Monitoring tumor motion with on-line mega-voltage cone-beam computed tomography imaging in a cine mode.
ABSTRACT Accurate daily patient localization is becoming increasingly important in external-beam radiotherapy (RT). Mega-voltage cone-beam computed tomography (MV-CBCT) utilizing a therapy beam and an on-board electronic portal imager can be used to localize tumor volumes and verify the patient's position prior to treatment. MV-CBCT produces a static volumetric image and therefore can only account for inter-fractional changes. In this work, the feasibility of using the MV-CBCT raw data as a fluoroscopic series of portal images to monitor tumor changes due to e.g. respiratory motion was investigated. A method was developed to read and convert the CB raw data into a cine. To improve the contrast-to-noise ratio on the MV-CB projection data, image post-processing with filtering techniques was investigated. Volumes of interest from the planning CT were projected onto the MV-cine. Because of the small exposure and the varying thickness of the patient depending on the projection angle, soft-tissue contrast was limited. Tumor visibility as a function of tumor size and projection angle was studied. The method was well suited in the upper chest, where motion of the tumor as well as of the diaphragm could be clearly seen. In the cases of patients with non-small cell lung cancer with medium or large tumor masses, we verified that the tumor mass was always located within the PTV despite respiratory motion. However for small tumors the method is less applicable, because the visibility of those targets becomes marginal. Evaluation of motion in non-superior-inferior directions might also be limited for small tumor masses. Viewing MV-CBCT data in a cine mode adds to the utility of MV-CBCT for verification of tumor motion and for deriving individualized treatment margins.
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ABSTRACT: Stereotactic body radiotherapy of lung cancer often makes use of a static cone-beam CT (CBCT) image to localize a tumor that moves during the respiratory cycle. In this work, we developed an algorithm to estimate the average and complete trajectory of an implanted fiducial marker from the raw CBCT projection data. After labeling the CBCT projection images based on the breathing phase of the fiducial marker, the average trajectory was determined by backprojecting the fiducial position from images of similar phase. To approximate the complete trajectory, a 3D fiducial position is estimated from its position in each CBCT project image as the point on the source-image ray closest to the average position at the same phase. The algorithm was tested with computer simulations as well as phantom experiments using a gold seed implanted in a programmable phantom capable of variable motion. Simulation testing was done on 120 realistic breathing patterns, half of which contained hysteresis. The average trajectory was reconstructed with an average root mean square (rms) error of less than 0.1 mm in all three directions, and a maximum error of 0.5 mm. The complete trajectory reconstruction had a mean rms error of less than 0.2 mm, with a maximum error of 4.07 mm. The phantom study was conducted using five different respiratory patterns with the amplitudes of 1.3 and 2.6 cm programmed into the motion phantom. These complete trajectories were reconstructed with an average rms error of 0.4 mm. There is motion information present in the raw CBCT dataset that can be exploited with the use of an implanted fiducial marker to sub-millimeter accuracy. This algorithm could ultimately supply the internal motion of a lung tumor at the treatment unit from the same dataset currently used for patient setup.Physics in Medicine and Biology 12/2010; 55(24):7439-52. · 2.70 Impact Factor
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ABSTRACT: This paper presents a novel method for respiratory motion compensated reconstruction for cone beam computed tomography (CBCT). The reconstruction is based on a time sequence of motion vector fields, which is generated by a dynamic geometrical object shape model. The dynamic model is extracted from the 2D projection images of the CBCT. The process of the motion extraction is converted into an optimal 3D multiple interrelated surface detection problem, which can be solved by computing a maximum flow in a 4D directed graph. The method was tested on 12 mega-voltage (MV) CBCT scans from three patients. Two sets of motion-artifact-free 3D volumes, full exhale (FE) and full inhale (FI) phases, were reconstructed for each daily scan. The reconstruction was compared with three other motion-compensated approaches based on quantification accuracy of motion and size. Contrast to noise ratio (CNR) was also quantified for image quality. The proposed approach has the best overall performance, with a relative tumor volume quantification error of 3.39±3.64% and 8.57±8.31% for FE and FI phases, respectively. The CNR near the tumor area is 3.85±0.42 (FE) and 3.58±3.33 (FI). These results show the clinical feasibility to use the proposed method to reconstruct motion-artifact-free MVCBCT volumes.IEEE transactions on medical imaging. 12/2012;
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ABSTRACT: Image-guided radiation therapy (IGRT) aims at frequent imaging in the treatment room during a course of radiotherapy, with decisions made on the basis of this information. The concept is not new, but recent developments and clinical implementations of IGRT drastically improved the quality of radiotherapy and broadened its possibilities as well as its indications. In general IGRT solutions can be classified in planar imaging, volumetric imaging using ionising radiation (kV- and MV- based CT) or non-radiographic techniques. This review will focus on volumetric imaging techniques applying ionising radiation with some comments on Quality Assurance (QA) specific for clinical implementation. By far the most important advantage of volumetric IGRT solutions is the ability to visualize soft tissue prior to treatment and defining the spatial relationship between target and organs at risk. A major challenge is imaging during treatment delivery. As some of these IGRT systems consist of peripheral equipment and others present fully integrated solutions, the QA requirements will differ considerably. It should be noted for instance that some systems correct for mechanical instabilities in the image reconstruction process whereas others aim at optimal mechanical stability, and the coincidence of imaging and treatment isocentre needs special attention. Some of the solutions that will be covered in detail are: (a) A dedicated CT-scanner inside the treatment room. (b) Peripheral systems mounted to the gantry of the treatment machine to acquire cone beam volumetric CT data (CBCT). Both kV-based solutions and MV-based solutions using EPIDs will be covered. (c) Integrated systems designed for both IGRT and treatment delivery. This overview will explain some of the technical features and clinical implementations of these technologies as well as providing an insight in the limitations and QA procedures required for each specific solution.Acta oncologica (Stockholm, Sweden) 08/2008; 47(7):1271-8. · 2.27 Impact Factor