X-ray Cone-beam CT Research Articles

Learning Scatter Artifact Correction in Cone-Beam X-Ray CT Using Incomplete Projections with Beam Hole Array

X-ray cone-beam computed tomography (CBCT) is a powerful tool for nondestructive testing and evaluation, yet the CT image quality can be compromised by artifact due to X-ray scattering within dense materials such as metals. This problem leads to the need for hardware- and software-based scatter artifact correction to enhance the image quality. Recently, deep learning techniques have merged as a promising approach to obtain scatter-free images efficiently. However, these deep learning techniques rely heavily on training data, often gathered through simulation. Simulated CT images, unfortunately, do not accurately reproduce the real properties of objects, and physically accurate X-ray simulation still requires significant computation time, hindering the collection of a large number of CT images. To address these problems, we propose a deep learning framework for scatter artifact correction using projections obtained solely by real CT scanning. To this end, we utilize a beam-hole array (BHA) to block the X-rays deviating from the primary beam path, thereby capturing scatter-free X-ray intensity at certain detector pixels. As the BHA shadows a large portion of detector pixels, we incorporate several regularization losses to enhance the training process. Furthermore, we introduce radiographic data augmentation to mitigate the need for long scanning time, which is a concern as CT devices equipped with BHA require two series of CT scans. Experimental validation showed that the proposed framework outperforms a baseline method that learns simulated projections where the entire image is visible and does not contain scattering artifacts.

High-resolution tiled X-ray cone-beam CT using the ASTRA toolbox

High-resolution tiled X-ray cone-beam CT using the ASTRA toolbox

Effect of academic-environmental stress on apical periodontitis of non-endodontic teeth

Abstract Background: The periapical area of a tooth was diagnosed using radiography; many types of risk factors can affect the health of the apical area which is the stress during life. Objective: To analyze the prevalence of academic-environmental stress and apical periodontitis in non-endodontic teeth of dental students using cone-beam computed tomography (CBCT) X-ray, and to demonstrate the association between stress and the prevalence of apical periodontitis. Materials and Methods: Cross-sectional study was done on the 103 recruited dental students aged 22–24 years during the final examination year of study in dentistry college. The academic-environmental stress scale was used to measure the level of stress in each student. The CBCT X-ray was taken for each student. The apical area was measured only for non-root canal-treated teeth using the CBCT periapical radiography index. Chi-square (χ 2) test was used to show the percentages of stress and the relationship between apical periodontitis and stress in students. Results: 53 students (51.5%) had a stressed state, whereas 50 students (48.5%) had a non-stressful state. The prevalence of apical periodontitis was greater among stressed than that of non-stressed students in non-endodontic teeth. Statistically, there was a significant relationship between academic-environmental stress and apical periodontitis in non-endodontic teeth. Conclusion: There was a negative effect of examination stress on the apical healthy of teeth that can be increased with the presence of any additional factors such as problems of life.

Geometric accuracy in patient positioning for stereotactic radiotherapy of intracranial tumors.

This study determines and compares the geometric setup errors between stereoscopic x-ray and kilo-voltage cone beam CT (CBCT) in phantom tests on a linear accelerator (linac) for image-guided (IG) stereotactic radiotherapy of intracranial tumors. Additionally, dose-volume metrics in the target volumes of the setup errors of CBCT were evaluated. A Winston-Lutz- and an anthropomorphic phantom were used. The mean deviation and root mean square error (RMSE) of CBCT and stereoscopic x-ray were compared. Dose-volume metrics of the planning target volume (PTV) and gross target volume (GTV) for CBCT were calculated. The RMSEs in the tests with the Winston-Lutz-Phantom were 0.3mm, 1.1mm and 0.3mm for CBCT and 0.1mm, 0,1 mm and<0.1mm for stereoscopic x-ray in the translational dimensions (right-left, anterior-posterior and superior-inferior). The RMSEs in the tests with the anthropomorphic phantom were 0.3mm, 0.2mm and 0.1mm for CBCT and 0.1mm, 0,1 mm and<0.1mm for stereoscopic x-ray. The effects on dose-volume metrics of the setup errors of CBCT on the GTV were within 1 % for all considered dose values. The effects on the PTV were within 5 % for all considered dose values. Both IG systems provide high accuracy patient positioning within a submillimeter range. The phantom tests exposed a slightly higher accuracy of stereoscopic x-ray than CBCT. The comparison with other studies with a similar purpose emphasizes the importance of individual IG installation quality assurance.

