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To suppress scatter in cone beam computed tomography (CBCT), two-dimensional antiscatter grids (2D grid) have been recently proposed. In this work, we developed several grid prototypes with higher grid ratios and smaller grid pitches than previous designs, and quantified their primary and scatter transmission properties in the context of CBCT for radiation therapy. Three focused 2D grid prototypes were developed with grid ratios at 12 and 16, and grid pitches at 2 and 3 mm. Their scatter transmission properties were measured between 80-140 kVp, and benchmarked against a high performance radiographic grid (1D grid) using a Varian TrueBeam CBCT system. The effect of source-grid misalignment on the primary transmission and the improvement in contrast-to-noise ratio (CNR) were also evaluated. Changing the grid pitch from two to three mm increased the average primary transmission from 84% to 89%. Maximum scatter-to-primary ratio (SPR) with grid ratio of 12 was 0.3, and increasing the grid ratio to 16 reduced SPR by 30%. A 10 mm misalignment in 2D grid position led to a 6%-8% reduction in average primary transmission, and reduction was more pronounced for the higher grid ratio. 2D grids provided up to factor of seven lower SPR and 21% better primary transmission than the 1D grid, and their scatter transmission exhibited lower energy dependence. While 2D grids provided up to factor of 2.3 higher CNR improvement, a significant variation in CNR improvement was not observed among different grid pitch and ratios. In summary, grid ratio of 16 and grid pitch of 2 mm can keep SPRs below 0.2 even in high scatter conditions, while keeping primary transmission fractions above 80%, key benefits of the investigated 2D grids in improving image quality of CBCT. However, such grids require precise alignment in source-grid geometry during CBCT acquisitions. This study also implies that 2D grids can provide substantially better scatter suppression and primary transmission than high-performance 1D grids currently available.

The purpose of this work is to evaluate the absorbed dose to the eye lenses due to the cone beam computed tomography (CBCT) system used to accurately position the patient during head-and-neck image guided procedures. The on-board imaging (OBI) systems (v.1.5) of Clinac iX and TrueBeam (Varian) accelerators were used to evaluate the imparted dose to the eye lenses and some additional points of the head. All CBCT scans were acquired with the Standard-Dose Head protocol from Varian. Doses were measured using thermoluminescence dosimeters (TLDs) placed in an anthropomorphic phantom. TLDs were calibrated at the beam quality used to reduce their energy dependence. Average dose to the lens due to the OBI systems of the Clinac iX and the TrueBeam were 0.71 ± 0.07 mGy/CBCT and 0.70 ± 0.08 mGy/CBCT, respectively. The extra absorbed dose received by the eye lenses due to one CBCT acquisition with the studied protocol is far below the 500 mGy threshold established by ICRP for cataract formation (ICRP 2011 Statement on Tissue Reactions). However, the incremental effect of several CBCT acquisitions during the whole treatment should be taken into account.

The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024 × 768 pixels.

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters and in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e., the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt angle that reduced quantum noise in the region of the stimulus by avoiding highly attenuating anatomical structures. The task-driven imaging framework offers a potentially valuable paradigm for prospective definition of acquisition and reconstruction protocols that improve task performance without increase in dose.

The use of cone beam CT in common radiotherapy treatments is increasing with the growth of image guided radiotherapy. Whilst the benefits that this technology offers are clear, such as improved patient positioning prior to treatment, it is always important to consider the implications of such intensive imaging regimes on the patient, especially when considering the fundamental radiation protection requirements for justification and optimisation.The purpose of this study was to develop a technique that uses readily available dose calculation software (PCXMC 2.0) to estimate the organ and effective doses that result from these types of examination in prostate treatments on the Varian OBI system. It has been shown that by separating these types of examinations into 28 different projections, with a range of x-ray beam qualities, it is possible to reproduce the complex geometry that is used on these imaging systems in PCXMC i.e. asymmetric radiation field with a half bowtie filter rotating 360° around the patient.This new technique has been validated with thermo-luminescent dosimeter measurements in the Rando anthropomorphic phantom, and has been shown to give excellent agreement with this established method (R(2) = 0.995). This technique will prove to be valuable to radiotherapy departments that are looking to optimise their CBCT imaging protocols as it allows a rapid evaluation of the impact of any changes on patient dose. It also serves to further highlight the levels of dose that these types of patient are subject to when having daily CBCT scans as part of the treatment, which further reinforces the need for optimisation of both patient dose and image quality on these systems.

Rotational artifacts in image guidance systems lead to registration errors that affect non-isocentric treatments and dose to off-axis organs-at-risk. This study investigates a rotational artifact in the images acquired with the on-board cone beam computed tomography system XVI (Elekta, Stockholm, Sweden). The goals of the study are to identify the cause of the artifact, to characterize its dependence on other quantities, and to investigate possible solutions. A 30 cm diameter cylindrical phantom is used to acquire clockwise and counterclockwise scans at five speeds (120 to 360 deg min(-1)) on six Elekta linear accelerators from three generations (MLCi, MLCi2 and Agility). Additional scans are acquired with different pulse widths and focal spot sizes for the same mAs. Image quality is evaluated using a common phantom with an in-house three dimensional contrast transfer function attachment. A robust, operator-independent analysis is developed which quantifies rotational artifacts with 0.02° accuracy and imaging system delays with 3 ms accuracy. Results show that the artifact is caused by mislabelling of the projections with a lagging angle due to various imaging system delays. For the most clinically used scan speed (360 deg min(-1)), the artifact is ∼0.5°, which corresponds to ∼0.25° error per scan direction with the standard Elekta procedure for angle calibration. This leads to a 0.5 mm registration error at 11 cm off-center. The artifact increases linearly with scan speed, indicating that the system delay is independent of scan speed. For the most commonly used pulse width of 40 ms, this delay is 34 ± 1 ms, part of which is half the pulse width. Results are consistent among the three linac generations. A software solution that corrects the angles of individual projections is shown to eliminate the rotational error for all scan speeds and directions. Until such a solution is available from the manufacturer, three clinical solutions are presented, which reduce the rotational error without compromising image quality.

Joint space morphology can be indicative of the risk, presence, progression, and/or treatment response of disease or trauma. We describe a novel methodology of characterizing joint space morphology in high-resolution 3D images [e.g., cone-beam CT (CBCT)] using a model based on elementary electrostatics that overcomes a variety of basic limitations of existing 2D and 3D methods. The method models each surface of a joint as a conductor at fixed electrostatic potential and characterizes the intra-articular space in terms of the electric field lines resulting from the solution of Gauss’ Law and the Laplace equation. As a test case, the method was applied to discrimination of healthy and osteoarthritic subjects (N = 39) in 3D images of the knee acquired on an extremity CBCT system. The method demonstrated improved diagnostic performance (area under the receiver operating characteristic curve, AUC > 0.98) compared to simpler methods of quantitative measurement and qualitative image-based assessment by three expert musculoskeletal radiologists (AUC = 0.87, p-value = 0.007). The method is applicable to simple (e.g., the knee or elbow) or multi-axial joints (e.g., the wrist or ankle) and may provide a useful means of quantitatively assessing a variety of joint pathologies.

