Use of MV and kV imager correlation for maintaining continuous real-time 3D internal marker tracking during beam interruptions.
ABSTRACT The integration of onboard kV imaging together with a MV electronic portal imaging device (EPID) on linear accelerators (LINAC) can provide an easy to implement real-time 3D organ position monitoring solution for treatment delivery. Currently, real-time MV-kV tracking has only been demonstrated by simultaneous imagining by both MV and kV imaging devices. However, modalities such as step-and-shoot IMRT (SS-IMRT), which inherently contain MV beam interruptions, can lead to loss of target information necessary for 3D localization. Additionally, continuous kV imaging throughout the treatment delivery can lead to high levels of imaging dose to the patient. This work demonstrates for the first time how full 3D target tracking can be maintained even in the presence of such beam interruption, or MV/kV beam interleave, by use of a relatively simple correlation model together with MV-kV tracking. A moving correlation model was constructed using both present and prior positions of the marker in the available MV or kV image to compute the position of the marker on the interrupted imager. A commercially available radiotherapy system, equipped with both MV and kV imaging devices, was used to deliver typical SS-IMRT lung treatment plans to a 4D phantom containing internally embedded metallic markers. To simulate actual lung tumor motion, previous recorded 4D lung patient motion data were used. Lung tumor motion data of five separate patients were inputted into the 4D phantom, and typical SS-IMRT lung plans were delivered to simulate actual clinical deliveries. Application of the correlation model to SS-IMRT lung treatment deliveries was found to be an effective solution for maintaining continuous 3D tracking during 'step' beam interruptions. For deliveries involving five or more gantry angles with 50 or more fields per plan, the positional errors were found to have < or =1 mm root mean squared error (RMSE) in all three spatial directions. In addition to increasing the robustness of MV-kV tracking against beam interruption, it was also found that use of correlation can be an effective way of lowering kV dose to the patient and for increasing kV image quality by reduction of MV scatter interference.
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ABSTRACT: Clinical image guided radiotherapy (IGRT) systems have kV imagers and respiratory monitors, the combination of which provides an 'internal-external' correlation for respiratory-induced tumor motion tracking. We developed a general framework of correlation-based position estimation that is applicable to various imaging configurations, particularly alternate stereoscopic (ExacTrac) or rotational monoscopic (linacs) imaging, where instant 3D target positions cannot be measured. By reformulating the least-squares estimation equation for the correlation model, the necessity to measure 3D target positions from synchronous stereoscopic images can be avoided. The performance of this sequential image-based estimation was evaluated in comparison with a synchronous image-based estimation. Both methods were tested in simulation studies using 160 abdominal/thoracic tumor trajectories and an external respiratory signal dataset. The sequential image-based estimation method (1) had mean 3D errors less than 1 mm at all the imaging intervals studied (0.2, 1, 2, 5 and 10 s), (2) showed minimal dependencies of the accuracy on the geometry and (3) was equal in accuracy to the synchronous image-based estimation method when using the same image input. In conclusion, the sequential image-based estimation method can achieve sub-mm accuracy for commonly used IGRT systems, and is equally accurate and more broadly applicable than the synchronous image-based estimation method.Physics in Medicine and Biology 06/2010; 55(12):3299-316. DOI:10.1088/0031-9155/55/12/003 · 2.92 Impact Factor
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ABSTRACT: Intra-fraction internal anatomy motion is one of the major causes of the uncertainty in prostate radiation therapy. Real-time tracking of the intra-fraction prostate motion during radiation therapy is necessary to truly benefit from the highly conformal dose distribution. With the widespread use of kV on-board imaging devices, it is desirable to estimate the 3D tumor position from a single x-ray imager during treatment delivery. In this work, we will present an improved real-time 3D Bayesian tracking algorithm with an online update scheme. By incorporating all previously acquired images during dose delivery and updating the motion probability density function in an online fashion, the algorithm is able to track large and abrupt changes that are typical of prostate motion. The flexible Bayesian formulation allows one to easily incorporate this information and obtain the 3D motion with minimal computational cost. The new tracking algorithm has been tested on actual prostate trajectories recorded with implanted electromagnetic transponders for a total of 10 patients. The new algorithm outperformed a previous one with a fixed prior built from the original setup images (Li et al. 2011). It was found that with the new algorithm, the mean 3D tracking error is about 0.15 mm and the 95th percentile error is about 0.45 mm on average for all the patients. The proposed 3D tracking algorithm is useful for real-time image guidance in prostate radiation therapy.
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ABSTRACT: Monoscopic x-ray imaging with on-board kV devices is an attractive approach for real-time image guidance in modern radiation therapy such as VMAT or IMRT, but it falls short in providing reliable information along the direction of imaging x-ray. By effectively taking consideration of projection data at prior times and/or angles through a Bayesian formalism, the authors develop an algorithm for real-time and full 3D tumor localization with a single x-ray imager during treatment delivery. First, a prior probability density function is constructed using the 2D tumor locations on the projection images acquired during patient setup. Whenever an x-ray image is acquired during the treatment delivery, the corresponding 2D tumor location on the imager is used to update the likelihood function. The unresolved third dimension is obtained by maximizing the posterior probability distribution. The algorithm can also be used in a retrospective fashion when all the projection images during the treatment delivery are used for 3D localization purposes. The algorithm does not involve complex optimization of any model parameter and therefore can be used in a "plug-and-play" fashion. The authors validated the algorithm using (1) simulated 3D linear and elliptic motion and (2) 3D tumor motion trajectories of a lung and a pancreas patient reproduced by a physical phantom. Continuous kV images were acquired over a full gantry rotation with the Varian TrueBeam on-board imaging system. Three scenarios were considered: fluoroscopic setup, cone beam CT setup, and retrospective analysis. For the simulation study, the RMS 3D localization error is 1.2 and 2.4 mm for the linear and elliptic motions, respectively. For the phantom experiments, the 3D localization error is < 1 mm on average and < 1.5 mm at 95th percentile in the lung and pancreas cases for all three scenarios. The difference in 3D localization error for different scenarios is small and is not statistically significant. The proposed algorithm eliminates the need for any population based model parameters in monoscopic image guided radiotherapy and allows accurate and real-time 3D tumor localization on current standard LINACs with a single x-ray imager.Medical Physics 07/2011; 38(7):4205-14. DOI:10.1118/1.3598435 · 3.01 Impact Factor