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Author Disclosure: S. Vedam, None; L. Dong, None; J. Zhang, None; J. Chang, None; G. Starkschall, None; J. Cox, None; R. Mohan, None; P. Keall, None. 2728 Evaluation of Breathing Control Methods for the Improvement of the Respiratory Motion Reproducibility Y. D. Mutaf, D. H. Brinkmann, J. A. Antolak Mayo Clinic, Rochester, MN Purpose/Objective(s): Available respiratory management systems which use surrogate motion to gate the treatment delivery rely on predictable and regular patient respiratory patterns to accurately predict the tumor position. This IRB-approved study investigates respiration management techniques for patients as a method to improve the regularity and reproducibility of respiratory motion. Materials/Methods: The respiration training methods we utilize for this study include audio instructions to help the patient establish a periodic respiratory pattern and real-time visual indicators which provide the patient feedback for the extent of the patient’s respiratory motion. Several metrics are considered for quantitative evaluation of the respiration training methods. Reproducibility metrics consist of the spread of respiration cycle amplitude and periods as well as the absolute value of the surrogate amplitude for detection of base drifting. Least motion metrics such as motion temperature, on the other hand, measure how much of respiration motion is produced by a training method during a specific gating window. Using this metric, we are able to automate the optimization of the gating window selection and provide superior evaluation of the amount of respiratory motion included during a range of gate window sizes. Results: Current practice with 4DCT studies shows significant intra-fractional variations in respiration patterns of the patients. We compare the breathing patterns obtained with the help of the respiratory coaching techniques to free-breathing. A significant improvement in the consistency of chest wall motion is generally observed with patients. Noticeable reductions in the spread of the breathing cycle period and amplitudes have also seen when respiratory coaching is implemented, shown for an example patient in Fig 1a. Comparison of other metrics such as motion temperature also reflects appreciable cooling of the patient motion within a gating window size centered at the end of exhalation, shown in Fig 1b. Conclusions: Significant improvements with patient respiration reproducibility are observed with the help of respiratory coaching techniques. We also compared the benefits of different coaching techniques and drew correlations between patient groups and these techniques. These correlations are further interpreted for the automatic determination of the optimum coaching method on an individual patient basis. Fig 1: An example of improvements observed with coaching techniques (audio instructions). Left plot shows the spread of respiration cycle amplitude and periods. Plots on the right show the motion temperature, a measure of residual motion. Author Disclosure: Y.D. Mutaf, General Electrics, B. Research Grant; D.H. Brinkmann, None; J.A. Antolak, None. 2729 Is Audio/Video Breathing Guidance Necessary for Delivering Segmental IMRT Under Dynamic Tracking? B. Yi, J. Ha, C. DeYoung, C. X. Yu University of Maryland, Baltimore, MD Purpose/Objective(s): Dynamic tracking of a target under breathing induced motion is one of the best methods to reduce the PTV margin and to eliminate the effects of the interplay between target motion and aperture motion required for intensity modulation. Currently available treatment delivery systems do not allow real-time MLC control. Dynamic MLC motion for tracking has to be preprogrammed before treatment delivery. It is widely viewed that audio/video guided breathing is essential to achieve reproducible breathing pattern and accurate delivery when tracking. This study is to prove the contrary - that it is feasible to deliver segmental IMRT under dynamic tracking with free breathing Materials/Methods: A new beam triggering logic is developed that triggers the radiation on at a preset phase and leave it on until radiation is stopped at the end of a segment. Patients’ free breathing signals were acquired in two sessions with a commercially available breathing surrogate system (RPM, Varian Medical Systems, Palo Alto, CA). The breathing signal acquired in the first session was averaged over multiple (10) breathing cycles. The averaged breathing pattern is used to convert the static IMRT segments to dynamic MLC sequence needed to track a target. The geometric tracking error was therefore taken as the amplitude difference between the averaged breathing pattern and the free breathing of the treatment day which are acquired in the second session. Free breathing tracking effect on isodose distribution is tested with a pancreas case of which target motion range is 2cm. PTV margin was reduced to 1cm. Results: Average 10.7 segments per field and average 7.9 MUs per segment were used in 10 abdomen cases treated with IMRT. Rare segments used more than 27 MUs (4 seconds or one breathing cycle, for a 400mu/min beam) for 1.8Gy or 2Gy per S615 Proceedings of the 48th Annual ASTRO Meeting
Transcript of 2729
Author Disclosure: S. Vedam, None; L. Dong, None; J. Zhang, None; J. Chang, None; G. Starkschall, None; J. Cox, None; R.Mohan, None; P. Keall, None.