This paper describes the modelisation of the Elekta XVI Cone Beam Computed Tomography (CBCT) machine components with Geant4 and its validation against calibration data taken for two commonly used machine setups. Preliminary dose maps of simulated CBCTs coming from this modelisation work are presented. This study is the first step of a research project, GHOST, aiming to improve the understanding of late toxicity risk in external beam radiotherapy patients by simulating dose depositions integrated from different sources (imaging, treatment beam) over the entire treatment plan. The second cancer risk will then be derived from different models relating irradiation dose and second cancer risk.

Cone-beam computed tomography (CBCT) imaging is an important requirement to perform real-time therapeutic image-guided procedures on patients. The purpose of this study is to estimate the personal-dose-equivalent and annual-personal-dose from CBCT imaging during transarterial chemoembolisation (TACE).Therapeutic staff doses (therapeutic and assistant physician) were collected during 200 patient (65 ± 15 years, range: 40–86) CBCT examinations over six months. Absorbed doses were assessed using thermo-luminescent dosimeters during patient hepatic TACE therapy. We estimated personal-dose-equivalent (PDE) and annual-personal-dose (APD) from absorbed dose based on international atomic energy agency protocol.APD for therapeutic procedure was calculated (therapeutic physician: 5.6 mSv; assistant physician: 5.08 mSv) based on institutional work load. Regarding PDE, the hands of the staff members received a greater dose compared to other anatomical locations (therapeutic physician: 56 mSv, 72 mSv; assistant physician: 12 mSv, 14 mSv). Annual radiation doses to the eyes and hands of the staff members were lower compared to the prescribed limits by the International Commission on Radiological Protection (ICRP).PDE and APD of both therapeutic staff members were within the recommended ICRP-103 annual limit. Dose to the assistant physician was lower than the dose to the therapeutic physician during imaging. Annual radiation doses to eye-lenses and hands of both staff members were lower than prescribed limits.

The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children.

Today, quantitative analysis of three-dimensional (3D) dynamics of the left ventricle (LV) cannot be performed directly in the catheter lab using a current angiographic C-arm system, which is the workhorse imaging modality for cardiac interventions. Therefore, myocardial wall analysis is completely based on the 2D angiographic images or pre-interventional 3D/4D imaging. In this paper, we present a complete framework to study the ventricular wall motion in 4D (3D+t) directly in the catheter lab. From the acquired 2D projection images, a dynamic 3D surface model of the LV is generated, which is then used to detect ventricular dyssynchrony. Different quantitative features to evaluate LV dynamics known from other modalities (ultrasound, magnetic resonance imaging) are transferred to the C-arm CT data. We use the ejection fraction, the systolic dyssynchrony index a 3D fractional shortening and the phase to maximal contraction (ϕi, max) to determine an indicator of LV dyssynchrony and to discriminate regionally pathological from normal myocardium. The proposed analysis tool was evaluated on simulated phantom LV data with and without pathological wall dysfunctions. The LV data used is publicly available online at https://conrad.stanford.edu/data/heart. In addition, the presented framework was tested on eight clinical patient data sets. The first clinical results demonstrate promising performance of the proposed analysis tool and encourage the application of the presented framework to a larger study in clinical practice.

Four dimensional cone beam computed tomography (4DCBCT) images suffer from angular under sampling and bunching of projections due to a lack of feedback between the respiratory signal and the acquisition system. To address this problem, respiratory motion guided 4DCBCT (RMG-4DCBCT) regulates the gantry velocity and projection time interval, in response to the patient's respiratory signal, with the aim of acquiring evenly spaced projections in a number of phase or displacement bins during the respiratory cycle. Our previous study of RMG-4DCBCT was limited to sinusoidal breathing traces. Here we expand on that work to provide a practical algorithm for the case of real patient breathing data. We give a complete description of RMG-4DCBCT including full details on how to implement the algorithms to determine when to move the gantry and when to acquire projections in response to the patient's respiratory signal. We simulate a realistic working RMG-4DCBCT system using 112 breathing traces from 24 lung cancer patients. Acquisition used phase-based binning and parameter settings typically used on commercial 4DCBCT systems (4 min acquisition time, 1200 projections across 10 respiratory bins), with the acceleration and velocity constraints of current generation linear accelerators. We quantified streaking artefacts and image noise for conventional and RMG-4DCBCT methods by reconstructing projection data selected from an oversampled set of Catphan phantom projections. RMG-4DCBCT allows us to optimally trade-off image quality, acquisition time and image dose. For example, for the same image quality and acquisition time as conventional 4DCBCT approximately half the imaging dose is needed. Alternatively, for the same imaging dose, the image quality as measured by the signal to noise ratio, is improved by 63% on average. C-arm cone beam computed tomography systems, with an acceleration up to 200°/s(2), a velocity up to 100°/s and the acquisition of 80 projections per second, allow the image acquisition time to be reduced to below 60 s. We have made considerable progress towards realizing a system to reduce projection clustering in conventional 4DCBCT imaging and hence reduce the imaging dose to the patient.

Intraoperative cone-beam CT (CBCT) is increasingly used for surgical navigation and validation of device placement. In spinal deformity correction, CBCT provides visualization of pedicle screws and fixation rods in relation to adjacent anatomy. This work reports and evaluates a method that uses prior information regarding such surgical instrumentation for improved metal artifact reduction (MAR). The known-component MAR (KC-MAR) approach achieves precise localization of instrumentation in projection images using rigid or deformable 3D-2D registration of component models, thereby overcoming residual errors associated with segmentation-based methods. Projection data containing metal components are processed via 2D inpainting of the detector signal, followed by 3D filtered back-projection (FBP). Phantom studies were performed to identify nominal algorithm parameters and quantitatively investigate performance over a range of component material composition and size. A cadaver study emulating screw and rod placement in spinal deformity correction was conducted to evaluate performance under realistic clinical imaging conditions. KC-MAR demonstrated reduction in artifacts (standard deviation in voxel values) across a range of component types and dose levels, reducing the artifact to 5-10 HU. Accurate component delineation was demonstrated for rigid (screw) and deformable (rod) models with sub-mm registration errors, and a single-pixel dilation of the projected components was found to compensate for partial-volume effects. Artifacts associated with spine screws and rods were reduced by 40%-80% in cadaver studies, and the resulting images demonstrated markedly improved visualization of instrumentation (e.g. screw threads) within cortical margins. The KC-MAR algorithm combines knowledge of surgical instrumentation with 3D image reconstruction in a manner that overcomes potential pitfalls of segmentation. The approach is compatible with FBP-thereby maintaining simplicity in a manner that is consistent with surgical workflow-or more sophisticated model-based reconstruction methods that could further improve image quality and/or help reduce radiation dose.