Development and application of high-performance cone-beam industrial X-ray CT system

Development and application of high-performance cone-beam industrial X-ray CT system

Investigation of Computed Tomography Numbers on Multiple Imaging Systems using Single and Multislice Methods.

The aim of this study is to determine the variation in Hounsfield values with single and multi-slice methods using in-house software on fan-beam computed tomography (FCT), linear accelerator (linac) cone-beam computed tomography (CBCT), and Icon-CBCT datasets acquired using Gammex and advanced electron density (AED) phantoms. The AED phantom was scanned on a Toshiba computed tomography (CT) scanner, five linac-based CBCT X-ray volumetric imaging systems, and Leksell Gamma Knife Icon. The variation between single and multi-slice methods was assessed by comparing scans acquired using Gammex and AED phantoms. The variation in Hounsfield units (HUs) between seven different clinical protocols was assessed using the AED phantom. A CIRS Model 605 Radiosurgery Head Phantom (TED) phantom was scanned on all three imaging systems to assess the target dosimetric changes due to HU variation. An in-house software was developed in MATLAB to assess the HU statistics and the trend along the longitudinal axis. The FCT dataset showed a minimal variation (central slice ± 3 HU) in HU values along the long axis. A similar trend was also observed between the studied clinical protocols acquired on FCT. Variation among multiple linac CBCTs was insignificant. In the case of the water insert, a maximum HU variation of -7.23 ± 68.67 was observed for Linac 1 towards the inferior end of the phantom. All five linacs appeared to have a similar trend in terms of HU variation from the proximal to the distal end of the phantom, with a few outliers for Linac 5. Among three imaging modalities, the maximum variation was observed in gamma knife CBCTs, whereas FCT showed no appreciable deviation from the central value. In terms of dosimetric comparison, the mean dose in CT and Linac CBCT scans differed by <0.5 Gy, whereas at least a 1 Gy difference was observed between CT and gamma knife CBCT. This study shows a minimal variation with FCT between single, volume-based, and multislice methods, and hence the current approach of determining the CT-electron density curve based on a single-slice method would be sufficient for producing a HU calibrations curve for treatment planning. However, CBCTs acquired on linac, and in particular, gamma knife systems, show noticeable variations along the long axis, which is likely to affect the dose calculations performed on CBCTs. It is highly recommended to assess the Hounsfield values on multiple slices before using the HU curve for dose calculations.

Influence of head positioning during cone-beam CT imaging on the accuracy of virtual 3D models.

Cone beam computed tomography (CBCT) images are being increasingly used to acquire three-dimensional (3D) models of the skull for additive manufacturing purposes. However, the accuracy of such models remains a challenge, especially in the orbital area. The aim of this study is to assess the impact of four different CBCT imaging positions on the accuracy of the resulting 3D models in the orbital area. An anthropomorphic head phantom was manufactured by submerging a dry human skull in silicon to mimic the soft tissue attenuation and scattering properties of the human head. The phantom was scanned on a ProMax 3D MAX CBCT scanner using 90 and 120 kV for four different field of view positions: standard; elevated; backwards tilted; and forward tilted. All CBCT images were subsequently converted into 3D models and geometrically compared with a "gold-standard" optical scan of the dry skull. Mean absolute deviations of the 3D models ranged between 0.15 ± 0.11 mm and 0.56 ± 0.28 mm. The elevated imaging position in combination with 120 kV tube voltage resulted in an improved representation of the orbital walls in the resulting 3D model without compromising the accuracy. Head positioning during CBCT imaging can influence the accuracy of the resulting 3D model. The accuracy of such models may be improved by positioning the region of interest (e.g. the orbital area) in the focal plane (Figure 2a) of the CBCT X-ray beam.