2728 Evaluation of Breathing Control Methods for the Improvement of the Respiratory MotionReproducibility
Y. D. Mutaf, D. H. Brinkmann, J. A. Antolak
Mayo Clinic, Rochester, MN
Purpose/Objective(s): Available respiratory management systems which use surrogate motion to gate the treatment deliveryrely on predictable and regular patient respiratory patterns to accurately predict the tumor position. This IRB-approved studyinvestigates respiration management techniques for patients as a method to improve the regularity and reproducibility ofrespiratory motion.
Materials/Methods: The respiration training methods we utilize for this study include audio instructions to help the patientestablish a periodic respiratory pattern and real-time visual indicators which provide the patient feedback for the extent of thepatient’s respiratory motion. Several metrics are considered for quantitative evaluation of the respiration training methods.Reproducibility metrics consist of the spread of respiration cycle amplitude and periods as well as the absolute value of thesurrogate amplitude for detection of base drifting. Least motion metrics such as motion temperature, on the other hand, measurehow much of respiration motion is produced by a training method during a specific gating window. Using this metric, we areable to automate the optimization of the gating window selection and provide superior evaluation of the amount of respiratorymotion included during a range of gate window sizes.
Results: Current practice with 4DCT studies shows significant intra-fractional variations in respiration patterns of the patients.We compare the breathing patterns obtained with the help of the respiratory coaching techniques to free-breathing. A significantimprovement in the consistency of chest wall motion is generally observed with patients. Noticeable reductions in the spreadof the breathing cycle period and amplitudes have also seen when respiratory coaching is implemented, shown for an examplepatient in Fig 1a. Comparison of other metrics such as motion temperature also reflects appreciable cooling of the patient motionwithin a gating window size centered at the end of exhalation, shown in Fig 1b.
Conclusions: Significant improvements with patient respiration reproducibility are observed with the help of respiratorycoaching techniques. We also compared the benefits of different coaching techniques and drew correlations between patientgroups and these techniques. These correlations are further interpreted for the automatic determination of the optimum coachingmethod on an individual patient basis.
Fig 1: An example of improvements observed with coaching techniques (audio instructions). Left plot shows the spread ofrespiration cycle amplitude and periods. Plots on the right show the motion temperature, a measure of residual motion.
Author Disclosure: Y.D. Mutaf, General Electrics, B. Research Grant; D.H. Brinkmann, None; J.A. Antolak, None.
2729 Is Audio/Video Breathing Guidance Necessary for Delivering Segmental IMRT Under DynamicTracking?
B. Yi, J. Ha, C. DeYoung, C. X. Yu
University of Maryland, Baltimore, MD
Purpose/Objective(s): Dynamic tracking of a target under breathing induced motion is one of the best methods to reduce thePTV margin and to eliminate the effects of the interplay between target motion and aperture motion required for intensitymodulation. Currently available treatment delivery systems do not allow real-time MLC control. Dynamic MLC motion fortracking has to be preprogrammed before treatment delivery. It is widely viewed that audio/video guided breathing is essentialto achieve reproducible breathing pattern and accurate delivery when tracking. This study is to prove the contrary - that it isfeasible to deliver segmental IMRT under dynamic tracking with free breathing
Materials/Methods: A new beam triggering logic is developed that triggers the radiation on at a preset phase and leave it onuntil radiation is stopped at the end of a segment. Patients’ free breathing signals were acquired in two sessions with acommercially available breathing surrogate system (RPM, Varian Medical Systems, Palo Alto, CA). The breathing signalacquired in the first session was averaged over multiple (�10) breathing cycles. The averaged breathing pattern is used toconvert the static IMRT segments to dynamic MLC sequence needed to track a target. The geometric tracking error wastherefore taken as the amplitude difference between the averaged breathing pattern and the free breathing of the treatment daywhich are acquired in the second session. Free breathing tracking effect on isodose distribution is tested with a pancreas caseof which target motion range is �2cm. PTV margin was reduced to 1cm.