Purpose. An algorithm for automatic spinal pedicle screw planning is reported and evaluated in simulation and first clinical studies.a#13; Methods. A statistical atlas of the lumbar spine (N=40 members) was constructed for Active Shape Model (ASM) registration of target vertebrae to an unsegmented patient CT. The atlas was augmented to include "reference" trajectories through the pedicles as defined by a spinal neurosurgeon. Following ASM registration, the trajectories are transformed to the patient CT and accumulated to define a patient-specific screw trajectory, diameter, and length. The algorithm was evaluated in leave-one-out analysis (N=40 members) and for the first time in a clinical study (N = 5 patients undergoing cone-beam CT (CBCT) guided spine surgery), and in simulated low-dose CBCT images. a#13; Results. ASM registration achieved (2.0 ± 0.5)mm root-mean-square-error (RMSE) in surface registration in 96% of cases, with outliers owing to limitations in CT image quality (high noise/slice thickness). Trajectory centerlines were conformant to the pedicle in 95% of cases. For all non-breaching trajectories, automatically defined screw diameter and length were similarly conformant to the pedicle and vertebral body (98.7%, Grade A/B). The algorithm performed similarly in CBCT clinical studies (93% centerline and screw conformance) and was consistent at the lowest dose levels tested. Average runtime in planning five-level (lumbar) bilateral screws (10 trajectories) was (312.1 ± 104.0)s. The runtime per level for ASM registration was (41.2 ± 39.9)s, and the runtime per trajectory was (4.1 ± 0.8)s, suggesting a runtime of ~(45.3 ± 39.9)s with a more fully parallelized implementation. a#13; Conclusions. The algorithm demonstrated accurate, automatic definition of pedicle screw trajectories, diameter, and length in CT images of the spine without segmentation. The studies support translation to clinical studies in free-hand or robot-assisted spine surgery, quality assurance, and data analytics in which fast trajectory definition is a benefit to workflow. a#13

Measurement of the dose gradients from the entrance surface to depth is a standard task for characterizing an ionizing radiation beam. Most gel dosimeters provide spurious results near an air interface, limiting their value for this geometry. In this study, a 3D dosimeter system consisting of a low-diffusion, radiochromic hydrogel cast in a custom polyethylene terephthalate (PETE) vessel and imaged with a modified commercial optical cone-beam computed tomography (CBCT) scanner was employed. The cylindrical vessel wall and flat ends were constructed from a 0.025 cm thick PETE sheet. The optical CBCT scanner was modified to place the entire vessel in the centre of the field of view or to have the vessel base at the optical axis. Pre-irradiation and post-irradiation scans were acquired with the sample mounted in the standard and elevated positions. The sample was irradiated with a 2x2 cm square, 6 MV x-ray beam. Normalized attenuation coefficients from the central quarter of the reconstructed beam images were compared to a Monte Carlo depth dose calculation. Placing the vessel base at the optical axis allowed accurate dose measurements to within 0.2 cm of the entrance face and for the standard position to within 0.4 cm. These measurements validated the Monte Carlo calculation and provide an alternative to parallel plate ion chambers for dose measurement in the build-up region.

This study aimed to develop geometry of irradiation applicable to the software PCXMC for organs dose estimate and the consequent calculation of effective dose in applications of Cone Beam Computed Tomography (CBCT). Three different CBCT scanners for dental applications were evaluated: CareStream CS 9000 3D; i-CAT, and Gendex GXCB-500. Initially, each image protocol was characterized dosimetrically, measuring the incident air kerma, K i and the product of air kerma-area product, P KA . A Radcal solid state detector and a PTW transmission chamber were used for this purpose. Then the technical parameters, dosimetric parameters, and geometric conditions of each preset protocol were input in the PCXMC™ software to calculate the values of effective dose. The dose values in organs and tissues vary according to the protocol used and the centering of the x-ray beam. The calculated effective dose was within the range of (15.7 to 18.7 μSv)/(41.9 to 55.7 μSv) for CS 9000 3D, (70.6 to 72.6 μSv)/(76.6 to 83.2 μSv) for the GXCB-500, and (85.9 to 120 μSv)/(114.0 to 141.1 μSv) for the Classical i-CAT. These values were compared with results obtained from dosimetric data using a thermoluminescent dosimeter, TLD, implanted in an anthropomorphic phantom. The comparison between the values obtained by PCXMC and TLD data was considered consistent. The effective dose results were very sensitive to the geometry of radiation (beam position in the mathematical stylized phantom). This factor indicated the limitations of the software used. However, the software used is very useful as a tool in the optimization process for image protocols and the awareness of professionals. It can be concluded that the use of the PCXMC Monte Carlo simulation software was useful for the assessment protocols for CBCT dental applications.

Cone beam computed tomography (CBCT) images can be used for dose calculation in adaptive radiation therapy (ART). The main challenges are the large artefacts and inaccurate Hounsfield unit (HU) values. Currently, deformed planning CT images are often used for this purpose, although anatomical accuracy might be a concern. Ideally, we would like to convert CBCT images to CT images with artifacts removed or greatly reduced and HU values corrected while keeping the anatomical accuracy. Recently, deep learning has achieved great success in image-to-image translation tasks. It is very difficult to acquire paired CT and CBCT images with exactly matching anatomy for supervised training. To overcome this limitation, we developed and tested a cycle generative adversarial network (CycleGAN) which is an unsupervised learning method and does not require paired training datasets to synthesize CT images from CBCT images. The synthesized CT (sCT) images have been compared with the deformed planning CT (dpCT) showing visual and quantitative similarity with artifacts being removed and HU value errors being reduced from 71.78 HU to 27.98 HU. Dose calculation accuracy using sCT images has been improved over the original CBCT images, with the average Gamma Index passing rate increased from 95.4% to 97.4% for 1 mm/1% criteria. A deformable phantom study has been conducted and demonstrated better anatomical accuracy for sCT over dpCT., 14 pages, 10 figures, 3 tables

