Bow-tie wobble artifact: effect of source assembly motion on cone-beam CT.
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ABSTRACT:
SUBMITTER: Zheng D
PROVIDER: S-EPMC3104720 | biostudies-other | 2011 May
REPOSITORIES: biostudies-other
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Project description:PurposeDuring spinal fusion surgery, screws are placed close to critical nerves suggesting the need for highly accurate screw placement. Verifying screw placement on high-quality tomographic imaging is essential. C-arm cone-beam CT (CBCT) provides intraoperative 3D tomographic imaging which would allow for immediate verification and, if needed, revision. However, the reconstruction quality attainable with commercial CBCT devices is insufficient, predominantly due to severe metal artifacts in the presence of pedicle screws. These artifacts arise from a mismatch between the true physics of image formation and an idealized model thereof assumed during reconstruction. Prospectively acquiring views onto anatomy that are least affected by this mismatch can, therefore, improve reconstruction quality.MethodsWe propose to adjust the C-arm CBCT source trajectory during the scan to optimize reconstruction quality with respect to a certain task, i.e., verification of screw placement. Adjustments are performed on-the-fly using a convolutional neural network that regresses a quality index over all possible next views given the current X-ray image. Adjusting the CBCT trajectory to acquire the recommended views results in non-circular source orbits that avoid poor images, and thus, data inconsistencies.ResultsWe demonstrate that convolutional neural networks trained on realistically simulated data are capable of predicting quality metrics that enable scene-specific adjustments of the CBCT source trajectory. Using both realistically simulated data as well as real CBCT acquisitions of a semianthropomorphic phantom, we show that tomographic reconstructions of the resulting scene-specific CBCT acquisitions exhibit improved image quality particularly in terms of metal artifacts.ConclusionThe proposed method is a step toward online patient-specific C-arm CBCT source trajectories that enable high-quality tomographic imaging in the operating room. Since the optimization objective is implicitly encoded in a neural network trained on large amounts of well-annotated projection images, the proposed approach overcomes the need for 3D information at run-time.
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Project description:As one of the key hardware components in Computed Tomography (CT) scanners, a bowtie filter reduces unnecessary radiation dose to the peripheries of a patient and equalizes radiation signal to the detector. Knowledge of the exact profiles from different bowtie filters are critical to model the imaging process of CT scanners and to estimate patient dose. However, bowtie filter profiles remain proprietary to most CT vendors. The data of bowtie profiles reported here were directly measured using a solid-state linear-array detector from three modern CT scanners (GE Revolution, Philips iQon, and Toshiba Aquilion ONE Vision. The detailed method, including associated geometrical calibration and data validation, was previously published. This data article is mainly to present the updated bowtie profile data measured after our previous publication.
| S-EPMC6706760 | biostudies-literature
Project description:PurposeTo provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm.MethodsThe algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. The eigenvectors are weighted by a parameterized function of the patient breathing trace recorded during 4DCBCT. The algorithm is demonstrated and tested via numerical simulation.ResultsThe algorithm is shown to produce accurate reconstruction results for the most complicated simulated motion, in which voxels move with a pseudo-periodic pattern and relative phase shifts exist between voxels. The tests show that principal component eigenvectors trained on DVFs from a novel 2D/3D registration method give substantially better results than eigenvectors trained on DVFs obtained by conventionally registering 4DCBCT phases reconstructed via filtered backprojection.ConclusionsProof of concept testing has validated the 4DCBCT reconstruction approach for the types of simulated data considered. In addition, the authors found the 2D/3D registration approach to be our best choice for generating the DVF training set, and the Nelder-Mead simplex algorithm the most robust optimization routine.
