4D cone beam CT via spatiotemporal tensor framelet.
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ABSTRACT:
SUBMITTER: Gao H
PROVIDER: S-EPMC3494730 | biostudies-other | 2012 Nov
REPOSITORIES: biostudies-other
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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:To 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.The 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.The 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.Proof 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:PURPOSE:Currently, four-dimensional (4D) cone-beam computed tomography (CBCT) requires a 3-4 min full-fan scan to ensure usable image quality. Recent advancements in sparse-view 4D-CBCT reconstruction have opened the possibility to reduce scan time and dose. The aim of this study is to provide a common framework for systematically evaluating algorithms for 4D-CBCT reconstruction from a 1-min scan. Using this framework, the AAPM-sponsored SPARE Challenge was conducted in 2018 to identify and compare state-of-the-art algorithms. METHODS:A clinically realistic CBCT dataset was simulated using patient CT volumes from the 4D-Lung database. The selected patients had multiple 4D-CT sessions, where the first 4D-CT was used as the prior CT, and the rest were used as the ground truth volumes for simulating CBCT projections. A GPU-based Monte Carlo tool was used to simulate the primary, scatter, and quantum noise signals. A total of 32 CBCT scans of nine patients were generated. Additional qualitative analysis was performed on a clinical Varian and clinical Elekta dataset to validate the simulation study. Participants were blinded from the ground truth, and were given 3 months to apply their reconstruction algorithms to the projection data. The submitted reconstructions were analyzed in terms of root-mean-squared-error (RMSE) and structural similarity index (SSIM) with the ground truth within four different region-of-interests (ROI) - patient body, lungs, planning target volume (PTV), and bony anatomy. Geometric accuracy was quantified as the alignment error of the PTV. RESULTS:Twenty teams participated in the challenge, with five teams completing the challenge. Techniques involved in the five methods included iterative optimization, motion-compensation, and deformation of the prior 4D-CT. All five methods rendered significant reduction in noise and streaking artifacts when compared to the conventional Feldkamp-Davis-Kress (FDK) algorithm. The RMS of the three-dimensional (3D) target registration error of the five methods ranged from 1.79 to 3.00 mm. Qualitative observations from the Varian and Elekta datasets mostly concur with those from the simulation dataset. Each of the methods was found to have its own strengths and weaknesses. Overall, the MA-ROOSTER method, which utilizes a 4D-CT motion model for temporal regularization, had the best and most consistent image quality and accuracy. CONCLUSION:The SPARE Challenge represents the first framework for systematically evaluating state-of-the-art algorithms for 4D-CBCT reconstruction from a 1-min scan. Results suggest the potential for reducing scan time and dose for 4D-CBCT. The challenge dataset and analysis framework are publicly available for benchmarking future reconstruction algorithms.
| S-EPMC6739166 | biostudies-literature
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.
| S-EPMC4263642 | biostudies-literature
Project description:PurposeTo improve the accuracy of liver tumor localization, this study tests a biomechanical modeling-guided liver cone-beam CT (CBCT) estimation (Bio-CBCT-est) technique, which generates new CBCTs by deforming a prior high-quality CT or CBCT image using deformation vector fields (DVFs). The DVFs can be used to propagate tumor contours from the prior image to new CBCTs for automatic 4D tumor localization.Methods/materialsTo solve the DVFs, the Bio-CBCT-est technique employs an iterative scheme that alternates between intensity-driven 2D-3D deformation and biomechanical modeling-guided DVF regularization and optimization. The 2D-3D deformation step solves DVFs by matching digitally reconstructed radiographs of the 3D deformed prior image to 2D phase-sorted on-board projections according to imaging intensities. This step's accuracy is limited at low-contrast intra-liver regions without sufficient intensity variations. To boost the DVF accuracy in these regions, we use the intensity-driven DVFs solved at higher-contrast liver boundaries to fine-tune the intra-liver DVFs by finite element analysis-based biomechanical modeling. We evaluated Bio-CBCT-est's accuracy with seven liver cancer patient cases. For each patient, we simulated 4D cone-beam projections from 4D-CT images, and used these projections for Bio-CBCT-est based image estimations. After Bio-CBCT-est, the DVF-propagated liver tumor/cyst contours were quantitatively compared with the manual contours on the original 4D-CT 'reference' images, using the DICE similarity index, the center-of-mass-error (COME), the Hausdorff distance (HD) and the voxel-wise cross-correlation (CC) metrics. In addition to simulation, we also performed a preliminary study to qualitatively evaluate the Bio-CBCT-est technique via clinically acquired cone beam projections. A quantitative study using an in-house deformable liver phantom was also performed.ResultsUsing 20 projections for image estimation, the average (±s.d.) DICE index increased from 0.48 ± 0.13 (by 2D-3D deformation) to 0.77 ± 0.08 (by Bio-CBCT-est), the average COME decreased from 7.7 ± 1.5 mm to 2.2 ± 1.2 mm, the average HD decreased from 10.6 ± 2.2 mm to 5.9 ± 2.0 mm, and the average CC increased from -0.004 ± 0.216 to 0.422 ± 0.206. The tumor/cyst trajectory solved by Bio-CBCT-est matched well with that manually obtained from 4D-CT reference images.ConclusionsBio-CBCT-est substantially improves the accuracy of 4D liver tumor localization via cone-beam projections and a biomechanical model.