The integration of pre-operative biomechanical planning with intra-operative imaging for navigated corrective spine surgery may improve surgical outcomes, as well as the accuracy and safety of manoeuvres such as pedicle screw insertion and cable tethering, as these steps are performed empirically by the surgeon. However, registration of finite element models (FEMs) of the spine remains challenging due to changes in patient positioning and imaging modalities. The purpose of this study was to develop and validate a new method registering a preoperatively constructed patient-specific FEM aimed to plan and assist anterior vertebral body tethering (AVBT) of scoliotic patients, to intraoperative cone beam computed tomography (CBCT) during navigated AVBT procedures. Prior to surgery, the 3D reconstruction of the patient's spine was obtained using biplanar radiographs, from which a patient-specific FEM was derived. The surgical plan was generated by first simulating the standing to intraoperative decubitus position change, followed by the AVBT correction techniques. Intraoperatively, a CBCT was acquired and an automatic segmentation method generated the 3D model for a series of vertebrae. Following a rigid initialization, a multi-level registration simulation using the FEM and the targeted positions of the corresponding reconstructed vertebrae from the CBCT allows for the refinement of the alignment between modalities. The method was tested with 18 scoliotic cases with a mean thoracic Cobb angle of 47° ± 7° having already undergone AVBT. The translation error of the registered FEM vertebrae to the segmented CBCT spine was 1.4 ± 1.2 mm, while the residual orientation error was 2.7° ± 2.6°, 2.8° ± 2.4° and 2.5° ± 2.8° in the coronal, sagittal, and axial planes, respectively. The average surface-to-surface distance was 1.5 ± 1.2 mm. The proposed method is a first attempt to use a patient-specific biomechanical FEM for navigated AVBT, allowing to optimize surgical strategies and screw placement during surgery.

Cone Beam Computed Tomography (CBCT) imaging for daily patient localization has gained enormous popularity as one of Image Guided Radiation Therapy (IGRT) methods in recent years. This is largerly due to the need of higher precision and accuracy in conformal beam delivery technique which is known as Intensity Modulated Radiation Therapy (IMRT). The success of this IMRT method is mainly determined by the treatment planning systems. The aim of this research is to provide detailed characteristics of incident photon beams for different beam energies from a Varian OBI 1.4 CBCT. The detailed characteristics consists of energy spectral distributions and fluence profiles. This information is critical to the future development of accurate treatment planning systems. BEAMnrc as one of EGSnrc Monte Carlo user code, has been used to simulate 100, 110, and 125 kVp photon beams from x-ray tube of a Varian OBI 1.4 CBCT. The details of each particle's complete history including where it has been and where it has interacted is stored in a phase space (phsp) data file. The phsp files are analyzed to obtain fluence profiles and energy spectral distributions.

Robotic C-arm cone beam computed tomography (CBCT) systems are playing an increasingly pivotal role in interventional cardiac procedures and high precision radiotherapy treatments. One of the main challenges in any form of cardiac imaging is mitigating the intrinsic motion of the heart, which causes blurring and artefacts in the 3D reconstructed image. Most conventional 3D cardiac CBCT acquisition techniques attempt to combat heart motion through retrospective gating techniques, whereby acquired projections are sorted into the desired cardiac phase after the completion of the scan. However, this results in streaking artefacts and unnecessary radiation exposure to the patient. Here, we present our Adaptive CaRdiac cOne BEAm computed Tomography (ACROBEAT) acquisition protocol that uses the patient's electrocardiogram (ECG) signal to adaptively regulate the gantry velocity and projection time interval in real-time. It enables prospectively gated patient connected imaging in a single sweep of the gantry. The XCAT digital software phantom was used to complete a simulation study to compare ACROBEAT to a conventional multi-sweep retrospective ECG gated acquisition, under a variety of different acquisition conditions. The effect of location and length of the acquisition window and total number of projections acquired on image quality and total scan time were examined. Overall, ACROBEAT enables up to a 5 times average improvement in the contrast-to-noise ratio, a 40% reduction in edge response width and an 80% reduction in total projections acquired compared to conventional multi-sweep retrospective ECG gated acquisition.

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The per cent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson's r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation. © 2013 Institute of Physics and Engineering in Medicine.

Truncation of a cone-beam computed tomography (CBCT) image, mainly caused by the limited field of view (FOV) of CBCT imaging, poses challenges to the problem of deformable image registration (DIR) between computed tomography (CT) and CBCT images in adaptive radiation therapy (ART). The missing information outside the CBCT FOV usually causes incorrect deformations when a conventional DIR algorithm is utilized, which may introduce significant errors in subsequent operations such as dose calculation. In this paper, based on the observation that the missing information in the CBCT image domain does exist in the projection image domain, we propose to solve this problem by developing a hybrid deformation/reconstruction algorithm. As opposed to deforming the CT image to match the truncated CBCT image, the CT image is deformed such that its projections match all the corresponding projection images for the CBCT image. An iterative forward-backward projection algorithm is developed. Six head-and-neck cancer patient cases are used to evaluate our algorithm, five with simulated truncation and one with real truncation. It is found that our method can accurately register the CT image to the truncated CBCT image and is robust against image truncation when the portion of the truncated image is less than 40% of the total image.

There is significant interest in delivering precisely targeted small-volume radiation treatments, in the pre-clinical setting, to study dose-volume relationships with tumour control and normal tissue damage. For these studies it is vital that image guidance systems and target positioning are accurately aligned (IGRT), in order to deliver dose precisely and accurately according to the treatment plan. In this work we investigate the IGRT targeting accuracy of the X-RAD 225 Cx system from Precision X-Ray using high-resolution 3D dosimetry techniques. Small cylindrical PRESAGE® dosimeters were used with optical-CT readout (DMOS) to verify the accuracy of 2.5, 1.0, and 5.0 mm X-RAD cone attachments. The dosimeters were equipped with four target points, visible on both CBCT and optical-CT, at which a 7-field coplanar treatment plan was delivered with the respective cone. Targeting accuracy (distance to agreement between the target point and delivery isocenter) and cone alignment (isocenter precision under gantry rotation) were measured using the optical-CT images. Optical-CT readout of the first 2.5 mm cone dosimeter revealed a significant targeting error of 2.1 ± 0.6 mm and a cone misalignment of 1.3 ± 0.1 mm. After the IGRT hardware and software had been recalibrated, these errors were reduced to 0.5 ± 0.1 and 0.18 ± 0.04 mm respectively, within the manufacturer specified 0.5 mm. Results from the 1.0 mm cone were 0.5 ± 0.3 mm targeting accuracy and 0.4 ± 0.1 mm cone misalignment, within the 0.5 mm specification. The results from the 5.0 mm cone were 1.0 ± 0.2 mm targeting accuracy and 0.18 ± 0.06 mm cone misalignment, outside of accuracy specifications. Quality assurance of small field IGRT targeting and delivery accuracy is a challenging task. The use of a 3D dosimetry technique, where targets are visible on both CBCT and optical-CT, enabled identification and quantification of a targeting error in 3D. After correction, the targeting accuracy of the irradiator was verified to be within 0.5 mm (or 1.0 mm for the 5.0 mm cone) and the cone alignment was verified to be within 0.2 mm (or 0.4 mm for the 1.0 mm cone). The PRESAGE®/DMOS system proved valuable for end-to-end verification of small field IGRT capabilities.