Sparse-view cone beam CT reconstruction using dual CNNs in projection domain and image domain

Cone beam computed tomography (CBCT) is used extensively in image-guided surgery and radiotherapy, but it induces ionizing radiation to the patients. Sparse-view CBCT is a main method to lower the radiation dose; however, it introduces streak artifacts in the reconstructed images. We develop a dual convolutional neural network architecture (DualCNN) to eliminate streak artifacts from sparse-view CBCT images. In the first part, we develop an interpolation CNN in the projection domain to restore the full-view projections from sparse-view projections. The restored full-view projections are then input to the Feldkamp–Davis–Kress algorithm for reconstructing the CBCT images. In the second part, we develop an image domain CNN to further improve the quality of the CBCT images. DualCNN is evaluated using real CBCT X-ray projection data of walnuts. Experimental results show that, DualCNN reconstructs good CT images with only a quarter number of full-view projections, and it achieves significantly higher performance than other representative methods in terms of qualitative and quantitative evaluations. DualCNN achieves a mean root-mean-square error of 0.0369, a mean peak-signal-to-noise ratio of 26.93 dB and a mean structural similarity of 0.732 in 3800 reconstructed images. Therefore, our DualCNN can significantly lower the CBCT radiation dose while maintaining good quality of reconstructed images.

Geometry Calibration of a Modular Stereo Cone-Beam X-ray CT System.

Compared to single source systems, stereo X-ray CT systems allow acquiring projection data within a reduced amount of time, for an extended field-of-view, or for dual X-ray energies. To exploit the benefit of a dual X-ray system, its acquisition geometry needs to be calibrated. Unfortunately, in modular stereo X-ray CT setups, geometry misalignment occurs each time the setup is changed, which calls for an efficient calibration procedure. Although many studies have been dealing with geometry calibration of an X-ray CT system, little research targets the calibration of a dual cone-beam X-ray CT system. In this work, we present a phantom-based calibration procedure to accurately estimate the geometry of a stereo cone-beam X-ray CT system. With simulated as well as real experiments, it is shown that the calibration procedure can be used to accurately estimate the geometry of a modular stereo X-ray CT system thereby reducing the misalignment artifacts in the reconstruction volumes.

Clinical application and accuracy analysis of occlusion-guided functional mandibular reconstruction

To investigate the influence of the design and application of novel surgical template on the accuracy of reconstructed mandibula and implant position in occlusion-guided functional mandibular reconstruction, so as to provide guidance for clinical treatment. Between January 2017 and May 2019, 11 patients with segmental mandible defects were treated, including 8 males and 3 females with an average age of 31.8 years (range, 19-45 years). There were 6 cases of ameloblastoma, 3 cases of keratocystic tumor, and 2 cases of ossifying fibroma. According to Urken classification of mandible defects, there were 1 case of CRB, 4 cases of RB, 2 cases of RBS, and 4 cases of SB. According to the occlusion relationship, a novel surgical template with the reconstruction titanium plate screws and implants drill-guided information was designed and manufactured. With the help of the novel surgical template, the "one and a half" fibula reconstruction mode was used for jaw functional reconstruction, and the implant supported denture was finally completed. The postoperative CT at 1 week were collected to analyze the morphology of the preoperative virtual design jaw and postoperative jaw. The coincidence of fibular reconstructed mandible (fibular upper barrel, fibular reconstructed ramus and condyle, and whole mandible) and implant in mandible were calculated. When the coincidence was less than 80%, it was considered that the deviation was obvious. Oral panoramic X-ray film and cone beam CT were examined at 6 months after operation to evaluate the osseointegration before implant repair. None of the 11 flaps had postoperative vascular crisis. One flap occurred necrosis at 1 month after reconstruction combined with 3 implants failed, and had been removed at 6 months after reconstructed surgery; the others had no flap necrosis. One week postoperatively, the coincidence of the fibular upper barrel was 87.55%±3.08%, the whole mandible was 82.68%±5.94%, and the implant in mandible was 88.00%, with significant differences ( t=8.131, P=0.000; t=2.118, P=0.046; Z=4.070, P=0.000) when compared to 80%, respectively. The fibular reconstructed ramus and condyle was 77.82%±3.54%, with no significant difference ( t=-2.042, P=0.068) when compared to 80%. Six months postoperatively, oral panoramic X-ray film and cone beam CT showed that all 22 implants achieved osseointegration and the palatal mucosa transplantation was performed, then finally completed the denture rehabilitation at 6-9 months after operation. All patients were satisfied with their postoperative appearance. The novel surgical template can guarantee the accuracy of functional mandible reconstruction guided by occlusal guidance, and ultimately achieve the beautiful contour of jaw and occlusal function reconstruction, and improve the patient's life quality.