| S-EPMC3247929 | biostudies-literature
Project description:Methods of reducing respiratory motion blurring in cone-beam CT (CBCT) have been limited to lung where soft tissue contrast is large. Respiration-correlated cone-beam CT uses slow continuous gantry rotation but image quality is limited by uneven projection spacing. This study investigates the efficacy of a novel gated CBCT technique.In gated CBCT, the linac is programmed such that gantry rotation and kV image acquisition occur within a gate around end expiration and are triggered by an external respiratory monitor. Standard CBCT and gated CBCT scans are performed in 22 patients (11 thoracic, 11 abdominal) and a respiration-correlated CT (RCCT) scan, acquired on a standard CT scanner, from the same day serves as a criterion standard. Image quality is compared by calculating contrast-to-noise ratios (CNR) for tumors in lung, gastroesophageal junction (GEJ) tissue, and pancreas tissue, relative to surrounding background tissue. Congruence between the object in the CBCT images and that in the RCCT is measured by calculating the optimized normalized cross-correlation (NCC) following CBCT-to-RCCT rigid registrations.Gated CBCT results in reduced motion artifacts relative to standard CBCT, with better visualization of tumors in lung, and of abdominal organs including GEJ, pancreas, and organs at risk. CNR of lung tumors is larger in gated CBCT in 6 of 11 cases relative to standard CBCT. A paired two-tailed t-test of lung patient mean CNR shows no statistical significance (p = 0.133). In 4 of 5 cases where CNR is not increased, lung tumor motion observed in RCCT is small (range 1.3-5.2 mm). CNR is increased and becomes statistically significant for 6 out of 7 lung patients with > 5 mm tumor motion (p = 0.044). CNR is larger in gated CBCT in 5 of 7 GEJ cases and 3 of 4 pancreas cases (p = 0.082 and 0.192). Gated CBCT yields improvement with lower NCC relative to standard CBCT in 10 of 11, 7 of 7, and 3 of 4 patients for lung, GEJ, and pancreas images, respectively (p = 0.0014, 0.0030, 0.165).Gated CBCT reduces image blurring caused by respiratory motion. The gated gantry rotation yields uniformly and closely spaced projections resulting in improved reconstructed image quality. The technique is shown to be applicable to abdominal sites, where image contrast of soft tissues is low.
| S-EPMC3618091 | biostudies-other
Project description:The authors investigate the CB artifact behavior of the factorization approach recently suggested for image reconstruction in circular cone-beam computed tomography. This investigation is carried out in a typical C-arm geometry and involves simulated data and for the first time also phantom and clinical CB data acquired with a commercially available angiographic system.The CB artifact level is first measured using quantitative figures-of-merit that are computed from the reconstructions of the mathematical FORBILD head phantom and of a modified disk phantom. The authors then show reconstructions from a physical thorax phantom and clinical head data sets for a visual assessment of image quality. The performance of the factorization method is primarily compared to that of short-scan FDK, but the authors also show the results obtained with the full-scan FDK and the virtual PI-line BPF method for the simulation studies, as a benchmark.Quantitatively, the FORBILD head phantom reconstructions of both FDK methods show a spatially averaged bias of up to 1.2% in the axial slices about 9 cm away from the plane of the scan, which is placed 4 cm below the central slice through the phantom. The artifact level for the short-scan FDK method and the virtual PI-line BPF method noticeably depends on the scan orientation. The factorization approach can significantly reduce both, this dependency as well as the reconstruction bias. It also shows visually an improved quality of the clinical images compared to short-scan FDK, particularly close to the spine and in the subcranial regions of the clinical data sets.The factorization approach comes with noticeably lower reconstruction bias than the FDK methods and is least sensitive to the scan orientation among all considered short-scan methods. The data inconsistencies contained in the real data sets, such as scatter, beam hardening, or data truncation, show only little impact on the factorization results. Hence, in both, reconstructions from real and simulated data, the factorization method yields better image quality than short-scan FDK, albeit at the cost of some slight, directed high-frequency artifacts that are mostly visible in axial slices.
| S-EPMC3161746 | biostudies-other
Project description:Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network-that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.
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Project description:PurposeTo provide initial assessment of image quality and dose for a cone-beam computed tomographic (CT) scanner dedicated to extremity imaging.Materials and methodsA prototype cone-beam CT scanner has been developed for imaging the extremities, including the weight-bearing lower extremities. Initial technical assessment included evaluation of radiation dose measured as a function of kilovolt peak and tube output (in milliampere seconds), contrast resolution assessed in terms of the signal difference-to-noise ratio (SDNR), spatial resolution semiquantitatively assessed by using a line-pair module from a phantom, and qualitative evaluation of cadaver images for potential diagnostic value and image artifacts by an expert CT observer (musculoskeletal radiologist).ResultsThe dose for a nominal scan protocol (80 kVp, 108 mAs) was 9 mGy (absolute dose measured at the center of a CT dose index phantom). SDNR was maximized with the 80-kVp scan technique, and contrast resolution was sufficient for visualization of muscle, fat, ligaments and/or tendons, cartilage joint space, and bone. Spatial resolution in the axial plane exceeded 15 line pairs per centimeter. Streaks associated with x-ray scatter (in thicker regions of the patient--eg, the knee), beam hardening (about cortical bone--eg, the femoral shaft), and cone-beam artifacts (at joint space surfaces oriented along the scanning plane--eg, the interphalangeal joints) presented a slight impediment to visualization. Cadaver images (elbow, hand, knee, and foot) demonstrated excellent visibility of bone detail and good soft-tissue visibility suitable to a broad spectrum of musculoskeletal indications.ConclusionA dedicated extremity cone-beam CT scanner capable of imaging upper and lower extremities (including weight-bearing examinations) provides sufficient image quality and favorable dose characteristics to warrant further evaluation for clinical use.