The purpose of this work is to present the results of a margin reduction study involving dosimetric and radiobiologic assessment of cumulative dose distributions, computed using an image guided adaptive radiotherapy based framework. Eight prostate cancer patients, treated with 7-9, 6 MV, intensity modulated radiation therapy (IMRT) fields, were included in this study. The workflow consists of cone beam CT (CBCT) based localization, deformable image registration of the CBCT to simulation CT image datasets (SIM-CT), dose reconstruction and dose accumulation on the SIM-CT, and plan evaluation using radiobiological models. For each patient, three IMRT plans were generated with different margins applied to the CTV. The PTV margin for the original plan was 10 mm and 6 mm at the prostate/anterior rectal wall interface (10/6 mm) and was reduced to: (a) 5/3 mm, and (b) 3 mm uniformly. The average percent reductions in predicted tumor control probability (TCP) in the accumulated (actual) plans in comparison to the original plans over eight patients were 0.4%, 0.7% and 11.0% with 10/6 mm, 5/3 mm and 3 mm uniform margin respectively. The mean increase in predicted normal tissue complication probability (NTCP) for grades 2/3 rectal bleeding for the actual plans in comparison to the static plans with margins of 10/6, 5/3 and 3 mm uniformly was 3.5%, 2.8% and 2.4% respectively. For the actual dose distributions, predicted NTCP for late rectal bleeding was reduced by 3.6% on average when the margin was reduced from 10/6 mm to 5/3 mm, and further reduced by 1.0% on average when the margin was reduced to 3 mm. The average reduction in complication free tumor control probability (P+) in the actual plans in comparison to the original plans with margins of 10/6, 5/3 and 3 mm was 3.7%, 2.4% and 13.6% correspondingly. The significant reduction of TCP and P+ in the actual plan with 3 mm margin came from one outlier, where individualizing patient treatment plans through margin adaptation based on biological models, might yield higher quality treatments.

In orthodontic diagnosis and oral treatment planning, 3D tooth model constructed by dental computed tomography (CT) images is an essential and useful assisted tool. In virtue of the higher spatial resolution and lower radiation of x-ray, cone beam computed tomography (CBCT) has been widely used in dental application. However, due to lower signal to noise ratio, vague and weak edge between tooth root and sockets as well as intensity inhomogeneity, the tooth root is easy to be under-segmented and appears false boundary. This paper presents a new hybrid active contour model in a variational level set formulation to segment the tooth root accurately. Initial shape and intensity information from the upper layer is used for next layer's enhancement and shape constraint. The hybrid level set model is constituted by multi-scale local likelihood image fitting (LLIF) energy term, prior shape constraint energy term with adaptive weight and reaction-diffusion (RD) regularization energy term. For detailed interpretation of this hybrid energy model, the intensity information in a narrowband region outside the contour was used to enhance the contrast between tooth dentine and sockets. The LLIF energy term was incorporated into the level set function to overcome the edge fuzziness and intensity inhomogeneity. The shape prior energy term with adaptive weight was used to differentiate the constraint of the contour evolution inside and outside the level set function to improve the capability of curve topology changes. The RD energy term was introduced to effectively regularize the level set evolution. A new measurement for tooth segmentation evaluation was proposed for quantitative validation. The experimental result of the proposed method was compared with two other typical approaches, and was demonstrated to achieve a higher segmentation accuracy.

To develop an online plan adaptation algorithm for intensity modulated proton therapy (IMPT) based on fast Monte Carlo dose calculation and cone beam CT (CBCT) imaging. A cohort of ten head and neck cancer patients with an average of six CBCT scans were studied. To adapt the treatment plan to the new patient geometry, contours were propagated to the CBCTs with a vector field (VF) calculated with deformable image registration between the CT and the CBCTs. Within the adaptive planning algorithm, beamlets were shifted following the VF at their distal falloff and raytraced in the CBCT to adjust their energies, creating a geometrically adapted plan. Four geometric adaptation modes were studied: unconstrained geometric shifts (Free), isocenter shift (Iso), a range shifter (RS), or isocenter shift and range shifter (Iso-RS). After evaluation of the geometrical adaptation, the weights of a selected subset of beamlets were automatically tuned using MC-generated influence matrices to fulfill the original plan requirements. All beamlet calculations were done with a fast Monte Carlo running on a GPU (graphics processing unit). Geometrical adaptation alone only worked with small anatomy changes. The weight-tuned adaptation worked for every fraction, with the Free and Iso modes performing similarly and being superior than the two range shifters modes. The mean V95 and V107 were 99.4 ± 0.9 and 6.4% ± 4.7% in the Free mode with weight tuning. The calculation time per fraction was ~5 min, but further task parallelization could reduce it to ~1-2 min for delivery adaptation right after patient setup. An online adaptation algorithm was developed that significantly improved the treatment quality for inter-fractional geometry changes. Clinical implementation of the algorithm would allow delivery adaptation right before treatment and thus allow planning margin reductions for IMPT.

Increasing evidence shows that intrafraction tumour motion monitoring must include both six degrees of freedom (6DoF): 3D translations and 3D rotations. Existing real-time algorithms for 6DoF target motion estimation require continuous intrafraction fluoroscopic imaging at high frequency, thereby exposing patients to additional high imaging dose. This paper presents the first method capable of 6DoF motion monitoring using intermittent 2D kV imaging and a continuous external respiratory signal. Our approach is to optimise a state-augmented linear correlation model between an external signal and internal 6DoF motion. In standard treatments, the model can be built using information obtained during pre-treatment cone beam CT (CBCT). Real-time 6DoF tumor motion can then be estimated using just the external signal. Intermittent intrafraction kV images are used to update the model parameters, accounting for changes in correlation and baseline shifts. The method was evaluated in silico using data from 6 lung SABR patients, with the internal tumour motion recorded with electromagnetic beacons and the external signal from a bellows belt. Projection images from CBCT (10 Hz) and intermittent kV images were simulated by projecting the 3D Calypso beacon positions onto an imager. IMRT and VMAT treatments were simulated with increasing imaging update intervals: 0.1 s, 1 s, 3 s, 10 s and 30 s. For all the tested clinical scenarios, translational motion estimates with our method had sub-mm accuracy (mean) and precision (standard deviation) while rotational motion estimates were accurate to

In a recently published paper by Li et al (2018 Phys. Med. Biol. 63 075001), reconstruction parameters were optimized for the so-called synchronized multiArtifact reduction with tomographic reconstruction (SMART-RECON) method to enable time-resolved Cone beam computed tomography angiography (TR-CBCTA) from a single short-scan CBCT data set. However, the paper did not quantitatively address how much temporal resolution can be improved by using the SMART-RECON algorithm in TR-CBCTA. The purpose of this note was to present a method to quantify this temporal resolution improvement factor and to use that method to quantify the improvement in temporal resolution using SMART-RECON and optimized reconstruction parameters. In the method proposed in this note, the potential temporal blurring caused by SMART-RECON was modeled as a convolution between a temporal Gaussian blurring kernel and the ground truth temporal enhancement curve. The width parameter of the resulting Gaussian blurring kernel was used as a surrogate metric for temporal resolution to quantify the achievable temporal resolution for the conventional filtered backprojection (FBP) and SMART-RECON methods. The ratio of the surrogate temporal resolutions for the two reconstruction methods was calculated to quantify the factor of temporal resolution improvement. The quantitative results show that the temporal resolution is improved by a factor of 4.5 using SMART-RECON compared with FBP.