Results: Average 10.7 segments per field and average 7.9 MUs per segment were used in 10 abdomen cases treated with IMRT.Rare segments used more than 27 MUs (4 seconds or one breathing cycle, for a 400mu/min beam) for 1.8Gy or 2Gy per
S615Proceedings of the 48th Annual ASTRO Meeting
fraction. The geometrical tracking error with free breath is less than 30% of the organ motion amplitude when the treatmentbeam on time for each segment is limited to less than one breathing cycle (27mu). Considering the MU analysis result for IMRTplans, guided breath is not necessary for dynamic tracking which enables to reduce target margin up to 70%. Figure 1 showsDVH’s for perfect tracking, dynamic tracking with free breathing and non-tracking free breathing of a pancreas case. Inter-playor DVH degradation effects are little in free breath tracking, while those of non-tracking treatment are significant.
Conclusions: Guided breathing is not necessary for delivering segmental IMRT under dynamic tracking for most of the clinicalcases, in which all the segmental beams are triggered at the preset phase and the beam-on time for each segment is less thanone breathing cycle.
Author Disclosure: B. Yi, None; J. Ha, None; C. DeYoung, None; C.X. Yu, None.
2730 A “3.5D” Strategy for Motion Management
G. H. Olivera1, W. Lu1, K. Ruchala1, T. Chapman1, Q. Chen1, E. Schnarr1, B. Brammer1, K. Sheng2, P. Read2
1TomoTherapy, Madison, WI, 2University of Virginia, Charlottesville, VA
Purpose/Objective(s): To present a method for planning and treating systematically moving targets, such as lung tumors.
Materials/Methods: The proposed method for treatment of a moving target consists of two components: 1) automaticallydefining an ITV, and 2) generating a motion-weighted plan.
The automatic ITV definition entails:● Acquire a 4DCT image of the patient● Manually contour 1 phase of the 4DCT● Auto-contouring the remaining phases using deformable registration● Generate an ITV from the 4D contoursThe motion-weighted plan entails:● Acquire a motion probability distribution function (PDF) from the 4DCT or from auxiliary images (eg 4D MRI)● Optimize a treatment plan incorporating the PDF● Use deformable-registration to accumulate dose for the plan, based on different “actual” breathing traces that deviate from
the PDF to varying degrees.
Results: An interface was developed to import 4D images, perform the deformable registration of each phase relative to aselected phase, and automatically generate contours and the ITV. The generated contours were reviewed and approved by aphysician. Each deformable registration requires 3–10 minutes on a PC, depending on the size and parameters selected, but all10 phases were run in parallel using a multi-processor system. This interface is shown in Figure 1. Optimizations wereperformed using both the standard and PDF-based optimizer. A variety of breathing traces were tested, both derived from idealsynthetic breathing patterns and from measurements recorded of healthy volunteers using an external camera system. Dose wasrecalculated in each case, and the planned doses were compared to the reconstructed doses for the different breathing patterns.Preliminary results indicate that the automatically generated ITV-based treatment can be implemented efficiently and easily.The PDF-based optimizer can improve treatments when the PDF closely approximates the actual breathing trace, but if thebreathing substantially deviates from the PDF then reverting to a traditional optimization is warranted.
Conclusions: The combination of an automatically-generated ITV and a probabilistic-based optimization can be an effectivemethod to treat systematically moving targets, such as lung tumors.
S616 I. J. Radiation Oncology ● Biology ● Physics Volume 66, Number 3, Supplement, 2006
