FIRST DEMONSTRATION OF COMBINED KV/MV IMAGE-GUIDED REAL-TIME DYNAMIC MULTILEAF-COLLIMATOR TARGET TRACKING

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1 doi: /j.ijrobp Int. J. Radiation Oncology Biol. Phys., Vol. 74, No. 3, pp , 2009 Copyright Ó 2009 Elsevier Inc. Printed in the USA. All rights reserved /09/$ see front matter PHYSICS CONTRIBUTION FIRST DEMONSTRATION OF COMBINED KV/MV IMAGE-GUIDED REAL-TIME DYNAMIC MULTILEAF-COLLIMATOR TARGET TRACKING BYUNGCHUL CHO, PH.D.,* PER R. POULSEN, PH.D.,* y ALEX SLOUTSKY, M.SC., z AMIT SAWANT, PH.D.,* AND PAUL J. KEALL, PH.D.* *Department of Radiation Oncology, Stanford University, Stanford, CA; y Department of Medical Physics, Department of Oncology, Aarhus University, Aarhus, Denmark; and z Varian Medical Systems, Palo Alto, CA Purpose: For intrafraction motion management, a real-time tracking system was developed by combining fiducial marker-based tracking via simultaneous kilovoltage (kv) and megavoltage (MV) imaging and a dynamic multileaf collimator (DMLC) beam-tracking system. Methods and Materials: The integrated tracking system employed a Varian Trilogy system equipped with kv/mv imaging systems and a Millennium 120-leaf MLC. A gold marker in elliptical motion (2-cm superior inferior, 1-cm left right, 10 cycles/min) was simultaneously imaged by the kv and MV imagers at 6.7 Hz and segmented in real time. With these two-dimensional projections, the tracking software triangulated the three-dimensional marker position and repositioned the MLC leaves to follow the motion. Phantom studies were performed to evaluate time delay from image acquisition to MLC adjustment, tracking error, and dosimetric impact of target motion with and without tracking. Results: The time delay of the integrated tracking system was 450 ms. The tracking error using a prediction algorithm was 0.9 ± 0.5 mm for the elliptical motion. The dose distribution with tracking showed better target coverage and less dose to surrounding region over no tracking. The failure rate of the gamma test (3%/3-mm criteria) was 22.5% without tracking but was reduced to 0.2% with tracking. Conclusion: For the first time, a complete tracking system combining kv/mv image-guided target tracking and DMLC beam tracking was demonstrated. The average geometric error was less than 1 mm, and the dosimetric error was negligible. This system is a promising method for intrafraction motion management. Ó 2009 Elsevier Inc. Real-time tumor tracking, X-ray image guidance, Dynamic multileaf collimator, Intrafraction motion management. INTRODUCTION Reprint requests to: Department of Radiation Oncology, Stanford University, 875 Blake Wilbur Drive, Stanford, CA Tel: (650) ; Fax: (650) ; bccho@stanford.edu Conflicts of interest: Per R. Poulsen has financial support from Varian Medical Systems, Alex Sloutsky is an employee of Varian Medical Systems, and Paul J. Keall has financial support from the National Institutes of Health/National Cancer Institute (Grant Nos. P01CA and R01CA93626) and Varian Medical Systems. 859 Intrafraction organ motion can adversely affect the treatment outcome of radiation therapy through either excessive irradiation of healthy tissue to cover tumor motion or increased dosimetric uncertainty, which can significantly degrade the benefit of highly conformal dose distributions attainable with intensity-modulated radiation therapy (IMRT) (1 3). Efforts to overcome these shortcomings have included various motion-management strategies, such as breath-hold techniques, respiratory gating, and tracking (4, 5). Tracking, which dynamically finds the tumor location and repositions the treatment beam to compensate for tumor motion, is a particularly attractive option, because neither patient-compliance for breath-hold techniques nor beam-interruption for gating is required. A tracking system capable of repositioning the multileaf collimator (MLC) dynamically to follow three-dimensional (3D) target motion in real time was developed in our group (hereafter called DMLC tracking); it has demonstrated that submillimeter accuracy can be achievable (6, 7).Inthatimplementation,3D target motion is detected optically using an external surrogate. This indirect target position estimation relying on external signal alone raises concerns about poor or changing internal/ external motion correlation (8, 9). Because direct measurement of tumor position is highly desirable for successful implementation of beam tracking, target localization with implanted electromagnetic transponders Acknowledgments The authors acknowledge financial support from the NIH/NCI (Grant Nos. P01CA and R01CA93626) and Varian Medical Systems. We particularly thank Herbert Cattell of Varian for engineering support with the multileaf collimator control. We also thank the anonymous reviewers whose comments and experimental suggestions greatly improved the manuscript and Devon Murphy for editing the manuscript. Received Sept 30, 2008, and in revised form Jan 28, Accepted for publication Feb 7, 2009.