| S-EPMC6445758 | biostudies-literature
Project description:To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set.A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set. A parametrized deformation model is applied to the source FBCT image, digitally reconstructed radiographs (DRRs) that emulate the CBCT projection image geometry are calculated and compared to the target CBCT projection data, and the deformation model parameters are adjusted iteratively until the DRRs optimally match the CBCT projection data set. The resulting deformed FBCT image is hypothesized to be an accurate representation of the patient's anatomy imaged by the CBCT system. The process is demonstrated via numerical simulation. A known deformation is applied to a prior FBCT image and used to create a synthetic set of CBCT target projections. The iterative projection matching process is then applied to reconstruct the deformation represented in the synthetic target projections; the reconstructed deformation is then compared to the known deformation. The sensitivity of the process to the number of projections and the DRR/CBCT projection mismatch is explored by systematically adding noise to and perturbing the contrast of the target projections relative to the iterated source DRRs and by reducing the number of projections.When there is no noise or contrast mismatch in the CBCT projection images, a set of 64 projections allows the known deformed CT image to be reconstructed to within a nRMS error of 1% and the known deformation to within a nRMS error of 7%. A CT image nRMS error of less than 4% is maintained at noise levels up to 3% of the mean projection intensity, at which the deformation error is 13%. At 1% noise level, the number of projections can be reduced to 8 while maintaining CT image and deformation errors of less than 4% and 13%, respectively. The method is sensitive to contrast mismatch between the simulated projections and the target projections when the soft-tissue contrast in the projections is low.By using prior knowledge available in a FBCT image, the authors show that a CBCT image can be iteratively reconstructed from a comparatively small number of projection images, thus saving acquisition time and reducing imaging dose. This will enable more frequent daily imaging during radiation therapy. Because the process preserves the CT numbers of the FBCT image, the resulting 3D image intensities will be more accurate than a CBCT image reconstructed via conventional backprojection methods. Reconstruction errors are insensitive to noise at levels beyond what would typically be found in CBCT projection data, but are sensitive to contrast mismatch errors between the CBCT projection data and the DRRs.
| S-EPMC2997812 | biostudies-other
Project description:Background and purposeThe limited image quality in Cone Beam CT (CBCT) stemming primarily from scattered radiation hinders accurate CBCT based dose calculation in radiotherapy. We investigated the use of a stoichiometric calibration for dose calculation on CBCT images of lung cancer patients.Materials and methodsCBCT calibrations were performed with thorax scan protocols, using a phantom with approximately the diameter of an average human thorax and a central cavity simulating the thoracic cavity. Thus scatter conditions resembling those in clinical thorax CBCT scans were simulated. A published stoichiometric parametrization was used. A treatment plan was simulated on CBCT and CT scans of an anthropomorphic phantom, the dose distributions were calculated, and clinically relevant DVH parameters were compared. Twelve lung cancer patients had surveillance CT scans (s-CT) taken twice during their treatment course in addition to daily setup CBCTs. Dose calculations were performed on the s-CTs and the corresponding CBCTs taken on the same day, and DVH parameters were compared.ResultsEighty percent of CBCT DVH parameters found for the phantom were within ±1% of CT doses, and 98% were within ±3%. For patients, the median CT/CBCT dose difference was within ±2%, and 98% of DVH parameters were within ±4%. Minimum dose to the tumor was underestimated (median 1.9%) on CBCT, while maximum doses to most organs at risk were slightly overestimated.ConclusionDirect dose calculations on CBCTs of lung cancer patients were feasible within ∼4% accuracy using a simple calibration method, which is easily implemented in a clinical setting.