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Project description:Background & purposeFour dimensional Cone beam CT (CBCT) has many potential benefits for radiotherapy but suffers from poor image quality, long acquisition times, and/or long reconstruction times. In this work we present a fast iterative reconstruction algorithm for 4D reconstruction of fast acquisition cone beam CT, as well as a new method for temporal regularization and compare to state of the art methods for 4D CBCT.Materials & methodsRegularization parameters for the iterative algorithms were found automatically via computer optimization on 60 s acquisitions using the XCAT phantom. Nineteen lung cancer patients were scanned with 60 s arcs using the onboard image on a Varian trilogy linear accelerator. Images were reconstructed using an accelerated ordered subset algorithm. A frequency based temporal regularization algorithm was developed and compared to the McKinnon-Bates algorithm, 4D total variation and prior images compressed sensing (PICCS).ResultsAll reconstructions were completed in 60 s or less. The proposed method provided a structural similarity of 0.915, compared with 0.786 for the classic McKinnon-bates method. For the patient study, it provided fewer image artefacts than PICCS, and better spatial resolution than 4D TV.ConclusionFour dimensional iterative CBCT reconstruction was done in less than 60 s, demonstrating the clinical feasibility. The frequency based method outperformed 4D total variation and PICCS on the simulated data, and for patients allowed for tumor location based on 60 s acquisitions, even for slowly breathing patients. It should thus be suitable for routine clinical use.
| S-EPMC7807579 | biostudies-literature
Project description:Understanding factors associated with tie strength in social networks is essential in a wide variety of settings. With the internet and cellular phones providing additional avenues of communication, measuring and inferring tie strength has become much more complex. We introduce the social bow tie framework, which consists of a focal tie and all actors connected to either or both of the two focal nodes on either side of the focal tie. We also define several intuitive and interpretable metrics that quantify properties of the bow tie which enable us to investigate associations between the strength of the "central" tie and properties of the bow tie. We combine the bow tie framework with machine learning to investigate what aspects of the bow tie are most predictive of tie strength in two very different types of social networks, a collection of medium-sized social networks from 75 rural villages in India and a nationwide call network of European mobile phone users. Our results show that tie strength depends not only on the properties of shared friends, but also on non-shared friends, those observable to only one person in the tie, hence introducing a fundamental asymmetry to social interaction.
| S-EPMC6008360 | biostudies-literature
Project description:BackgroundCone beam computed tomography (CBCT) for radiotherapy image guidance suffers from respiratory motion artifacts. This limits soft tissue visualization and localization accuracy, particularly in abdominal sites. We report on a prospective study of respiratory motion-corrected (RMC)-CBCT to evaluate its efficacy in localizing abdominal organs and improving soft tissue visibility at end expiration.Material and methodsIn an IRB approved study, 11 patients with gastroesophageal junction (GEJ) cancer and five with pancreatic cancer underwent a respiration-correlated CT (4DCT), a respiration-gated CBCT (G-CBCT) near end expiration and a one-minute free-breathing CBCT scan on a single treatment day. Respiration was recorded with an external monitor. An RMC-CBCT and an uncorrected CBCT (NC-CBCT) were computed from the free-breathing scan, based on a respiratory model of deformations derived from the 4DCT. Localization discrepancy was computed as the 3D displacement of the GEJ region (GEJ patients), or gross tumor volume (GTV) and kidneys (pancreas patients) in the NC-CBCT and RMC-CBCT relative to their positions in the G-CBCT. Similarity of soft-tissue features was measured using a normalized cross correlation (NCC) function.ResultsLocalization discrepancy from the end-expiration G-CBCT was reduced for RMC-CBCT compared to NC-CBCT in eight of eleven GEJ cases (mean ± standard deviation, respectively, 0.21 ± 0.11 and 0.43 ± 0.28 cm), in all five pancreatic GTVs (0.26 ± 0.21 and 0.42 ± 0.29 cm) and all ten kidneys (0.19 ± 0.13 and 0.51 ± 0.25 cm). Soft-tissue feature similarity around GEJ was higher with RMC-CBCT in nine of eleven cases (NCC =0.48 ± 0.20 and 0.43 ± 0.21), and eight of ten kidneys (0.44 ± 0.16 and 0.40 ± 0.17).ConclusionsIn a prospective study of motion-corrected CBCT in GEJ and pancreas, RMC-CBCT yielded improved organ visibility and localization accuracy for gated treatment at end expiration in the majority of cases.
| S-EPMC6053337 | biostudies-literature