2 860 I. J. Radiation Oncology d Biology d Physics Volume 74, Number 3, 2009 (10) has recently been integrated with the DMLC tracking system (11). Another alternative of direct tumor-motion tracking is to use fluoroscopic imaging systems with implanted fiducials (12 14). Because linear accelerators are increasingly equipped with both kv and MV imaging systems, recent investigations (15, 16) have also proposed the use of such kv/mv imaging systems to track tumor position and demonstrated the feasibility by offline analysis. To close the loop of real-time tracking from image-guided target tracking to beam tracking, we implemented an imagebased marker tracking by online processing of X-ray images acquired by kv and MV imaging systems and integrated it with the DMLC tracking system. Phantom studies were performed with the integrated tracking system to evaluate geometric accuracy of the 3D position determination for either a static or moving target, time delay from image acquisition to MLC adjustment, and dosimetric effects with and without tracking. METHODS AND MATERIALS X-ray image-guided real-time DMLC tracking system A real-time DMLC tracking system (6) integrated with a target tracking system using simultaneous kv and MV imaging of a fiducial marker is shown schematically in Fig. 1. A Varian Trilogy system (Varian Medical Systems, Palo Alto, CA) was employed with the integrated tracking system. A gold marker (3 mm in length and 1 mm in diameter), embedded in a styrofoam block, was placed on a 3D motion platform (17), which was programmed to produce an elliptical motion with 2 cm in the superior inferior (SI) direction and 1 cm in the left right (LR) direction at 10 cycles/min. The marker was simultaneously, but independently, imaged by an On-Board kv imaging system and a PortalVision AS-1000 MV imaging system (Varian Medical Systems, Palo Alto, CA). Both kv and MV image acquisition were performed in service mode using IAS3Monitor software (Varian Medical Systems, Palo Alto, CA), which allows auto saving of the images on the hard disk and also changes the imaging frequency. The image resolution was MV images were obtained continuously with the synchronized scan mode. In this mode, the detector readout was performed between MV beam pulses to reduce artifacts. The frame rate of MV imaging was variable depending on the MV beam energy and dose rate but limited to a maximum of 9 frames per second (fps). For the irradiation conditions used in this study, 6 MV at 300 MU/min, the frame rate of the MV imaging was 6.7 fps with 0.75 MU per frame (or 150 ms exposure time). At the same time, the kv images were acquired continuously in the fluoroscopic scan mode with the exposure conditions of 55 kv, 40 ma, and 12 ms; these conditions were optimized to yield the best contrast for the marker with the MV beam on. The degradation of kv image quality due to MV beam scatter was solved by moving the kv detector further away from the isocenter at the source-to-imager distance (SID) of 180 cm. Although the maximum frame rate of kv imaging in the fluoroscopy scan mode was 15 fps, accumulated delays of image saving above 11 fps were observed. For consistency, the kv imaging frequency was reduced to 6.7 fps to match that of the MV imaging. Immediately after an acquired kv (or MV) image was saved on the kv (or MV) workstation, an in-house marker tracking program read the image and extracted the projected marker position using a template-matching algorithm. This program extracts the marker position on the image that gives the maximum correlation with a template image. The template image of the pixels surrounding the marker was selected from an image acquired before tracking started. To speed up the segmentation process, the search area was confined to a pixel region centered at the computed marker position in the preceding image. No attempt was performed for subpixel matching. An example of a series of kv/mv image pairs acquired for tracking the marker in elliptical motion is shown in Fig. 2. After segmentation, the marker tracking program sent the computed two-dimensional (2D) marker position to the DMLC tracking computer via Ethernet. When the DMLC tracking system received a projected position, it read the current gantry angle information via communication with the linac and tagged it on the projected position. Megavoltage (MV) Beam Dynamic Multileaf Collimator (DMLC) 6 DMLC Controller MLC Positions 5 DMLC Tracking System Kilovoltage (kv) Source 3D Motion Phantom kv Imager 1 kv Workstation 2 3 kv Image Marker Storage Extraction 2D Position 3D Position 4 3D Target Position Triangulation MV Imager 1 MV Workstation 2 3 MV Image Marker Storage Extraction 2D Position Fig. 1. Flowchart of X-ray image-guided real-time dynamic multileaf collimator (DMLC) tracking.