Due to the higher LET of kilovoltage (kV) radiation, there is potential for an increase in relative biological effectiveness (RBE) of absorbed doses of radiation from kV cone beam computed tomography (CBCT) sources in reference to megavoltage or Co-60 doses. This work develops a method for accurately coupling a Monte Carlo (MC) radiation transport code (PENELOPE) with the damage simulation (MCDS) to predict relative numbers of DNA double strand breaks (DSBs). The MCDS accounts for slowing down of electrons and delta ray production within the cell nucleus; however, determining the spectrum of electrons incident on the cell nucleus from photons interacting in a larger region of tissue is not trivial. PENELOPE simulations were conducted with a novel tally algorithm invoked where electrons incident on a detection material were tracked and both the incident energy and the final deposited dose were recorded. The DSB yield predicted by a set of MCDS runs of monoenergetic electrons was then looked up in a table and weighted by the specific energy of the incident electron. Our results indicate that the RBE for DSB induction is 1.1 for diagnostic x-rays with energies from 80 to 125 kVp. We found no significant change in RBE with depth or filtration. The predicted absolute DSB yields are about three times lower for cells irradiated under anoxic conditions than the yield in cells irradiated under normoxic (5%) or fully aerobic (100%) conditions. However, oxygen concentration has a negligible (± 0.02) effect on the RBE of kV CBCT x-rays.

Due to a limited number of projections at each phase, severe view aliasing artifacts are present in four-dimensional cone beam computed tomography (4D-CBCT) when reconstruction is performed using conventional algorithms. In this work, we aim to obtain high-quality 4D-CBCT of lung cancer patients in radiation therapy by deforming the planning CT. The deformation vector fields (DVF) to deform the planning CT are estimated through matching the forward projection of the deformed prior image and measured on-treatment CBCT projection. The estimation of the DVF is formulated as an unconstrained optimization problem, where the objective function to be minimized is the sum of the squared difference between the forward projection of the deformed planning CT and the measured 4D-CBCT projection. A nonlinear conjugate gradient method is used to solve the DVF. As the number of the variables in the DVF is much greater than the number of measurements, the solution to such a highly ill-posed problem is very sensitive to the initials during the optimization process. To improve the estimation accuracy of DVF, we proposed a new strategy to obtain better initials for the optimization. In this strategy, 4D-CBCT is first reconstructed by total variation minimization. Demons deformable registration is performed to register the planning CT and the 4D-CBCT reconstructed by total variation minimization. The resulted DVF from demons registration is then used as the initial parameters in the optimization process. A 4D nonuniform rotational B-spline-based cardiac-torso (NCAT) phantom and a patient 4D-CBCT are used to evaluate the algorithm. Image quality of 4D-CBCT is substantially improved by using the proposed strategy in both NCAT phantom and patient studies. The proposed method has the potential to improve the temporal resolution of 4D-CBCT. Improved 4D-CBCT can better characterize the motion of lung tumors and will be a valuable tool for image-guided adaptive radiation therapy.

The field of view (FOV) of a cone-beam computed tomography (CBCT) unit in a single-photon emission computed tomography (SPECT)/CBCT system can be increased by offsetting the CBCT detector. Analytic-based algorithms have been developed for image reconstruction from data collected at a large number of densely sampled views in offset-detector CBCT. However, the radiation dose involved in a large number of projections can be of a health concern to the imaged subject. CBCT-imaging dose can be reduced by lowering the number of projections. As analytic-based algorithms are unlikely to reconstruct accurate images from sparse-view data, we investigate and characterize in the work optimization-based algorithms, including an adaptive steepest descent-weighted projection onto convex sets (ASD-WPOCS) algorithms, for image reconstruction from sparse-view data collected in offset-detector CBCT. Using simulated data and real data collected from a physical pelvis phantom and patient, we verify and characterize properties of the algorithms under study. Results of our study suggest that optimization-based algorithms such as ASD-WPOCS may be developed for yielding images of potential utility from a number of projections substantially smaller than those used currently in clinical SPECT/CBCT imaging, thus leading to a dose reduction in CBCT imaging.

Computed tomography (CT) to cone-beam computed tomography (CBCT) deformable image registration (DIR) is a crucial step in adaptive radiation therapy. Current intensity-based registration algorithms, such as demons, may fail in the context of CT-CBCT DIR because of inconsistent intensities between the two modalities. In this paper, we propose a variant of demons, called Deformation with Intensity Simultaneously Corrected (DISC), to deal with CT-CBCT DIR. DISC distinguishes itself from the original demons algorithm by performing an adaptive intensity correction step on the CBCT image at every iteration step of the demons registration. Specifically, the intensity correction of a voxel in CBCT is achieved by matching the first and the second moments of the voxel intensities inside a patch around the voxel with those on the CT image. It is expected that such a strategy can remove artifacts in the CBCT image, as well as ensuring the intensity consistency between the two modalities. DISC is implemented on computer graphics processing units (GPUs) in compute unified device architecture (CUDA) programming environment. The performance of DISC is evaluated on a simulated patient case and six clinical head-and-neck cancer patient data. It is found that DISC is robust against the CBCT artifacts and intensity inconsistency and significantly improves the registration accuracy when compared with the original demons., Comment: 22 pages, 9 figures, and 3 tables

The aim of this study is to investigate the imaging dose to red bone marrow (RBM) and the associated leukaemia risks attributable to pelvic kilo-voltage cone beam computed tomography (kVCBCT) scans in image-guided radiation therapy (IGRT). The RBM doses of 42 patients (age 2.7-86.4 years) were calculated using Monte Carlo simulations. The trabecular spongiosa was segmented to substitute RBM rather than the whole bone. Quantitative correlations between anthropometric variables such as age, physical bone density (PBD) and RBM dose were established. Personalized leukaemia risk was evaluated using an improved Boice model which included the age-associated RBM involvement. An incremental leukaemia risk of 29%-82% (mean = 45%) was found to be associated with 40 pelvic kVCBCT scans in the subject group used in a typical external beam radiation therapy course. Higher risks were observed in children. Due to the enhanced photoelectric effect in high atomic number materials, PBD was observed to strongly affect the RBM dose. Considerable overestimations (9%-42%, mean = 28%) were observed if the whole bone doses were used as surrogates of RBM doses. The personalized estimation of RBM dose and associated leukaemia risk caused by pelvic kVCBCT scans is clinically feasible with the proposed empirical models. Higher radiogenic cancer risks are associated with repeated kVCBCT scans in IGRT of cancer patients, especially children.

