and 48 treatment fractions of 62 lung, 5 liver, and 23 pancreas patients, respectively, were analyzed. Each fraction contained 40–112 (mean = 62) stereoscopic radiographs acquired over a mean treatment fraction duration of 64 per minute. Each was divided into four blocks representing the first, second, third, and last quarter of data acquired during a single fraction. The differences in mean fiducial centroid positions between the first and last data blocks were measured. The Wilcoxon Rank-Sum test and the Kruskal-Wallis one-way ANOVA test were used to compare fiducial centroid coordinates across quarters. To assess changes in the spatial relationship between tumor and respiratory surrogates, partial least squares (PLS) models of 3D tumor centroid positions as a function of 3D optical marker positions were created from the first quarter of data in each fraction, and the average PLS errors for the remaining 3 quarters of data were determined. Results: The mean ± SD of the difference between mean tumor positions in the first and last quarters of data (drift) for lung, liver, and pancreas cases, respectively, were 2.0 ± 1.7 mm, 2.6 ± 2.1 mm, and 2.5 ± 2.1 mm in the superior-inferior (SI) direction, 1.8 ± 1.8 mm, 2.0 ± 1.3 mm, and 1.7 ± 1.6 mm in the medial-lateral direction, and 1.4 ± 1.5 mm, 2.0 ± 2.1 mm, and 1.1 ± 0.9 mm in the anterior-posterior direction. A significant (p \ 0.05) difference between SI tumor centroid positions was observed in 32%, 13%, and 27% of consecutive data blocks from individual lung, liver, and pancreas cases, respectively. In addition, in 63%, 30%, and 64% of lung, liver, and pancreas fractions, the differences in SI motion between data blocks were statistically significant (p\0.05). The predicted tumor position errors using PLS increased monotonically for subsequent quarters; the mean PLS radial errors in the second, third, and fourth data blocks were 2.5 mm, 3.5 mm, and 4.6 mm for lung cases, 1.9 mm, 2.5 mm, and 2.9 mm for liver cases, and 1.0 mm, 4.0 mm, and 6.7 mm for pancreas cases. Conclusions: Both respiration-induced tumor motion and the spatial relationship between the tumor centroid and external respiratory surrogates vary significantly during individual treatment fractions. Such changes must be considered during motion correction. Author Disclosure: K.T. Malinowski, None; T.J. McAvoy, None; R. George, None; S. Dietrich, None; W.D. D’Souza, None.
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47
Free Breathing Motion Model: First Report of Patient Model Parameters 1
D. Low , T. Zhao1, D. Yang1, W. Lu1, S. Mutic1, C. Noel1, J. Hubenschmidt2, P. Parikh1, J. Bradley1 1
Washington University, St. Louis, MO, 2Philips, Cleveland, OH
Purpose/Objective(s): To determine the free breathing lung motion model parameters for lung cancer and non-lung cancer radiation therapy patients. Materials/Methods: Our group has developed a lung and lung tumor breathing motion model that is based on tidal volume and airflow rather than the traditional amplitude or phase approaches. This model equates the position X of a piece of tissue with the tidal volume v and airflow f as X = X0 + av + bf, where a and b are vector fields. The breathing motion model reconstructs the complex hysteresis motion in time through the cyclic behavior of the tidal volume and the fact that airflow is the time derivative of tidal volume. We have applied this motion model to 4D-CT datasets of 49 patients, 27 with lung cancer, and 22 without. The CT datasets were acquired using a 16-slice CT scanner operating in cine´ mode using 25 acquisitions. Simultaneous spirometry measurements were made to record the tidal volume and airflow during acquisition. A cross-correlation registration technique was applied in small (10.6 10.6 15.0 mm3) cuboid blocks to determine the position of tissues as a function of tidal volume and airflow. In this study, the fifth percentile tidal volume was defined as exhalation (0 mL). The 25 registered positions were correlated against the tidal volume and airflow to fit the a, b, and X0 vectors, which when computed for all tissue blocks provided vector fields that described the breathing motion and hysteresis throughout the lungs. The maps of a and b were examined to characterize them and determine if there were differences between different patient populations. Results: For the 49 patients, the mean peak-to-peak breathing amplitude was 593 mL ± 294 mL and the mean airflow was 286 mL/ second ± 66 mL/second. For most patients, the 85th percentile value of jaj was between 20 mm/L and 40 mm/L, and 15 mm/L and 35 mm/L, for the right and left lungs, respectively. The 85th percentile value of jbj was between 2 mm/l/second and 6 mm/l/second for both lungs. For most patients the maximum values of jaj lay in the inferior-posterior regions of the lungs, while the maximum values of jbj lay in the inferior and lateral portions of the lungs. Only 5 patients diverged from this behavior, 3 with and 2 without lung cancer. Conclusions: This is the first report of a patient-specific, free-breathing motion model results for a large cohort of patients. The motion model provides a patient-specific prediction of the complex 3D motion of lung tumors and lung tumor tissues that can be used for treatment planning. This study showed that most patients exhibited similar motion patterns but with motion magnitudes that varied within a factor of two and that intrapatient variations are large and patient-specific models will be necessary to model free-breathing lung motion. This work supported in part by NIHR01CA96679 and R01CA166712. Author Disclosure: D. Low, Tomotherapy, B. Research Grant; Varian, B. Research Grant; Viewray, F. Consultant/Advisory Board; T. Zhao, None; D. Yang, None; W. Lu, None; S. Mutic, None; C. Noel, None; J. Hubenschmidt, Philips, A. Employment; P. Parikh, Philips, B. Research Grant; Calypso, B. Research Grant; J. Bradley, None.