3 Combined kv/mv image-guided real-time DMLC target tracking d B. CHO et al. 861 Fig. 3. Example of an MV image obtained during the same experiment as Fig. 2. The distance between the marker position and the center of the circular MLC aperture represents the tracking error. position and were then communicated to the MLC controller (Millennium 120-leaf MLC, Varian Medical Systems, Palo Alto, CA), which actuated the mechanical leaf motion of the MLC at 50-ms intervals. The maximum leaf speed of the MLC is known to be approximately 3.5 cm/sec (18). In addition, the MLC controller is configured to assert beam-hold interruptions when any leaf is more than 0.5 cm from the requested position. Fig. 2. Example of a series of (left) megavoltage (MV) and (right) kilovoltage (kv) image pairs acquired during the elliptical motion of the marker by vertical MV and horizontal kv imaging. On MV images with marker locations as insets, the dash-lined box with central cross was also displayed to guide the MV beam isocenter. The centers of MLC apertures were seen to be lagging behind the marker because of the time delay from image acquisition to MLC adjustment. The DMLC tracking system determined the 3D marker position by computing the position that had the minimum distance from both ray lines formed by a pair of kv/mv-projected 2D positions with their projection angles. This triangulation was performed using the latest pair of kv/mv positions every time a new kv or a new MV position became available. Therefore, the triangulation error could increase as the imaging time interval and/or the motion speed increases. Finally, the required leaf positions were computed to facilitate repositioning of the MLC aperture to match the updated 3D marker Calibration of kv/mv imager and static positioning accuracy To use the orthogonal kv/mv imager pair as a 3D target-positioning guide for beam delivery, the MV beam isocenter should be projected at the origin of the imagers (defined as the center pixel of the imagers) irrelevant to gantry rotation. Any offset of the center pixel of each imager relative to the MV beam isocenter results in beam-delivery positioning errors. These offsets can be caused by several reasons, including misalignment of imager or gantry sagging. For each imager, any offset was determined and corrected as a function of gantry angle. To begin calibration, the MV beam isocenter was determined by the pixel coordinates of the MV imager by acquiring two MV images of an asymmetric field at inverted collimator angles of 90 and 270 for four principal gantry angles (0, 90, 180, and 270 ). This was accomplished using the calibration method described by Sharpe et al. (19). Next, the gold marker was located at the MV beam isocenter, and a pair of kv/mv images was acquired at every 10 gantry rotation from 0 to 360 with an SID of 150 cm and 180 cm for the MV and kv imagers, respectively. The marker position relative to the center pixel of each imager was fitted to a sinusoidal form as a function of gantry angle and used for correcting the offset of each imager. The geometrical accuracy of determining stationary 3D marker positions was evaluated by positioning the marker at 27 static 3D positions in a lattice pattern with 10-mm separation. At each location, horizontal kv and vertical MV images were acquired, and the 3D location of the marker was calculated and compared with the known value. The static positioning accuracy with gantry rotation was also evaluated by analyzing triangulated 3D positions of the stationary marker at the MV beam isocenter during 360 arc beam delivery. Time delay and dynamic positioning (tracking) accuracy X-ray image-guided DMLC tracking was performed during AP beam delivery. The 3D motion platform was programmed to move the marker horizontally in elliptical motion with a motion

4 862 I. J. Radiation Oncology d Biology d Physics Volume 74, Number 3, 2009 Offset of kv imager (SID = 180 cm; mm/pixel) Offset of MV imager (SID = 150 cm; mm/pixel) Offset (pixels) Yp offset from center Xp offset from center Yp offset sinusoidal fit Xp offset sinusoidal fit Offset (pixels) Yp offset from center Xp offset from center Yp offset sinusoidal fit Xp offset sinusoidal fit Gantry angle (deg) (a) Gantry angle (deg) (b) Fig. 4. Offsets of kv and MV imager as a function of gantry angle with respect to the MV beam isocenter, along with sinusoidal fits. AP = anterior posterior; LR = left right; SID = source-to-imager distance. range of 2 cm in the SI direction, 1 cm in the LR direction, and a period of 10 cycles per minute. The range and speed of the elliptical motion was empirically chosen to avoid beam-hold interruption during tracking. The gold marker in the elliptical motion was tracked by simultaneous kv/mv imaging at 6.7 fps. The collimator was rotated so that MLC leaves moved parallel to the SI motion. The tracking error was quantified as the distance between the marker position and the MLC aperture center, as measured through Fig. 5. The three-dimensional positions of the stationary marker at the MV beam isocenter determined by kv/mv images during the arc delivery. The marker was aligned at the isocenter by acquiring anterior posterior MV and left lateral kv images. The mean offset in each direction from the isocenter, indicated by the center of dotted circle, was caused by the uncertainty of this alignment process. The radius of the dotted circle, 0.25 mm (1 pixel), represents the uncertainty of marker extraction.