The authors propose a combined scatter reduction and correction method to improve image quality in cone beam computed tomography (CBCT). The scatter kernel superposition (SKS) method has been used occasionally in previous studies. However, this method differs in that a scatter detecting blocker (SDB) was used between the X-ray source and the tested object to model the self-adaptive scatter kernel. This study first evaluates the scatter kernel parameters using the SDB, and then isolates the scatter distribution based on the SKS. The quality of image can be improved by removing the scatter distribution. The results show that the method can effectively reduce the scatter artifacts, and increase the image quality. Our approach increases the image contrast and reduces the magnitude of cupping. The accuracy of the SKS technique can be significantly improved in our method by using a self-adaptive scatter kernel. This method is computationally efficient, easy to implement, and provides scatter correction using a single scan acquisition.

Image-guided adaptive radiotherapy requires deformable image registration to map radiation dose back and forth between images. The purpose of this study is to develop a novel method to improve the accuracy of an intensity-based image registration algorithm in low-contrast regions. A computational framework has been developed in this study to improve the quality of the “demons” registration. For each voxel in the registration’s target image, the standard deviation of image intensity in a neighborhood of this voxel was calculated. A mask for high-contrast regions was generated based on their standard deviations. In the masked regions, a tetrahedral mesh was refined recursively so that a sufficient number of tetrahedral nodes in these regions can be selected as driving nodes. An elastic system driven by the displacements of the selected nodes was formulated using a finite element method (FEM) and implemented on the refined mesh. The displacements of these driving nodes were generated with the “demons” algorithm. The solution of the system was derived using a conjugated gradient method, and interpolated to generate a displacement vector field for the registered images. The FEM correction method was compared with the “demons” algorithm on the CT images of lung and prostate patients. The performance of the FEM correction relating to the “demons” registration was analyzed based on the physical property of their deformation maps, and quantitatively evaluated through a benchmark model developed specifically for this study. Compared to the benchmark model, the “demons” registration has the maximum error of 1.2 cm, which can be corrected by the FEM method to 0.4 cm, and the average error of the “demons” registration is reduced from 0.17 cm to 0.11 cm. For the CT images of lung and prostate patients, the deformation maps generated by the “demons” algorithm were found unrealistic at several places. In these places, the displacement differences between the “demons” registrations and their FEM corrections were found in the range of 0.4 cm and 1.1cm. The mesh refinement and FEM simulation were implemented in a single thread application which requires about 45 minutes of computation time on a 2.6 GH computer. This study has demonstrated that the finite element method can be integrated with intensity-based image registration algorithms to improve their registration accuracy, especially in low-contrast regions.

In this work, the suitability and performance of a mouse-size MOSFET (Mousefet) phantom is investigated for routine quality assurance (QA) of the small animal radiation research platform (SARRP). This Mousefet phantom is a simple construction consisting of five micro-MOSFETS custom integrated in a quincunx pattern within a tissue-equivalent phantom, allowing repeat/multiple QA tasks to be quickly performed in one experimental set-up. The Mousefet phantom is particularly evaluated for facilitating SARRP QA tasks which may warrant daily evaluation, including output constancy, isocenter congruency test and cone beam computed tomography (CBCT) image geometric accuracy. Results for the output constancy measurements showed a maximum daily variation of less than 2.6% for all MOSFETS, in consonance with observations from concurrent ion chamber measurements. It is also shown that the design of the Mousefet phantom allows the output check data to be used for prompt verification of beam energy and cone profile constancy. For the isocenter congruency test, it is demonstrated that the Mousefet phantom can detect 0.3 mm deviations of the CBCT isocenter from the radiation isocenter. Meanwhile, results for CBCT image geometric accuracy were consistently found to be within 2% of the expected value. Other CBCT image quality parameters could also be assessed in terms of image intensity constancy, noise and image uniformity. Overall, the results establish the Mousefet phantom as a simple and time-efficient multipurpose tool that could be employed effectively for routine QA of the SARRP.

C-arm cone-beam CT could replace preoperative multi-detector CT scans in the cardiac interventional setting. However, cardiac gating results in view angle undersampling and the small size of the detector results in projection data truncation. These problems are incompatible with conventional tomographic reconstruction algorithms. In this paper, the prior image constrained compressed sensing (PICCS) reconstruction method was adapted to solve these issues. The performance of the proposed method was compared to that of FDK, FDK with extrapolated projection data (E-FDK), and total variation-based compressed sensing. A canine projection dataset acquired using a clinical C-arm imaging system supplied realistic cardiac motion and anatomy for this evaluation. Three different levels of truncation were simulated. The relative root mean squared error and the universal image quality index were used to quantify the reconstruction accuracy. Three main conclusions were reached. (1) The adapted version of the PICCS algorithm offered the highest image quality and reconstruction accuracy. (2) No meaningful variation in performance was observed when the amount of truncation was changed. (3) This study showed evidence that accurate interior tomography with an undersampled acquisition is possible for realistic objects if a prior image with minimal artifacts is available.

This paper proposes a hybrid technique to simulate the complete chain of an oral cone beam computed tomography (CBCT) system for the study of both radiation dose and image quality. The model was developed around a 3D Accuitomo 170 unit (J Morita, Japan) with a tube potential range of 60-90 kV. The Monte Carlo technique was adopted to simulate the x-ray generation, filtration and collimation. Exact dimensions of the bow-tie filter were estimated iteratively using experimentally acquired flood images. Non-flat radiation fields for different exposure settings were mediated via 'phase spaces'. Primary projection images were obtained by ray tracing at discrete energies and were fused according to the two-dimensional energy modulation templates derived from the phase space. Coarse Monte Carlo simulations were performed for scatter projections and the resulting noisy images were smoothed by Richardson-Lucy fitting. Resolution and noise characteristics of the flat panel detector were included using the measured modulation transfer function (MTF) and the noise power spectrum (NPS), respectively. The Monte Carlo dose calculation was calibrated in terms of kerma free-in-air about the isocenter, using an ionization chamber, and was subsequently validated by comparison against the measured air kerma in water at various positions of a cylindrical water phantom. The resulting dose discrepancies were found

X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.

