Author Disclosure: D.J. Godfrey, Varian Medical Systems, B. Research Grant; Z. Wang, None; S. Yoo, None; J. Wu, None;M. Oldham, None; C. Willett, None; F. Yin, Varian Medical Systems, B. Research Grant.

2727 Impact of Respiration-Induced Tumor Motion Uncertainties on Adaptive Treatment Delivery Strategies:A Comparison Through Repeat 4D CT Imaging

S. Vedam1, L. Dong1, J. Zhang1, J. Chang1, G. Starkschall1, J. Cox1, R. Mohan1, P. Keall2

1University of Texas M.D. Anderson Center, Houston, TX, 2Virginia Commonwealth University, Richmond, VA

Purpose/Objective(s): The advent of 4D and cone beam CT imaging has triggered a shift towards adaptive image guidedradiotherapy by enabling tumor motion estimation both within and between a fraction, throughout the treatment course.Furthermore, developments in passive and active respiratory tumor motion management strategies (motion-accommodation,gating, motion-tracking etc.,) necessitate an understanding of various systematic and random respiration-induced tumor motionuncertainties for each delivery method. This study presents a comparative analysis of such uncertainties for the above threedelivery scenarios using repeat 4D CT images obtained from an institutional review board approved organ motion protocol.

Materials/Methods: Thirty 4D CT scans from five patients were acquired prior to and periodically during the radiotherapycourse. For all patients, each subsequent 4D CT scan was registered to the treatment planning 4D CT by aligning to both bony(vertebra closest to gross tumor volume GTV) and soft tissue (GTV) anatomy using in-house registration software. Internalmotion of GTV relative to bony anatomy was then calculated. Using such GTV motion data, two setup scenarios weresimulated: (a) Bony setup - beam position aligned to mean GTV position from the treatment planning 4D CT and (b) Soft tissuesetup - beam position aligned to mean GTV position from each subsequent 4D CT, with the assumption that this mean positionremains constant during the actual delivery. Systematic and random uncertainties for each setup scenario were calculated basedon measured difference between beam and tumor positions for each of three treatment scenarios: motion-accommodation,respiratory gating and motion-tracking.

Results: For bony set-up, systematic beam-tumor position uncertainties (�) were 6.4 mm (-3.6 - 9.1), 4.0 mm (-3.5 - 4.3) and6.4 mm (-3.6 - 9.1) in the dominant superior-inferior direction for motion-accommodation, gating and motion-tracking deliveryrespectively. With soft tissue setup, this uncertainty was eliminated for all delivery modes. For bony setup, random beam-tumorposition uncertainties () were 5.4 mm (3.6 - 7.5), 3.1 mm (2.7 - 3.5) and 4.1 mm (2.5 - 6.0) for motion-accommodation, gatingand motion-tracking delivery respectively. With soft tissue setup, corresponding values were 4.6 mm (2.9 - 6.6), 2.4 mm (1.0- 3.4) and 3.1 mm (1.4 - 4.9).

Conclusions: Estimating systematic and random uncertainties due to respiration-induced tumor motion can help identifyappropriate motion management strategies during image guided radiation delivery. Based on our preliminary results, tumortargeting accuracy can be improved through soft tissue setup as compared to bony setup. Active motion management strategiessuch as respiratory gating and tracking can reduce respiration-induced tumor motion uncertainties as compared to theconventional motion accommodation approach. Gating and tracking using internal surrogates could substantially increasetargeting accuracy.

S614 I. J. Radiation Oncology ● Biology ● Physics Volume 66, Number 3, Supplement, 2006

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