5 Combined kv/mv image-guided real-time DMLC target tracking d B. CHO et al. 863 Fig. 6. Trajectories of the marker positions and the aperture centers on MV images with tracking error for the tracking experiment with prediction applied. X, Y = the horizontal and vertical directions on the MV images, and the Y direction coincides with the superior inferior direction. the MV images acquired during tracking (Fig. 3). The marker position determined by the marker tracking program during the tracking experiment was used for this purpose. To determine the MLC aperture center on each MV image, the edge curve of the MLC field was segmented and then fitted to a circle with center and radius as fit parameters using linear-squares estimation. The intensity threshold for the edge detection was adjusted so that the estimated radius was equal to the known 5-cm radius of the circular aperture. The time delay from image acquisition to MLC adjustment was estimated by the phase shift from the marker position trajectory to the aperture center trajectory, as fitted to sinusoidal functions in the x and y directions. To investigate individual contributions to the total time delay, timestamps at major tracking steps, such as at the beginning and end of image reading, marker segmentation, and triangulation, were logged and analyzed. To overcome the time delay, a modified linear adaptive prediction with the estimated time delay (20) was applied to additional tracking experiments for quantifying tracking error and dosimetric analysis. Dosimetric impact To evaluate dosimetric effects of tracking, film dosimetry was performed with Kodak EDR2 films in three scenarios: static target, moving target without tracking, and moving target with tracking. The film was sandwiched between 1-cm-thick acrylic slabs and placed on the top of the marker-embedded Styrofoam block that was attached to the end of the arm of the motion platform. For each case, a film was irradiated by 300 MU using 6-MV photon AP beams. The same elliptical motion was used for the target motion. During film exposure, MV images were also acquired to investigate distributions of geometric error, as described earlier. Assuming that in each case the 10-cm MLC aperture was adequate for covering its clinical target volume (CTV) with 95% dose, the V95 region was segmented and considered to be the CTV. Its area was computed, and the reduction relative to the area of MLC aperture was compared. Its geometric extent to the beam edge was also computed as an indicator of margins. Furthermore a region outside of CTV and confined within

6 864 I. J. Radiation Oncology d Biology d Physics Volume 74, Number 3, 2009 Fig. 7. Dose distributions of the 10-cm circular multileaf collimator (MLC) aperture (blue) for (a) static, (b) no tracking, and (c) tracking, along with the definitions of clinical target volume (CTV), organ at risk (OAR), and margins (d f) in each case. Assuming that in each case the 10-cm circular MLC aperture was designed to cover its CTV with 95% dose (red), V95 was defined as CTV, and OAR was defined as the outer region of CTV bound to a square of cm 2. a square of cm 2 was termed an organ at risk (OAR). Dose volume histograms of both CTV and OAR for each case were computed. In addition, two films with moving target were registered with the film of the static target, and a gamma evaluation analysis (21) was performed with 3% dose difference and 3-mm distance-toagreement criteria. RESULTS Calibration of kv/mv imager and static positioning accuracy Figure 4 shows the offsets of the kv/mv imager with gantry rotation, as well as the sinusoidal calibration curves. The geometric error of determining 27 static marker positions was mm in 3D. As shown in Fig. 5, static3d Table 1. Margins, CTV reductions, and mean OAR doses for static target, moving target without and with tracking Static No tracking Tracking Margin X (mm) Total (excluding s p ) (4.5) 4.3 (0.9) Margin Y (mm) Total (excluding s p ) (8.0) 3.3 (0.8) CTV reduction compared with area of MLC aperture (%) CTV reduction compared with CTV static (%) Mean dose (%) of OAR Abbreviations: CTV = clinical target volume; MLC = multileaf collimator; OAR = organ at risk. The margins for the static target are due to the penumbra, s p. Fig. 8. Dose volume histogram of clinical target volumes (CTVs) and organs at risk (OARs) for static, no tracking, and tracking.

