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.
"A promising solution to derive accurate MVF just prior to the treatment delivery is to utilize the cone beam projection images, since they provide high temporal resolution (about 0.3 s for MVCBCT). Previous methods that make use of the projection images include monitoring tumor change by projecting a volume of interest , extracting the projected implanted marker  or diaphragm edge . MVF derived by registration between the volume space and the projection space achieves improved image quality for MC reconstruction , , but the iterative scheme of forward-projection and optimization is extremely slow, making it difficult for an immediate application in the treatment room. "
[Show abstract][Hide abstract] 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.
"Most volumetric IGRT solutions produce a static volumetric image data set and can therefore only account for interfractional variability in patient set-up, target localization or anatomy. This technology is still an area of continuing development and techniques allowing cine-mode approaches  or respiratory correlated cone-beam CT (CBCT) [6Á8] are currently being investigated. These techniques can help to assess if the PTV margin suffices for adequate tumour coverage or evaluation of motion management. "
[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] ABSTRACT: In this work several algorithms for diaphragm detection in 2D views of cone-beam computed tomography (CBCT) raw data are developed. These algorithms are tested on 21 Siemens megavoltage CBCT scans of lungs and the result is compared against the diaphragm apex identified by human experts. Among these algorithms dynamic Hough transform is sufficiently quick and accurate for motion determination prior to radiation therapy. The diaphragm was successfully detected in all 21 data sets, even for views with poor image quality and confounding objects. Each CBCT scan analysis (200 frames) took about 38 seconds on a 2.66 GHz Intel quad-core 2 CPU. The average cranio-caudal position error was 1.707 ± 1.117 mm. Other directions were not assessed due to uncertainties in expert identification.
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