Author Disclosure: T. Zhang, None; E. Meldolesi, None; Y. Chi, None; D. Yan, None.

2794 Automated Segmentation of Cone Beam CT (CBCT) Datasets Using the Planning CT (PCT) as A-PrioriKnowledge

I. R. Crocker1, F. Tim1, E. Elder1, H. Shu1, J. Landry1, E. Schreibmann1, L. Xing2

1The Emory Clinic, Atlanta, GA, 2Stanford University School of Medicine, Stanford, CA

Purpose/Objective(s): While CBCT provides a powerful tool to study inter-fraction anatomical changes, a hurdle in fullyrealizing its potentials for dose tracking is the need to segment the involved organs efficiently and consistently. In this study,we investigate a strategy of using deformable image registration to adapt the planning structures to match the anatomy observedin the CBCT images.

Materials/Methods: CBCT image sets for five patients with spine, head and neck, esophageal and prostate malignancies wereacquired by using a kilovoltage on-board imaging system attached to a linear accelerator. The deformation occurring betweenthe PCT and daily CBCT images was obtained using a modified version of the B-Spline deformable model designed toovercome the low soft tissue contrast and artifacts/distortions observed in the CBCT images. The contour points in thePCT-delineated structures were automatically registered to the corresponding locations on the CBCT images following themapping relationship established by the deformable model. The performance of the auto-segmentation tool was evaluated byvisual inspection and by comparison with the manually outlined structures.

Results: The deformable model was capable of accommodating significant variability of structures over time. In all patients,the mean measured error was 1 mm for poorly differentiated organs in the head and neck region, and 2 mm for extra-cranialorgans. A mean maximum error of 4 mm was observed locally for binning-artifact degraded voxels.

Conclusions: Contour evolution in CBCT images can be easily defined and tracked using a deformable model, with no userinteraction required. The method provides a valuable tool for routine CBCT-based dose tracking and verification, achievingmillimeter accuracy while eliminating the labor-intensive, manual segmentation procedure. The procedure is completelyautomated and has the advantages of incorporating a-priori human knowledge in the segmentation in the form of PCT delineatedstructures.

Author Disclosure: I.R. Crocker, None; F. Tim, None; E. Elder, None; H. Shu, None; J. Landry, None; E. Schreibmann, None;L. Xing, None.

2795 Use of Daily CT-Based Deformable Registration To Track Lung Daily Tumor Volumes and Position

Q. Chen1, G. H. Olivera1,2, W. Lu1, K. J. Ruchala1, K. M. Langen3, S. L. Meeks3, P. A. Kupelian3

1Tomotherapy Inc., Madison, WI, 2University of Wisconsin-Madison, Madison, WI, 3Radiation Oncology Department, MDAnderson Cancer Center of Orlando, Orlando, FL

Purpose/Objective(s): Track daily target volume and center of mass location. Compare between target contours generatedmanually and automatically based on deformable registration of daily MVCT images.

Materials/Methods: A megavoltage CT (MVCT) is acquired prior to each treatment for patients that are treated with aTomoTherapy Hi*ART II unit. Daily MVCT images for six lung tumor patients were used for this study. A deformable imageregistration algorithm was used to register the tumor volume from each MVCT image to the first MVCT image. The tumorvolume was manually contoured on the first MVCT image. This first fraction contour is used as template to generate dailycontours via deformable registration. The deformation map generated by this process was used to transfer the contour from thefirst MVCT image to each subsequent fraction image. These automatically generated tumor volumes were compared withmanual contours of the tumor volume on each MVCT scan. In addition, the center of mass location for the target generated fromthe manual and automatic contours were compared. This information is relevant to study the adequacy of deformableregistration information to localize targets.

Results: Figure 1 shows the automatically and manually generated center of mass target location as function of fraction numberfor Patient 1. On average the center of mass difference is 2 mm with a standard deviation of 1.6 mm. This indicates thatautomatic contouring tool could be useful for automatic positioning of the tumor volume for image guidance purposes. Alsoin principle changes on target position as function of fraction could be studied. Figure 2 shows the automatically and manuallygenerated tumor volumes for Patient 2. Both sets of contours show the same tendency for the decrease in the tumor volume.However, the absolute decrease in volume is less pronounced in the automatic contours. The origin of this discrepancy is stillunder investigation. However, this information is still good enough to analyze the fractional reduction of target volumes.