Flat-panel-detector X-ray cone-beam computed tomography (CBCT) is used in a rapidly increasing host of imaging applications, including image-guided surgery and radiotherapy. The purpose of the work is to investigate and evaluate image reconstruction from data collected at projection views significantly fewer than what is used in current CBCT imaging. Specifically, we carried out imaging experiments by use of a bench-top CBCT system that was designed to mimic imaging conditions in image-guided surgery and radiotherapy; we applied an image reconstruction algorithm based on constrained total-variation (TV)-minimization to data acquired with sparsely sampled view-angles; and we conducted extensive evaluation of algorithm performance. Results of the evaluation studies demonstrate that, depending upon scanning conditions and imaging tasks, algorithms based on constrained TV-minimization can reconstruct images of potential utility from a small fraction of the data used in typical, current CBCT applications. A practical implication of the study is that the optimization of algorithm design and implementation can be exploited for considerably reducing imaging effort and radiation dose in CBCT.

For decades, the heel effect has been known to cause an angular dependence of the emitted spectrum of an x-ray tube. In radiography, artifacts were observed and attributed to the heel effect. However, no problems due to the heel effect were discerned in multi-slice computed tomography (MSCT) so far. With flat-detector CT (FDCT), involving larger cone angles and different system geometries, the heel effect might cause new artifacts. These artifacts were analyzed in this paper for system geometries different from the ones widely used nowadays. Simulations and measurements were performed. Simulations included symmetric as well as asymmetric detector layouts and different x-ray tube orientations with respect to the detector plane. The measurements were performed on a micro-CT system in an asymmetric detector layout. Furthermore, an analytical correction scheme is proposed to overcome heel effect artifacts. It was shown that the type of artifact greatly depends on the orientation of the x-ray tube and also on the type of detector alignment (i.e. symmetric or different types of asymmetric alignment). Certain combinations exhibited almost no significant artifact while others greatly influenced the quality of the reconstructed images. The proposed correction scheme showed good results that were further improved when also applying a scatter correction. When designing CT systems, care should be taken when placing the tube and the detector. Orientation of the x-ray tube like in most MSCT systems seems advisable in asymmetric detector layouts. However, a different type of tube orientation can be overcome with suitable correction schemes.

Mandibular ramus thickness is one of the most important factors that must be considered while performing bilateral sagittal split osteotomy (BSSO). Unfavourable fracture or bad split could occur while performing BSSO if the mandibular ramus is thin. To the best of our knowledge, there are only a few published reports with anthropometric data about the thickness of the mandibular ramus. The objective of this study was to measure the thickness of the mandibular ramus based on cone beam computed tomography (CBCT) to be used as a reference while performing BSSO. The study subjects comprised 61 data samples of CBCT-based DICOM images which reoriented in three planes, and we measured the thickness of the mandibular ramus. The mean thickness was 8.049 + 1.205 mm for males and 8.463 + 1.358 mm for females. For 18–30-, 31–40- and 41–50-year-old patients, the mean thickness of the mandibular ramus was 8.087 + 1.29 mm, 8.176 + 1.49 mm and 8.742 + 1.04 mm, respectively. Based on the CBCT images, there were no statistically significant differences between the thicknesses of the mandibular ramus in terms of sex and age.

Four-dimensional (4D) x-ray cone-beam computed tomography (CBCT) is important for a precise radiation therapy for lung cancer. Due to the repeated use and 4D acquisition over a course of radiotherapy, the radiation dose becomes a concern. Meanwhile, the scatter contamination in CBCT deteriorates image quality for treatment tasks. In this work, we propose the use of a moving blocker (MB) during the 4D CBCT acquisition ('4D MB') and to combine motion-compensated reconstruction to address these two issues simultaneously. In 4D MB CBCT, the moving blocker reduces the x-ray flux passing through the patient and collects the scatter information in the blocked region at the same time. The scatter signal is estimated from the blocked region for correction. Even though the number of projection views and projection data in each view are not complete for conventional reconstruction, 4D reconstruction with a total-variation (TV) constraint and a motion-compensated temporal constraint can utilize both spatial gradient sparsity and temporal correlations among different phases to overcome the missing data problem. The feasibility simulation studies using the 4D NCAT phantom showed that 4D MB with motion-compensated reconstruction with 1/3 imaging dose reduction could produce satisfactory images and achieve 37% improvement on structural similarity (SSIM) index and 55% improvement on root mean square error (RMSE), compared to 4D reconstruction at the regular imaging dose without scatter correction. For the same 4D MB data, 4D reconstruction outperformed 3D TV reconstruction by 28% on SSIM and 34% on RMSE. A study of synthetic patient data also demonstrated the potential of 4D MB to reduce the radiation dose by 1/3 without compromising the image quality. This work paves the way for more comprehensive studies to investigate the dose reduction limit offered by this novel 4D MB method using physical phantom experiments and real patient data based on clinical relevant metrics.

The aim of this article is to derive and verify a mathematical formulation for the reduction of the six-dimensional (6D) positional inaccuracies of patients (lateral, longitudinal, vertical, pitch, roll and yaw) to three-dimensional (3D) linear shifts. The formulation was mathematically and experimentally tested and verified for 169 stereotactic radiotherapy patients. The mathematical verification involves the comparison of any (one) of the calculated rotational coordinates with the corresponding value from the 6D shifts obtained by cone beam computed tomography (CBCT). The experimental verification involves three sets of measurements using an ArcCHECK phantom, when (i) the phantom was not moved (neutral position: 0MES), (ii) the position of the phantom shifted by 6D shifts obtained from CBCT (6DMES) from neutral position and (iii) the phantom shifted from its neutral position by 3D shifts reduced from 6D shifts (3DMES). Dose volume histogram and statistical comparisons were made between and . The mathematical verification was performed by a comparison of the calculated and measured yaw (γ°) rotation values, which gave a straight line, Y = 1X with a goodness of fit as R 2 = 0.9982. The verification, based on measurements, gave a planning target volume receiving 100% of the dose (V100%) as 99.1 ± 1.9%, 96.3 ± 1.8%, 74.3 ± 1.9% and 72.6 ± 2.8% for the calculated treatment planning system values TPSCAL, 0MES, 3DMES and 6DMES, respectively. The statistical significance (p-values: paired sample t-test) of V100% were found to be 0.03 for the paired sample and 0.01 for . In this paper, a mathematical method to reduce 6D shifts to 3D shifts is presented. The mathematical method is verified by using well-matched values between the measured and calculated γ°. Measurements done on the ArcCHECK phantom also proved that the proposed methodology is correct. The post-correction of the table position condition introduces a minimal spatial dose delivery error in the frameless stereotactic system, using a 6D motion enabled robotic couch. This formulation enables the reduction of 6D positional inaccuracies to 3D linear shifts, and hence allows the treatment of patients with frameless stereotactic radiosurgery by using only a 3D linear motion enabled couch.