Multi-Slice Fusion for Sparse-View and Limited-Angle 4D CT Reconstruction

Inverse problems spanning four or more dimensions such as space, time andother independent parameters have become increasingly important. State-of-the-art 4D reconstruction methods use model based iterative reconstruction (MBIR), but depend critically on the quality of the prior modeling. Recently, plug-and-play (PnP) methods have been shown to be an effective way to incorporate advanced prior models using state-of-the-art denoising algorithms. However, state-of-the-art denoisers such as BM4D and deep convolutional neural networks (CNNs) are primarily available for 2D or 3D images and extending them to higher dimensions is difficult due to algorithmic complexity and the increased difficulty of effective training. In this paper, we present multi-slice fusion , a novel algorithm for 4D reconstruction, based on the fusion of multiple low-dimensional denoisers. Our approach uses multi-agent consensus equilibrium (MACE), an extension of plug-and-play, as a framework for integrating the multiple lower-dimensional models. We apply our method to 4D cone-beam X-ray CT reconstruction for non destructive evaluation (NDE) of samples that are dynamically moving during acquisition. We implement multi-slice fusion on distributed, heterogeneous clusters in order to reconstruct large 4D volumes in reasonable time and demonstrate the inherent parallelizable nature of the algorithm. We present simulated and real experimental results on sparse-view and limited-angle CT data to demonstrate that multi-slice fusion can substantially improve the quality of reconstructions relative to traditional methods, while also being practical to implement and train.

A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system

ABSTRACT Accurate knowledge of the acquisition geometry of a CT scanning system is key for high quality tomographic imaging. Unfortunately, in modular X-ray CT setups, geometry misalignment occurs each time the setup is changed, which calls for an efficient calibration procedure to correct for geometric inaccuracies. Although many studies have been dealing with the calibration of X-ray CT systems, these are often specifically designed for one setup and/or expensive. In this work, we explore the possibilities of a low-cost, easy-to-build, and modular phantom, constructed from LEGO bricks, which serves as a structure to hold small metal beads, for geometric calibration of a tomographic X-ray system. By estimating the bead coordinates using deep learning, and minimizing center-to-center distances of the metal beads between measured and reference projection data, geometry parameters are derived. With simulated as well as real experiments, it is shown that the LEGO phantom can be used to accurately estimate the geometry of a modular X-ray CT system.

Detection of Vertical Root Fractures Using Three Different Imaging Modalities: An In Vitro Study