S654 I. J. Radiation Oncology ● Biology ● Physics Volume 66, Number 3, Supplement, 2006

Conclusions: Deformable registration maps are a useful tool to generate automatic daily target contours using the first fractionas template. The volume decrease tendency can certainly be followed and the fractional volume that can be computed isadequate. The center of mass location can be accurately predicted. This information can be used to determine daily targetlocation very quickly including anatomical variations.

Author Disclosure: Q. Chen, None; G.H. Olivera, None; W. Lu, None; K.J. Ruchala, None; K.M. Langen, None; S.L. Meeks,Tomotherapy Inc., B. Research Grant; P.A. Kupelian, Tomotherapy Inc., B. Research Grant.

2796 A 2D-3D System for Automatic Determination of Patient Setup Based on KVP X-Rays

B. J. Choi, P. Balter, L. Dong, R. Mohan, J. Chang, G. Starkschall

The University of Texas M.D. Anderson Cancer Center, Houston, TX

Purpose/Objective(s): To validate a system for automatically setting up patients based on a stereo pair of 2D images evaluatedagainst the 3D planning dataset.

Materials/Methods: We have developed a 2D-3D registration system to aid in patient setup using images from a kV x-raysystem mounted to the radiation therapy gantry (OBI, Varian Medical System, Palo Alto, CA). AP and lateral 2D x-ray imagesare acquired of the patient in treatment position and these are compared to DRRs generated on-the-fly from the 3D planningCT. The isocenter used to generate the DRRs is moved in an iterative process until the best match with the 2D x-ray imagesis obtained. The difference between the determined isocenter and the planned isocenter is the daily patient shift.

The 2D-3D system was tested using data from four patients undergoing radiotherapy of the thorax each of which had 5–7evaluations. Cone beam CT (CBCT) and projection x-rays were acquired as part of the patient’s routine care and their data wascollected under an I.R.B. approved retrospective chart review protocol. The CBCT images were registered with the planningCT using in-house software to generate the patient shifts for treatment. The shifts were checked by an attending physician usingthe 2D projection x-rays. These same x-rays were used by the 2D-3D registration system and it’s performance was comparedwith the CBCT analysis. The pixel spacing of the planning CT and the CBCT datasets were 0.977 mm in the transverse planeand 2.5 mm along the couch axis. The projection x-ray pixel spacing was 0.3 x 0.3 mm at isocenter. Projection x-rays and CBCTwere taken at 120 kVp.

Results: The mean registration time for translations was 9 seconds; adding a rotational degree of freedom about the gantry axisdoubled this time. The CBCT analysis reported translation values, while the 2D-3D registration tool reported the rotation aboutthe gantry axis as well; however only the translation values were compared. The standard deviation of the 2D-3D registeredshifts compared with the CBCT shifts along the Anterior-Posterior, Superior-Inferior, and lateral directions were 1.6 mm, 1.7mm, and 2.3 mm respectively. The corresponding means were 0.7 mm, 0.8 mm, and 0.1 mm.

Conclusions: The mean shift values demonstrate that there are minimal (� 1 mm) systematic errors. The standard deviationsdemonstrate that 2D-3D registration is consistent with CBCT analysis at the 2 mm level. The speed and accuracy of the 2D-3Dsystem demonstrates that it could be a viable tool in the clinic. The daily use of such a tool would allow us to reduce marginsthat account for setup uncertainty, allowing both the escalation of dose to improve tumor control and the sparing of more lungfrom radiation induced injury.

Author Disclosure: B.J. Choi, Philips Medical, C. Other Research Support; P. Balter, None; L. Dong, None; R. Mohan, None;J. Chang, None; G. Starkschall, None.

2797 Validation of a 4D Monte Carlo Treatment Planning Tool Using an Image Interpolation Model

M. Ding1, L. Xing2, W. Xiong3, K. Stuhr1, F. Newman1

1University of Colorado at Denver and Health Science Center, Aurora, CO, 2Stanford University School of Medicine,Stanford, CA, 3Memorial Sloan-Kettering Cancer Center, Rockville Center, NY

Purpose/Objective(s): Four-dimensional (4D) radiotherapy, the explicit inclusion of the temporal changes in anatomy duringthe imaging, planning and delivery of radiotherapy, has been investigated recently. We developed a 4D Monte Carlo treatment

S655Proceedings of the 48th Annual ASTRO Meeting