7 Combined kv/mv image-guided real-time DMLC target tracking d B. CHO et al. 865 Fig. 9. Dose difference maps computed by subtracting the dose distributions of the static target from the dose distributions of the moving target (a) without tracking and (b) with tracking, as well as gamma test results with gamma index >1 shown in red for (c) without tracking and (d) with tracking. position estimation with gantry rotation showed similar results. Static positioning accuracy is important, because any errors in this process will manifest themselves as tracking errors. The 3D position estimation during gantry rotation provides a simple yet accurate way to align the marker at the MV beam isocenter. By shifting the marker to the estimated mean offset, the error of the marker alignment can be easily eliminated. Time delay and tracking accuracy The time delay estimated by the phase shift in each direction ranged from 435 to 455 ms. Further analysis with time stamping on the tracking log files showed that the total time delay was caused by the following: image acquisition (200 ms), image handling time of saving and reading (150 ms), image processing for marker segmentation and triangulation (50 ms), and MLC adjustment (50 ms) in sequence. The large contributions from image acquisition (200 ms) and image handling time (150 ms) delineate clearly what must be focused on to improve the current implementation. Figure 6 shows trajectories of the marker and the center of the MLC aperture in each direction on the MV images for the tracking experiment with prediction applied during the AP beam delivery. The tracking error was mm. Without tracking, the error was expected to be mm. Dosimetric impact Figure 7 shows dose distributions of the 10-cm circular MLC aperture for static, no tracking, and tracking. In each case, the region covered by more than 95% dose (red lines in Fig. 7) was defined as CTV, with the assumption that the MLC aperture is designed to cover each CTV with 95% dose. As summarized in Table 1, reduction of CTV with no tracking was 76.2%, compared with CTV for static, and could be significantly mitigated to 97.2% with tracking. Without tracking, additional margins of mm were required to cover the elliptical motion. These margins could be reduced to mm with tracking, thereby reducing the dose to the surrounding normal tissue. The dose volume histogram of OAR shows significant differences between no tracking vs. tracking, as shown in Fig. 8. Figure 9 shows dose difference maps obtained by subtracting dose distributions of a static target from dose distributions of a moving target with and without tracking. With these maps, the gamma tests were performed. The percentage of points exceeding the acceptance criteria of less than 3% dose difference within 3-mm distance was 0.2% with tracking and 22.5% without tracking. The dosimetric benefit with tracking over no motion management is reduced as the range of motion decreases and/or

8 866 I. J. Radiation Oncology d Biology d Physics Volume 74, Number 3, 2009 Delivered MU (%) No tracking Tracking X displacement (mm) Delivered MU (%) No tracking Tracking Y displacement (mm) Fig. 10. Distribution of target-positioning errors with and without tracking for the elliptical motion in the (a) x and (b) y directions measured using MV images acquired during the film irradiation. the speed of motion increases. Figure 10 shows the distribution of target-positioning errors with and without tracking, measured using the MV images acquired during the film irradiation. Without tracking, the errors distribute widely over the range of motion and have peaks at the end of range, which can be expected because of the probability density function of the elliptical motion. These errors could become close to Gaussian distribution with tracking. With tracking, most of the errors larger than 5 mm (5% of the total MU) occurred at the treatment onset when the MLC attempted to catch up with the target motion. DISCUSSION In this study, we demonstrated an entire tracking system, from marker-based target monitoring with kv/mv imaging to DMLC beam tracking, by incorporating online feedback of kv/mv imaging information into a clinical treatment