The diagnosis of nondisplaced longitudinal fractures [vertical root fractures (VRFs)] is challenging in clinical practice. Radiographic techniques showed a difficulty in detection of VRFs. Cone-beam computed tomography (CBCT) is a new diagnostic imaging modality that provides high-quality three-dimensional (3D) images for dental diagnosis. The aim of this in vitro study is to compare accuracy of three different imaging modalities: conventional periapical radiographs, digital radiographs, and CBCT in detecting VRFs in teeth that are endodontically as well as nonendodontically treated. An in vitro model consisting of 60 recently extracted human mandibular lower premolars were used. Root canal treatment was carried out for 30 teeth. Root fractures were created in 30 teeth (15 root canal treated and 15 non-treated) by mechanical force. Other 30 teeth remain intact. The teeth were mounted and images were taken with a periapical, digital, and CBCT X-ray unit. Three endodontists separately evaluated the images. Interobserver κ values showed a very good interobserver agreement (0.98 for CBCT, 0.88 for digital, and 0.93 for conventional periapical X-rays). There was an overall statistically significant difference (p = 0.00) in detecting of root fracture among the three imaging modalities and the highest accuracy with CBCT images. In in vitro model, CBCT scan appears to give the highest accuracy in detecting VRFs when compared with the periapical systems in both endodontically and nonendodontically treated teeth. The CBCT scan shows higher sensitivity in detection of VRFs in comparison with periapical images.

Slice-wise reconstruction for low-dose cone-beam CT using a deep residual convolutional neural network

Because of the growing concern over the radiation dose delivered to patients, X-ray cone-beam CT (CBCT) imaging of low dose is of great interest. It is difficult for traditional reconstruction methods such as Feldkamp to reduce noise and keep resolution at low doses. A typical method to solve this problem is using optimization-based methods with careful modeling of physics and additional constraints. However, it is computationally expensive and very time-consuming to reach an optimal solution. Recently, some pioneering work applying deep neural networks had some success in characterizing and removing artifacts from a low-dose data set. In this study, we incorporate imaging physics for a cone-beam CT into a residual convolutional neural network and propose a new end-to-end deep learning-based method for slice-wise reconstruction. By transferring 3D projection to a 2D problem with a noise reduction property, we can not only obtain reconstructions of high image quality, but also lower the computational complexity. The proposed network is composed of three serially connected sub-networks: a cone-to-fan transformation sub-network, a 2D analytical inversion sub-network, and an image refinement sub-network. This provides a comprehensive solution for end-to-end reconstruction for CBCT. The advantages of our method are that the network can simplify a 3D reconstruction problem to a 2D slice-wise reconstruction problem and can complete reconstruction in an end-to-end manner with the system matrix integrated into the network design. Furthermore, reconstruction can be less computationally expensive and easily parallelizable compared with iterative reconstruction methods.

Giant-cell granuloma: 2 case reports

Introduction: Giant-cell granuloma (GCG) is a benign tumor occurring almost exclusively in the jaws. These lesions remain rare but can sometime have an aggressive behavior. In this article, we will describe and follow two cases of GCG. Observations: The first case is a referred female patient, who presents a mandibular swelling. Its clinical and radiological aspects lead us to do a biopsy, with a histological result of GCG. The second case is a patient with a terminal kidney failure, referred for a buccal swelling in the upper left jaw. The cone-beam computed tomography X-ray shows a compartmentalized lesion with blurry limits. An excisional biopsy is performed and the histological diagnosis is a GCG. Discussion: Although the first patient suffers from no systemic disease, the second one presents a terminal kidney failure resulting in a chronic hyperparathyroidism. Hyperparathyroidism can activate osteoclastic resorption and create bone lesions such as brown tumors. Conclusion: The slow and asymptomatic growth of these lesions often result in a late diagnosis. It should be kept in mind as a differential diagnosis when dealing with an osteolytic lesion of the jaws with no clear etiology, especially if hyperparathyroidism or kidney failure is associated.

Estimated radiation risk of cancer from dental cone-beam computed tomography imaging in orthodontics patients

BackgroundRadiation dose evaluation is important to cone-beam computed tomography (CBCT) for routine orthodontic treatment planning, especially for a significant proportion of children in orthodontic patients. This study evaluated the patient radiation dose and estimated the radiation cancer risk on dental CBCT according to the calculations by the Monte Carlo simulation method.MethodsThe dental CBCT scanner evaluated in this project was the i- CAT® (Imaging Sciences International Inc., PA, U.S.A.) device. Organ doses and effective doses were calculated by using personal computer-based Monte Carlo simulation (PCXMC 2.0 Rotation) software. The cancer risk resulting from the exposure to ionizing radiation was estimated by using the BEIR VII (Biologic Effects of Ionizing Radiation VII) report model, and the risk of exposure-induced death (REID) was assessed by PCXMC 2.0 Rotation software.ResultsThe largest contribution to the organ dose and effective dose at Zref 83 cm positioned in the dental CBCT x-ray beam centerline was from the salivary glands (738.29μGy, 7.38 μSv). The different organ doses showed the maximum values at the different Zref locations, and the largest contribution to the organ dose and effective dose of all simulated positions was from the thyroid (928.77μGy, 37.5 μSv). The REID values in the 10-year olds (22.6 × 10− 7, female; 19 × 10− 7, male) were approximately double than those in 30-year olds (10.4 × 10− 7, female; 8.88 × 10− 7, male) for all cancers. The highest change during age range from 10 to 30 was shown in breast cancer of females.ConclusionsAlthough individual cancer risk estimates as a function of gender and age are small, the concern about the risks from dental CBCT is related to the rapid increase in its use for orthodontic practice, especially in children patients.

Relationship between tooth length and three-dimensional mandibular morphology.

To clarify the relationship between tooth length and three-dimensional mandibular morphology in a healthy Japanese population. This study included 181 Japanese adults: 66 men and 115 women. Cone-beam computed tomography (CBCT) images were acquired with a dentofacial cone-beam x-ray CT scanner. Tooth length was measured with open-source OsiriX medical image processing software. Crown height and root length were measured in the maxillary and mandibular central incisors, lateral incisors, canines, first premolars, second premolars, first molars, and second molars. Based on these measurements, principal component (PC) analysis was performed. The following measurements were used to assess three-dimensional mandibular morphology: CD-GO, GO-GN, RCD-LCD, RGO-LGO, RCP-LCP, and the gonial angle. Stepwise multiple regression analysis was performed to examine the associations between three-dimensional mandibular morphology and the patterns of crown and root lengths using the mandibular measurements as explanatory variables and each PC as the dependent variable. CD-GO was positively associated with PC1, which represented overall tooth length. RGO-LGO was positively associated with PC2, whereas GO-GN, RCP-LCP, and gonial angle were negatively associated with PC2, which was the axis denoting relatively longer root (+) vs higher crown (-). Being female was associated with PC3, which was the axis denoting relatively longer posterior tooth (+) vs anterior tooth (-). The present clinical study effectively used CBCT images and PC analysis to reveal significant correlations between tooth length and mandibular morphology in a modern human population, confirming in part the statement that "large teeth necessitate large jaws."

A patient-centric approach to quality control and dosimetry in CT including CBCT

One measurement and an algebraic formula are used to calculate the incident air kerma (Ka,i) at the skin after any CT examination, including cone-beam CT (CBCT) and multi-slice CT (MSCT).Empty scans were performed with X-ray CBCT systems (dental, C-arm and linac guidance scanners) as well as two MSCT scanners. The accumulated Ka,i at the flat panel (in CBCT) or the maximum incident air kerma at the isocentre (in MSCT) were measured using a solid-state probe. The average Ka,i(skin), at the skin of a hypothetical patient, was calculated using the proposed formula. Additional measurements of dose at the isocentre (DFOV) and kerma-area product (KAP), as well as Ka,i(skin) from thermoluminiscence dosimeters (TLDs) and size-specific dose estimates are presented for comparison.The Ka,i(skin) for the standard head size in the dental scanner, the C-arm (high dose head protocol) and the linac (head protocol) were respectively 3.33 ± 0.19 mGy, 15.15 ± 0.76 mGy and 3.23 ± 0.16 mGy. For the first MSCT, the calculated Ka,i(skin) was 13.1 ± 0.7 mGy and the TLDs provided a Ka,i(skin) between 10.3 ± 1.1 mGy and 13.8 ± 1.4 mGy.Estimation of patient air kerma in tomography with an uncertainty below 7% is thus feasible using an empty scan and conventional measurement tools. The provided equations and website can be applied to a standard size for the sake of quality control or to several sizes for the definition of diagnostic reference levels (DRLs). The obtained incident air kerma can be directly compared to the Ka,i from other X-ray modalities as recommended by ICRU and IAEA.

Z-Index Parameterization for Volumetric CT Image Reconstruction via 3-D Dictionary Learning.

Despite the rapid developments of X-ray cone-beam CT (CBCT), image noise still remains a major issue for the low dose CBCT. To suppress the noise effectively while retain the structures well for low dose CBCT image, in this paper, a sparse constraint based on the 3-D dictionary is incorporated into a regularized iterative reconstruction framework, defining the 3-D dictionary learning (3-DDL) method. In addition, by analyzing the sparsity level curve associated with different regularization parameters, a new adaptive parameter selection strategy is proposed to facilitate our 3-DDL method. To justify the proposed method, we first analyze the distributions of the representation coefficients associated with the 3-D dictionary and the conventional 2-D dictionary to compare their efficiencies in representing volumetric images. Then, multiple real data experiments are conducted for performance validation. Based on these results, we found: 1) the 3-D dictionary-based sparse coefficients have three orders narrower Laplacian distribution compared with the 2-D dictionary, suggesting the higher representation efficiencies of the 3-D dictionary; 2) the sparsity level curve demonstrates a clear Z-shape, and hence referred to as Z-curve, in this paper; 3) the parameter associated with the maximum curvature point of the Z-curve suggests a nice parameter choice, which could be adaptively located with the proposed Z-index parameterization (ZIP) method; 4) the proposed 3-DDL algorithm equipped with the ZIP method could deliver reconstructions with the lowest root mean squared errors and the highest structural similarity index compared with the competing methods; 5) similar noise performance as the regular dose FDK reconstruction regarding the standard deviation metric could be achieved with the proposed method using (1/2)/(1/4)/(1/8) dose level projections. The contrast-noise ratio is improved by ~2.5/3.5 times with respect to two different cases under the (1/8) dose level compared with the low dose FDK reconstruction. The proposed method is expected to reduce the radiation dose by a factor of 8 for CBCT, considering the voted strongly discriminated low contrast tissues.

P14.20 Local control an overall survival after frameless LINAC radiosurgery: a single center experience

Abstract Introduction: Stereotactic radiosurgery (SRS) has been increasingly advocated for 1-3 small brain metastases. Goal of this study was to evaluate the clinical results in patients with brain metastases treated with SRS using a thermoplastic mask non-invasive fixation system and image-guided treatment. MATERIAL AND METHODS: In this single-institution study 48 patients with 77 brain metastases were treated between February 2012 and January 2014. The head fixation was realized using a BrainLAB thermoplastic mask. The prescribed dose was 20 Gy or 18 Gy as a single dose. The SRS were performed with a True Beam STX Novalis Radiosurgery LINAC (Varian Medical Systems). The verification of positioning was done using the BrainLAB ExacTrac ® X-ray 6D system and cone-beam CT. Results: In 69 of 77 (89.6%) treated brain metastases the follow-up was documented on MR imaging performed every 3 months. In 7/69 (10.1%) brain metastases local failure was diagnosed with a mean follow-up time of 10.7 months (range 1-43 months). Estimated 1-year local control was 83.1%. Median progression free survival (PFS) was 3.7 months, largely due to distant brain relapse. A GTV of ≤ 2.0 cm3 was significantly associated with a better PFS than a GTV > 2.0 cm3. We observed 2 cases of radiation necrosis diagnosed by histology after surgical resection. No other cases of severe side effects (CTACE≥3) were observed. CONCLUSION: In our experience local control after frameless (ringless) LINAC based SRS with mean follow-up of 10.7 months is 89.9%. Without the invasive head fixation radiotherapy is more comfortable for the patients.