48
Does Respiration-induced Tumor Motion and its Relationship with Respiratory Surrogates Change during a Treatment Fraction?
K. T. Malinowski1,2, T. J. McAvoy2, R. George1, S. Dietrich3, W. D. D’Souza1,2 University of Maryland School of Medicine, Baltimore, MD, 2University of Maryland, College Park, MD, 3Stanford University Cancer Center, Stanford, CA 1
Purpose/Objective(s): To determine whether (1) tumor motion and (2) the spatial relationship between the tumor and respiratory surrogates change during the course of a treatment fraction in lung, liver, or pancreas cancers. Materials/Methods: Fiducial markers were implanted in or near tumors and three external respiratory surrogate markers were tracked. The CyberKnife Synchrony system localized the centroid of the fiducial markers in 3D using a pair of stereoscopic radiographs and simultaneously tracked the external markers. Data corresponding to 128, 10, and 48 treatment fractions of 62 lung, 5 liver, and 23 pancreas patients, respectively, were analyzed. Each fraction contained 40–112 (mean = 62) stereoscopic radiographs acquired over a mean treatment fraction duration of 64 per minute. Each was divided into four blocks representing the first, second, third, and last quarter of data acquired during a single fraction. The differences in mean fiducial centroid positions between the first and last data blocks were measured. The Wilcoxon Rank-Sum test and the Kruskal-Wallis one-way ANOVA test were used to compare fiducial centroid coordinates across quarters. To assess changes in the spatial relationship between tumor and respiratory surrogates, partial least squares (PLS) models of 3D tumor centroid positions as a function of 3D optical marker positions were created from the first quarter of data in each fraction, and the average PLS errors for the remaining 3 quarters of data were determined. Results: The mean ± SD of the difference between mean tumor positions in the first and last quarters of data (drift) for lung, liver, and pancreas cases, respectively, were 2.0 ± 1.7 mm, 2.6 ± 2.1 mm, and 2.5 ± 2.1 mm in the superior-inferior (SI) direction, 1.8 ± 1.8 mm, 2.0 ± 1.3 mm, and 1.7 ± 1.6 mm in the medial-lateral direction, and 1.4 ± 1.5 mm, 2.0 ± 2.1 mm, and 1.1 ± 0.9 mm in the anterior-posterior direction. A significant (p \ 0.05) difference between SI tumor centroid positions was observed in 32%, 13%, and 27% of consecutive data blocks from individual lung, liver, and pancreas cases, respectively. In addition, in 63%, 30%, and 64% of lung, liver, and pancreas fractions, the differences in SI motion between data blocks were statistically significant (p\0.05). The predicted tumor position errors using PLS increased monotonically for subsequent quarters; the mean PLS radial errors in the second, third, and fourth data blocks were 2.5 mm, 3.5 mm, and 4.6 mm for lung cases, 1.9 mm, 2.5 mm, and 2.9 mm for liver cases, and 1.0 mm, 4.0 mm, and 6.7 mm for pancreas cases. Conclusions: Both respiration-induced tumor motion and the spatial relationship between the tumor centroid and external respiratory surrogates vary significantly during individual treatment fractions. Such changes must be considered during motion correction. Author Disclosure: K.T. Malinowski, None; T.J. McAvoy, None; R. George, None; S. Dietrich, None; W.D. D’Souza, None.
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