machine. The method uses the kv/mv imaging systems already available on clinical treatment machines, thus provides an easy implementation for monitoring intrafraction tumor motion. Here, we only used open-beam apertures to avoid blocking of the marker by the MLC on MV images. Use of multiple markers and/or monoscopic estimation of the 3D position using a priori motion information is future work for intensitymodulated fixed/rotational therapy with tracking (22). The main limitation of the current prototype is the relatively large time delay. One of main contributions is the image acquisition process (200 ms). The lack of direct communication between each imaging system and the marker extraction program in the current prototype added a further time delay of 150 ms. These time delays could be reduced through engineering efforts, such as direct memory access of image data by the segmentation program and/or reading of a reduced image region of interest only. An alternative to reduce the time delay is a hybrid tracking system such as the Synchrony system (Accuracy, Sunnyvale, CA), in which a simpler and faster external surrogate signal is used for estimating target position, and occasional X-ray imaging is used to build an internal/external correlation model (13, 23). After all these efforts, any residual time delay could be mitigated with a suitable prediction algorithm (24 26). Experimental studies without the prediction algorithms (results not shown) yielded geometric errors of mm due to the total time delay of 450ms. The error was reduced to mm when using a prediction algorithm. A number of issues still need to be addressed to ensure that this technology is safe and effective for clinical use. First, new quality assurance (QA) protocols need to be developed based on the accumulated clinical experiences from other real-time tracking systems, such as the Synchrony system (13) and the real-time tumor tracking system (14) developed by Mitsubishi Electronics (Tokyo, Japan). Here, kv/mv images, containing spatial information about tumor and OARs with irradiated field during treatment, will play important roles for QA as well as for record and verify purposes. In addition, the implanted marker-based tracking has the following limitations: (1) possible migration of the fiducial marker from the implanted position, (2) possible deformation of the tumor during radiation therapy, (3) risk of pneumothorax, and (4) lack of knowledge about the relationship between

9 Combined kv/mv image-guided real-time DMLC target tracking d B. CHO et al. 867 the marker and the OARs. The first two limitations can be reduced by using three or four fiducial markers around the tumor. The others may require more general approaches, such as intensity-based tracking without markers with fluoroscopy (27) or fast MRI scan (28). The maximum speed of some tumors (29) can exceed the finite velocity constraints of current MLC systems, indicating that beam holds will be necessary when using current generation MLCs for tumor tracking. The beam delivery efficiency for the elliptical motion in this work was 95%. However, the median tumor speed (29) is well below the velocity constraints indicating that a strategy to pause the beam during such motion would be appropriate without lengthening the treatment time significantly. CONCLUSION For the first time, combined kv/mv image-guided realtime DMLC tracking has been demonstrated. The static positioning accuracy is 0.3 mm. For the large elliptical target motion used in this study, the average geometric error was less than 1 mm, and the dosimetric error was negligible. Although the current prototype showed a relatively large time delay (450 ms), the method is promising for intrafraction motion management. REFERENCES 1. Grills IS, Yan D, Martinez AA, et al. Potential for reduced toxicity and dose escalation in the treatment of inoperable non-small-cell lung cancer: A comparison of intensity-modulated radiation therapy (IMRT), 3D conformal radiation, and elective nodal irradiation. Int J Radiat Oncol Biol Phys 2003; 57: Hugo G, Tenn S, Agazaryan N. An evaluation of intrafraction motion-induced error for fractionated IMRT delivery. Med Phys 