| S-EPMC7807659 | biostudies-literature
Project description:BackgroundMinimally invasive surgery (MIS) for evacuation of spontaneous intracerebral hemorrhage (ICH) has shown promise but there remains a need for intraoperative performance assessment considering the wide range of evacuation effectiveness. In this feasibility study, we analyzed the benefit of intraoperative 3-dimensional imaging during navigated endoscopy-assisted ICH evacuation by mechanical clot fragmentation and aspiration.Methods18 patients with superficial or deep supratentorial ICH underwent MIS for clot evacuation followed by intraoperative computerized tomography (iCT) or cone-beam CT (CBCT) imaging. Eligibility for MIS required (a) availability of intraoperative iCT or CBCT, (b) spontaneous lobar or deep ICH without vascular pathology, (c) a stable ICH volume (20-90 ml), (d) a reduced level of consciousness (GCS 5-14), and (e) a premorbid mRS ≤ 1. Demographic, clinical, and radiographic patient data were analyzed by two independent observers.ResultsNine female and 9 male patients with a median age of 76 years (42-85) presented with an ICH score of 3 (1-4), GCS of 10 (5-14) and ICH volume of 54 ± 26 ml. Clot fragmentation and aspiration was feasible in all cases and intraoperative imaging determined an overall evacuation rate of 80 ± 19% (residual hematoma volume: 13 ± 17 ml; p < 0.0001 vs. Pre-OP). Based on the intraoperative imaging results, 1/3rd of all patients underwent an immediate re-aspiration attempt. No patient experienced hemorrhagic complications or required conversion to open craniotomy. However, routine postoperative CT imaging revealed early hematoma re-expansion with an adjusted evacuation rate of 59 ± 30% (residual hematoma volume: 26 ± 37 ml; p < 0.001 vs. Pre-OP).ConclusionsRoutine utilization of iCT or CBCT imaging in MIS for ICH permits direct surgical performance assessment and the chance for immediate re-aspiration, which may optimize targeting of an ideal residual hematoma volume and reduce secondary revision rates.
| S-EPMC7593312 | biostudies-literature
Project description:OBJECTIVES::To determine the optimized kV setting for a narrow detector cone-beam CT (CBCT) unit. METHODS::Clinical (CL) and quantitative (QUANT) evaluations of image quality were performed using an anthropomorphic phantom. Technical (TECH) evaluation was performed with a polymethyl methacrylate phantom. Images were obtained using a PaX-i3D Green CBCT (Vatech, Hwaseong, Korea) device, with a large 21 × 19?and a medium 12 × 9?cm field of view (FOV), and high-dose (HD-ranging from 85 to 110 kV) and low-dose (LD-ranging from 75 to 95 kV) protocols, totaling four groups (21 × 19?cm HD, 21 × 19?cm LD, 12 × 9?cm HD, 12 × 9?cm LD). The radiation dose within each group was fixed by adapting the mA according to a predetermined dose-area product. For CL evaluation, three observers assessed images based on overall quality, sharpness, contrast, artefacts, and noise. For QUANT evaluation, mean gray value shift, % increase of standard deviation (SD), % of beam hardening and contrast-to-noise ratio (CNR) were calculated. For TECH evaluation, segmentation accuracy, CNR, metal artefact SD, metal object area, and sharpness were measured. Representative parameters were chosen for CL, QUANT, and TECH evaluations to determine the optimal kV based on biplot graphs. kV values of the same protocol were compared by the bootstrapping approach. The ones that had statistical differences with the best kV were considered as worse quality. RESULTS::Overall, kV values within the same group showed similar quality (p > 0.05), except for 110 kV in 21 × 19?cm HD and 85 kV in 12 × 9?cm HD of CL score; also 85, 90 kV in 21 × 19?cm HD and 75, 80 kV in 21 × 19?cm LD of QUANT score which were worse (p < 0.05). CONCLUSION::At a constant dose, low and high kV protocols yield acceptable image quality for a narrow-detector CBCT unit.
| S-EPMC6476352 | biostudies-literature
Project description:Background. The present study was undertaken to compare the Hounsfield Unit (HU) in computed tomography (CT) with the gray level in CBCT in human tissues. Methods. In this study, 25 different soft and hard tissues were evaluated in 21 patients. CBCT images were taken with Newtom VGi machine (Verona, Italy) and CT images were prepared with Somatom Sensation unit (Siemens, Germany). The HU values of soft and hard tissues were compared with the gray level values of CBCT images. Results. There was a strong correlation between the HU in CT and the gray level in CBCT in soft tissues (P<0.001, R2 = 0.85) and hard tissues (P<0.001, R2 = 0.74) and in general (P<0.001, R2 = 0.91). Conclusion. A high degree of agreement was seen between HU in CT and gray level in CBCT in both hard and soft tissues. Since the gray level in CBCT was similar to HU in CT and can be used as a parameter determine bone density in implant treatment and also to determine the bone type, the CBCT technique is recommended in such cases due to its low radiation dose, short time and low cost compared to CT.
| S-EPMC6904917 | biostudies-literature