2003;30: Schwarz M, Van Der Geer J, Van Herk M, et al. Impact of geometrical uncertainties on 3D CRT and IMRT dose distributions for lung cancer treatment. Int J Radiat Oncol Biol Phys 2006;65: Jiang SB. Radiotherapy of mobile tumors. Semin Radiat Oncol 2006;16: Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys 2006;33: Keall PJ, Cattell H, Pokhrel D, et al.geometricaccuracyofarealtime target tracking system with dynamic multileaf collimator tracking system. Int J Radiat Oncol Biol Phys 2006;65: Sawant A, Venkat R, Srivastava V, et al. Management of threedimensional intrafraction motion through real-time DMLC tracking. Med Phys 2008;35: Gierga DP, Brewer J, Sharp GC, et al. The correlation between internal and external markers for abdominal tumors: Implications for respiratory gating. Int J Radiat Oncol Biol Phys 2005;61: Beddar AS, Kainz K, Briere TM, et al. Correlation between internal fiducial tumor motion and external marker motion for liver tumors imaged with 4D-CT. Int J Radiat Oncol Biol Phys 2007;67: Balter JM, Wright JN, Newell LJ, et al. Accuracy of a wireless localization system for radiotherapy. Int J Radiat Oncol Biol Phys 2005;61: Sawant A, Smith RL, Venkat RB, et al. Geometric accuracy and latency of an integrated 4D IMRT delivery system using realtime internal position monitoring and dynamic MLC tracking. Int J Radiat Oncol Biol Phys 2008;72:S27 S Berbeco RI, Jiang SB, Sharp GC, et al. Integrated radiotherapy imaging system (IRIS): Design considerations of tumour tracking with linac gantry-mounted diagnostic x-ray systems with flat-panel detectors. Phys Med Biol 2004;49: Schweikard A, Shiomi H, Adler J. Respiration tracking in radiosurgery. Med Phys 2004;31: Shirato H, Shimizu S, Kitamura K, et al. Four-dimensional treatment planning and fluoroscopic real-time tumor tracking radiotherapy for moving tumor. Int J Radiat Oncol Biol Phys 2000;48: Mao WH, Riaz N, Lee L, et al. A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kv imaging. Med Phys 2008;35: Wiersma RD, Mao WH, Xing L. Combined kv and MV imaging for real-time tracking of implanted fiducial markers. Med Phys 2008;35: Malinowski K, Lechleiter K, Hubenschmidt J, et al. Use of the 4D phantom to test real-time targeted radiation therapy device accuracy. Med Phys 2007;(34): Wijesooriya K, Bartee C, Siebers JV, et al. Determination of maximum leaf velocity and acceleration of a dynamic multileaf collimator: Implications for 4D radiotherapy. Med Phys 2005; 32: Sharpe MB, Moseley DJ, Purdie TG, et al. The stability of mechanical calibration for a kv cone beam computed tomography system integrated with linear accelerator. Med Phys 2006;33: Srivastava V, Keall P, Sawant A, et al. Accurate prediction of intra-fraction motion using a modified linear adaptive filter. Med Phys 2007;34: Low DA, Dempsey JF. Evaluation of the gamma dose distribution comparison method. Med Phys 2003;30: Poulsen PR, Cho B, Langen K, et al. Three-dimensional prostate position estimation with a single x-ray imager utilizing the spatial probability density. Phys Med Biol 2008;53: Cho BC, Suh YL, Dieterich S, et al. A monoscopic method for real-time tumour tracking using combined occasional x-ray imaging and continuous respiratory monitoring. Phys Med Biol 2008;53: Murphy MJ, Dieterich S. Comparative performance of linear and nonlinear neural networks to predict irregular breathing. Phys Med Biol 2006;51: Ren Q, Nishioka S, Shirato H, et al. Adaptive prediction of respiratory motion for motion compensation radiotherapy. Phys Med Biol 2007;52: Ruan D, Fessler JA, Balter JM. Real-time prediction of respiratory motion based on local regression methods. Phys Med Biol 2007;52: Cui Y, Dy JG, Sharp GC, et al. Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers. Phys Med Biol 2007;52: Koch N, Liu HH, Starkschall G, et al. Evaluation of internal lung motion for respiratory-gated radiotherapy using MRI: Part I correlating internal lung motion with skin fiducial motion. Int J Radiat Oncol Biol Phys 2004;60: Shirato H, Suzuki K, Sharp GC, et al. Speed and amplitude of lung tumor motion precisely detected in four-dimensional setup and in real-time tumor-tracking radiotherapy. Int J Radiat Oncol Biol Phys 2006;64: