Commercial Computed Tomography Scanner Research Articles

Tomographic reconstruction strategies for nondestructive testing with a commercial CT scanner

In this work, a framework was developed to access and process raw data from a commercial X-ray Computed Tomography (CT) scanner for research purposes. Our method requires vendor-provided binaries to convert the data to a readable format and also to remove the effect of proprietary beam hardening preprocessing. As a result, custom reconstruction techniques, including beam-hardening corrections algorithms, can be applied. Small region-of-interest CT imaging techniques and different backprojection algorithms were investigated to improve image quality (spatial resolution, noise) with an in-house iterative reconstruction algorithm. For a reconstruction matrix of 512 pixels × 512 pixels, processing times of approximately 2.5 s per slice were obtained using a set of 8 x GPUs. With this framework, high-quality images of high density samples (e.g., minerals) can be obtained with reduced truncation-induced blurring, free of artifacts stemming from the reconstruction process and reduced beam-hardening artifacts.

Photon counting x-ray detectors as scatter probes.

Direct conversion x-ray Photon Counting Detectors (PCD) are posed to play a vital role in future medical imaging devices such as Computed Tomography (CT) scanners. PCD are expected to improve current CT technology on several fronts, such as resolution, dose utilization, and spectral performance. However, they are not readily expected to improve the handling of object scatter, one of the major sources of image artifacts in CT technology. We explore a potential method for obtaining in-situ object scatter estimation using the same PCD array used in the x-ray imaging system, such as in computed tomography. This unexpected benefit of using PCD has the potential to improve the image quality by providing better input into the scatter estimation and correction algorithms used in image reconstruction. In CT scanners the primary method for rejecting scatter signal originating from the scanned object relies on placing anti-scatter grids (ASG) close to the detector plane. This remains the case when transitioning to using PCD instead of energy integration detectors in CT. However, the combination of PCD and ASG opens a possibility to use some of the unique properties of PCD, namely, very low noise and coincidence counters to obtain, in addition to the attenuation data, a simultaneous and instantaneous estimate of the scatter signal reaching every detector element. When a small air gap is introduced between the ASG and the detector surface, the scatter radiation with large angular distribution has a greater probability of producing charge sharing events that can be detected by a coincidence counter. In this work we demonstrate the feasibility of such an approach in a tabletop experiment using PCD detector that lacks coincidence counting capability, instead we use the spectral signature of split charge events as proxy to coincidence counting. For this purpose, we first demonstrate the spectral impact of ASG misalignment using the same experimental setup. In addition, we perform a separate tabletop scattering experiment from a narrow column of water that demonstrates another potential use of the low noise capabilities of PCDs. We measured and quantified the high sensitivity of the spectral response to ASG alignment on the PCD detector pixel array, we found that the probability of energy misregistration of 60keV photons can increase by up to a factor of 3 when the ASG is poorly aligned. We then leveraged these results to obtain an estimate on the expected increase in coincidence counts for a wide range of scatter-to-primary (SPR) ratio and find a good match with expectations from a geometric modeling of the system, where the expected increase in coincidences was of the order of the SPR. Finally, the low noise detector also allowed us to measure the real space scatter signal associated with the coherent molecular form factor of water, revealing the ring-shaped scatter signal with an energy dependent distribution that was well captured by calculation. The advent of PCD detectors and their imminent use in commercial CT scanners opens new and exciting possibilities for utilizing PCD detectors in unexpected ways. In this proof-of-concept study, we showed how charge sharing, a spectral information degrading effect, can instead be used to obtain in-situ scatter estimation. We also demonstrated the PCD ability to perform extremely sensitive measurements using affordable benchtop setup for investigations normally reserved for synchrotron facilities.

Harmonizing CT Images via Physics-based Deep Neural Networks.

The rendition of medical images influences the accuracy and precision of quantifications. Image variations or biases make measuring imaging biomarkers challenging. The objective of this paper is to reduce the variability of computed tomography (CT) quantifications for radiomics and biomarkers using physics-based deep neural networks (DNNs). With the proposed framework, it is possible to harmonize the different renditions of a single CT scan (with variations in reconstruction kernel and dose) into an image that is in close agreement with the ground truth. To this end, a generative adversarial network (GAN) model was developed where the generator is informed by the scanner's modulation transfer function (MTF). To train the network, a virtual imaging trial (VIT) platform was used to acquire CT images, from a set of forty computational models (XCAT) serving as the patient model. Phantoms with varying levels of pulmonary disease, such as lung nodules and emphysema, were used. We scanned the patient models with a validated CT simulator (DukeSim) modeling a commercial CT scanner at 20 and 100 mAs dose levels and then reconstructed the images by twelve kernels representing smooth to sharp kernels. An evaluation of the harmonized virtual images was conducted in four different ways: 1) visual quality of the images, 2) bias and variation in density-based biomarkers, 3) bias and variation in morphological-based biomarkers, and 4) Noise Power Spectrum (NPS) and lung histogram. The trained model harmonized the test set images with a structural similarity index of 0.95±0.1, a normalized mean squared error of 10.2±1.5%, and a peak signal-to-noise ratio of 31.8±1.5 dB. Moreover, emphysema-based imaging biomarkers of LAA-950 (-1.5±1.8), Perc15 (13.65±9.3), and Lung mass (0.1±0.3) had more precise quantifications.

Calibration of 3D scan trajectories for an industrial computed tomography setup with 6-DOF object manipulator system using a single sphere

In industrial x-ray computed tomography (CT), the application of more complex scan paths in comparison to the typical circular trajectory ( rotation of the measurement object) can extend the potential of CT. One way to enable such 3D scan trajectories is to use a 6-degrees-of-freedom (DOF) object manipulator system. In our case, a hexapod is mounted on top of the rotary table of a commercial CT scanner. This allows for adaptive tilting of the measurement object during the scan. For high accuracy, the geometry calibration of such setups is typically done using the x-ray projections of a calibrated multi-sphere object. Contrary to this, here, we demonstrate a procedure that is based on only a single sphere and can therefore experimentally be implemented with low effort. Using the intrinsic geometry parameters of the CT device as prior information, the hexapod coordinate system with respect to the CT machine coordinate system is determined by means of a one-step optimization approach. The resulting parameters are used to calculate projection matrices that enable the volume reconstruction for 3D scan trajectories. The method is validated using simulated x-ray images and experimental investigations including dimensional measurements. For the used setup, geometric measurement results for 3D scan trajectories that are calibrated with the presented method show in sum increased errors compared to the circular scans. A limited pose accuracy of the manipulator system is discussed as a potential cause. The results nevertheless indicate that the presented method is generally feasible for dimensional CT measurements provided that the pose accuracy is sufficient. The calibration procedure can therefore be a low-cost and easier to implement alternative compared to trajectory calibration methods based on multi-sphere objects, but with a tendency towards lower measurement accuracy. The methodology can in principle be transferred to different setups with 6-DOF manipulator systems, e.g. C-arm CT devices with a robot arm.

Simulated design optimization of a prototype solid tank optical CT scanner for 3D radiation dosimetry

Optical computed tomography (CT) is one of the leading modalities for imaging gel dosimeters. There exist many prototype designs, as well as some commercial optical CT scanners that have showcased the value that gel dosimeters can provide to improve 3D dose verification for radiation treatments. However, due to factors including image accuracy, scan time, or demanding setup and maintenance there is currently no single scanner that has become a ubiquitous staple in a clinical setting. In this work, a prototype solid tank optical CT scanner is proposed that minimizes the need for a refractive index bath commonly found in optical CT systems. In addition to the design proposal, a ray-path simulator was created to optimize the design such that the solid tank geometry improves light collection across the detector array, maximizes the volume of the dosimeter scanned, and maximizes the dynamic range of the scanner.

Complex 3D scan trajectories for industrial cone-beam computed tomography using a hexapod

Industrial x-ray computed tomography (CT) represents an established measurement technique in the field of nondestructive testing and dimensional metrology. However, the measurement accuracy is sometimes limited by measurement artifacts that cannot be avoided using a standard circular scan trajectory. This problem can be addressed with the aid of flexible 3D trajectories, but up to date, the application of these is mainly restricted to special CT devices using robot arms. In this paper, we present results using a hexapod as an additional positioning system in a commercial industrial CT scanner. In addition to the 360∘ rotation, task-specific tilting of the part during the scan is possible in this way. We used and adapted geometry calibration procedures based on a multi-sphere reference object to enable reconstruction with high accuracy. Using a demonstrator test fixture with high absorbing elements, we show that severe metal and truncation artifacts can be avoided for a region-of-interest scan. Furthermore, cone-beam artifacts, which are inherent to circular scan trajectories, can be reduced significantly. Using measurement objects that can be measured well with a circular trajectory, we found that applying a 3D trajectory leads to dimensional measurement deviations in the same range or even lower than those of a circular trajectory. This suggests that the pose repeatability of the hexapod is sufficient to perform complex scan paths without general loss of accuracy. The obtained results could be relevant for end users of conventional CT scanners, as upgrading existing devices is in principle possible. The presented investigations form the basis for the application of trajectory optimization algorithms.

Incorporation of residual attention modules into two neural networks for low-dose CT denoising.

The low-dose computed tomography (CT) imaging can reduce the damage caused by x-ray radiation to the human body. However, low-dose CT images have a different degree of artifacts than conventional CT images, and their resolution is lower than that of conventional CT images, which can affect disease diagnosis by clinicians. Therefore, methods for noise-level reduction and resolution improvement in low-dose CT images have inevitably become a research hotspot in the field of low-dose CT imaging. In this paper, residual attention modules (RAMs) are incorporated into the residual encoder-decoder convolutional neural network (RED-CNN) and generative adversarial network with Wasserstein distance (WGAN) to learn features that are beneficial to improving the performances of denoising networks, and developed models are denoted as RED-CNN-RAM and WGAN-RAM, respectively. In detail, RAM is composed of a multi-scale convolution module and an attention module built on the residual network architecture, where the attention module consists of a channel attention module and a spatial attention module. The residual network architecture solves the problem of network degradation with increased network depth. The function of the attention module is to learn which features are beneficial to reduce the noise level of low-dose CT images to reduce the loss of detail in the final denoising images, which is also the key point of the proposed algorithms. To develop a robust network for low-dose CT image denoising, multidose-level torso phantom images provided by a cooperating equipment vendor are used to train the network, which can improve the network's adaptability to clinical application. In addition, a clinical dataset is used to test the network's migration capabilities and clinical applicability. The experimental results demonstrate that these proposed networks can effectively remove noise and artifacts from multidose CT scans. Subjective and objective analyses of multiple groups of comparison experiments show that the proposed networks achieve good noise suppression performance while preserving the image texture details. In this study, two deep learning network models are developed using multidose-level CT images acquired from a commercial spiral CT scanner. The two network models can reduce and even remove streaking artifacts, and noise from low-dose CT images confirms the effectiveness of the proposed algorithms.

Validation of synthesized normal-resolution image data generated from high-resolution acquisitions on a commercial CT scanner.

To validate a normal-resolution (NR) simulation (NRsim) algorithm that uses high-resolution (HR) or super-high resolution (SHR) acquisitions on a commercial HR computed tomography (CT) scanner by comparing image quality between NRsim-generated images and actual NR images. NRsim is intended to allow direct comparison between normal-resolution CT and HR/SHR reconstructions in clinical investigations, without repeating exams. The Aquilion Precision CT (Canon Medical Systems Corporation) HR CT scanner has three resolution modes resulting from detector binning in the channel (x-y) and row (z) directions. For NR, each detector element is 0.5mm×0.5mm along the channel and row directions, 0.25mm×0.5mm for HR, and 0.25mm×0.25mm for SHR. The NRsim algorithm simulates NR acquisitions from HR or SHR acquisitions (termed NRHR and NRSHR , respectively) by downsampling the pre-log raw data in the channel direction for the HR acquisitions and in the channel and row direction for the SHR acquisition. The downsampled data are then reconstructed using the same process as NR. The axial modulation transfer function (MTF), slice sensitivity profile (SSP), and CT number accuracy were measured using the Catphan 600 phantom, and the three-dimensional noise power spectrum (NPS) was measured in water-equivalent phantoms for standard protocols across a range of size-specific dose estimates (SSDE): head (6.2-29.8mGy), lung (2.2-18.2mGy), and body (5.6-19.4mGy). The MTF and NPS measurements were combined to estimate low-contrast detectability (LCD) using a non-prewhitening model observer with an eye filter for a 5-mm disk with 10HU contrast. All metrics were compared for NR, NRHR , and NRSHR images reconstructed using filtered back projection (FBP) and an iterative reconstruction algorithm (AIDR3D). We chose a 15% error threshold as a reasonable definition of success for NRsim when compared against actual NR based on published studies showing that a just-noticeable difference in image noise level for human observers is typically <15%. The axial MTF and SSPs for NRsim were in good agreement with NR demonstrated by a maximum difference of 5.1% for the MTF at 10% and 50% across materials (air, Teflon, LDPE, and polystyrene) and a maximum SSP difference of 2.2%. Noise magnitude differences were within 15% across the SSDE levels with the exception of below 4.5mGy for the lung protocol with FBP. The relative RMSE of normalized NPS comparisons were all <15%. Differences in CT numbers for NRsim reconstructions were within 2HU of NR. LCD for NRsim was within 15% of NR with the exception of NRSHR for the lung protocol SSDE levels below 3.7mGy with FBP. NRsim, an algorithm for simulating NR acquisitions using HR and SHR raw data, was introduced and shown to generate images with spatial resolution, noise, HU accuracy, and LCD largely equivalent to scans acquired using an actual NR acquisition. At SSDE levels below ~5mGy for the lung protocol, differences in noise magnitude and LCD for NRSHR were >15% which defines a region where NRsim degrades due to contributions from electronic noise.

Noise and spatial resolution properties of a commercially available deep learning-based CT reconstruction algorithm.

To characterize the noise and spatial resolution properties of a commercially available deep learning-based computed tomography (CT) reconstruction algorithm. Two phantom experiments were performed. The first used a multisized image quality phantom (Mercury v3.0, Duke University) imaged at five radiation dose levels (CTDIvol : 0.9, 1.2, 3.6, 7.0, and 22.3mGy) with a fixed tube current technique on a commercial CT scanner (GE Revolution CT). Images were reconstructed with conventional (FBP), iterative (GE ASiR-V), and deep learning-based (GE True Fidelity) reconstruction algorithms. Noise power spectrum (NPS), high-contrast (air-polyethylene interface), and intermediate-contrast (water-polyethylene interface) task transfer functions (TTF) were measured for each dose level and phantom size and summarized in terms of average noise frequency (fav ) and frequency at which the TTF was reduced to 50% (f50% ), respectively. The second experiment used a custom phantom with low-contrast rods and lung texture sections for the assessment of low-contrast TTF and noise spatial distribution. The phantom was imaged at five dose levels (CTDIvol : 1.0, 2.1, 3.0, 6.0, and 10.0mGy) with 20 repeated scans at each dose, and images reconstructed with the same reconstruction algorithms. The local noise stationarity was assessed by generating spatial noise maps from the ensemble of repeated images and computing a noise inhomogeneity index, , following AAPM TG233 methods. All measurements were compared among the algorithms. Compared to FBP, noise magnitude was reduced on average (± one standard deviation) by 74±6% and 68±4% for ASiR-V (at "100%" setting) and True Fidelity (at "High" setting), respectively. The noise texture from ASiR-V had substantially lower noise frequency content with 55±4% lower NPS fav compared to FBP while True Fidelity had only marginally different noise frequency content with 9±5% lower NPS fav compared to FBP. Both ASiR-V and True Fidelity demonstrated locally nonstationary noise in a lung texture background at all radiation dose levels, with higher noise near high-contrast edges of vessels and lower noise in uniform regions. At the 1.0mGy dose level values were 314% and 271% higher in ASiR-V and True Fidelity compared to FBP, respectively. High-contrast spatial resolution was similar between all algorithms for all dose levels and phantom sizes (<3% difference in TTF f50% ). Compared to FBP, low-contrast spatial resolution was lower for ASiR-V and True Fidelity with a reduction of TTF f50% of up to 42% and 36%, respectively. The deep learning-based CT reconstruction demonstrated a strong noise magnitude reduction compared to FBP while maintaining similar noise texture and high-contrast spatial resolution. However, the algorithm resulted in images with a locally nonstationary noise in lung textured backgrounds and had somewhat degraded low-contrast spatial resolution similar to what has been observed in currently available iterative reconstruction techniques.

Dose Reduction for Sinus and Temporal Bone Imaging Using Photon-Counting Detector CT With an Additional Tin Filter.

The aim of this study was to quantitatively demonstrate radiation dose reduction for sinus and temporal bone examinations using high-resolution photon-counting detector (PCD) computed tomography (CT) with an additional tin (Sn) filter. A multienergy CT phantom, an anthropomorphic head phantom, and a cadaver head were scanned on a research PCD-CT scanner using ultra-high-resolution mode at 100-kV tube potential with an additional tin filter (Sn-100 kV) and volume CT dose index of 10 mGy. They were also scanned on a commercial CT scanner with an energy-integrating detector (EID) following standard clinical protocols. Thirty patients referred to clinically indicated sinus examinations, and two patients referred to temporal bone examinations were scanned on the PCD-CT system after their clinical scans on an EID-CT. For the sinus cohort, PCD-CT scans were performed using Sn-100 kV at 4 dose levels at 10 mGy (n = 9), 8 mGy (n = 7), 7 mGy (n = 7), and 6 mGy (n = 7), and the clinical EID-CT was performed at 120 kV and 13.7 mGy (mean CT volume dose index). For the temporal bone scans, PCD-CT was performed using Sn-100 kV (10.1 mGy), and EID-CT was performed at 120 kV and routine clinical dose (52.6 and 66 mGy). For both PCD-CT and EID-CT, sinus images were reconstructed using H70 kernel at 0.75-mm slice thickness, and temporal bone images were reconstructed using a U70 kernel at 0.6-mm slice thickness. In addition, iterative reconstruction with a dedicated sharp kernel (V80) was used to obtain high-resolution PCD-CT images from a sinus patient scan to demonstrate improved anatomic delineation. Improvements in spatial resolution from the dedicated sharp kernel was quantified using modulation transfer function measured with a wire phantom. A neuroradiologist assessed the H70 sinus images for visualization of critical anatomical structures in low-dose PCD-CT images and routine-dose EID-CT images using a 5-point Likert scale (structural detection obscured and poor diagnostic confidence, score = 1; improved anatomic delineation and diagnostic confidence, score = 5). Image contrast and noise were measured in representative regions of interest and compared between PCD-CT and EID-CT, and the noise difference between the 2 acquisitions was used to estimate the dose reduction in the sinus and temporal bone patient cohorts. The multienergy phantom experiment showed a noise reduction of 26% in the Sn-100 kV PCD-CT image, corresponding to a total dose reduction of 56% compared with EID-CT (clinical dose) without compromising image contrast. The PCD-CT images from the head phantom and the cadaver scans demonstrated a dose reduction of 67% and 83%, for sinus and temporal bone examinations, respectively, compared with EID-CT. In the sinus cohort, PCD-CT demonstrated a mean dose reduction of 67%. The 10- and 8-mGy sinus patient images from PCD-CT were significantly superior to clinical EID-CT for visualization of critical sinus structures (median score = 5 ± 0.82 and P = 0.01 for lesser palatine foramina, median score = 4 ± 0.68 and P = 0.039 for nasomaxillary sutures, and median score = 4 ± 0.96 and P = 0.01 for anterior ethmoid artery canal). The 6- and 7-mGy sinus patient images did not show any significant difference between PCD-CT and EID-CT. In addition, V80 (sharp kernel, 10% modulation transfer function = 18.6 cm) PCD-CT images from a sinus patient scan increased the conspicuity of nasomaxillary sutures compared with the clinical EID-CT images. The temporal bone patient images demonstrated a dose reduction of up to 85% compared with clinical EID-CT images, whereas visualization of inner ear structures such as the incudomalleolar joint were similar between EID-CT and PCD-CT. Phantom and cadaver studies demonstrated dose reduction using Sn-100 kV PCD-CT compared with current clinical EID-CT while maintaining the desired image contrast. Dose reduction was further validated in sinus and temporal bone patient studies. The ultra-high resolution capability from PCD-CT allowed improved anatomical delineation for sinus imaging compared with current clinical standard.

Resolution characterization of a silicon-based, photon-counting computed tomography prototype capable of patient scanning.

Photon-counting detectors are expected to bring a range of improvements to patient imaging with x-ray computed tomography (CT). One is higher spatial resolution. We demonstrate the resolution obtained using a commercial CT scanner where the original energy-integrating detector has been replaced by a single-slice, silicon-based, photon-counting detector. This prototype constitutes the first full-field-of-view silicon-based CT scanner capable of patient scanning. First, the pixel response function and focal spot profile are measured and, combining the two, the system modulation transfer function is calculated. Second, the prototype is used to scan a resolution phantom and a skull phantom. The resolution images are compared to images from a state-of-the-art CT scanner. The comparison shows that for the prototype are detectable with the same clarity as on the reference scanner at equal dose and reconstruction grid, with more line pairs visible with increasing dose and decreasing image pixel size. The high spatial resolution remains evident in the anatomy of the skull phantom and is comparable to that of other photon-counting CT prototypes present in the literature. We conclude that the deep silicon-based detector used in our study could provide improved spatial resolution in patient imaging without increasing the x-ray dose.

Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks

In recent years, health risks concerning high-dose x-ray radiation have become a major concern in dental computed tomography (CT) examinations. Therefore, adopting low-dose computed tomography (LDCT) technology has become a major focus in the CT imaging field. One of these LDCT technologies is downsampling data acquisition during low-dose x-ray imaging processes. However, reducing the radiation dose can adversely affect CT image quality by introducing noise and artifacts in the resultant image that can compromise diagnostic information. In this paper, we propose an artifact correction method for downsampling CT reconstruction based on deep learning. We used clinical dental CT data with low-dose artifacts reconstructed by conventional filtered back projection (FBP) as inputs to a deep neural network and corresponding high-quality labeled normal-dose CT data during training. We trained a generative adversarial network (GAN) with Wasserstein distance (WGAN) and mean squared error (MSE) loss, called m-WGAN, to remove artifacts and obtain high-quality CT dental images in a clinical dental CT examination environment. The experimental results confirmed that the proposed algorithm effectively removes low-dose artifacts from dental CT scans. In addition, we showed that the proposed method is efficient for removing noise from low-dose CT scan images compared to existing approaches. We compared the performances of the general GAN, convolutional neural networks, and m-WGAN. Through quantitative and qualitative analysis of the results, we concluded that the proposed m-WGAN method resulted in better artifact correction performance preserving the texture in dental CT scanning. The image quality evaluation metrics indicated that the proposed method effectively improves image quality when used as a postprocessing technique for dental CT images. To the best of our knowledge, this work is the first deep learning architecture used with a commercial cone-beam dental CT scanner. The artifact correction performance was rigorously evaluated and demonstrated to be effective. Therefore, we believe that the proposed algorithm represents a new direction in the research area of low-dose dental CT artifact correction.

Stray light in cone beam optical computed tomography: III. Evaluation of a redesigned large-volume commercial scanner based on a convergent light source

Optical cone beam computed tomography (CT), using a digital camera to acquire 2D projection images, provides a fast, mechanically simple method for 3D radiation dosimetry. However, original cone beam designs had poor accuracy as a result of considerable scatter/stray light reaching the camera. Previously, our group presented a redesigned convergent light source for optical cone beam CT that considerably reduced stray light contribution and improved accuracy (Dekker et al 2016 Phys. Med. Biol. 61 2910). Here, we performed an evaluation of a newly updated commercial optical cone beam CT scanner (VistaTM, ModusQA, London, Canada) based on that design. Two different light source configurations were examined: the manufacturer’s default configuration which uses a 10 cm wide, 5 cm high diffuser light source, and a smaller, 1.5 cm diameter diffuser light source that more closely aligns with our previously described design. We imaged large volume (15 cm diameter cylinders) absorbing and scattering solution phantoms as well as a 1.25 cm diameter absorber placed within 15 cm diameter gel-like scattering phantom. Optical CT reconstructions were compared against narrow-beam measurements of attenuation made by placing an aperture in the optical CT system. Our results show that considerable stray light is present when using the manufacturer’s default configuration, as cupping artifacts and large (⩾10%) discrepancies between optical CT and narrow-beam attenuation measurements occur when imaging scattering phantoms. However, when imaging is performed using the 1.5 cm diameter source, optical CT measurements agree with narrow-beam measurements within ∼3% for both absorbing and scattering objects, as well as the small absorber in a scattering medium. Using this light source will require higher optical quality vessels than are currently provided by the manufacturer.

Breast dose reduction with organ-based, wide-angle tube current modulated CT.

This study aimed to estimate the organ dose reduction potential for organ-dose-based tube current modulated (ODM) thoracic computed tomography (CT) with a wide dose reduction arc. Twenty-one computational anthropomorphic phantoms (XCAT) were used to create a virtual patient population with clinical anatomic variations. The phantoms were created based on patient images with normal anatomy (age range: 27 to 66 years, weight range: 52.0 to 105.8kg). For each phantom, two breast tissue compositions were simulated: [Formula: see text] and [Formula: see text] (glandular-to-adipose ratio). A validated Monte Carlo program (PENELOPE, Universitat de Barcelona, Spain) was used to estimate the organ dose for standard tube current modulation (TCM) (SmartmA, GE Healthcare) and ODM (GE Healthcare) for a commercial CT scanner (Revolution, GE Healthcare) using a typical clinical thoracic CT protocol. Both organ dose and [Formula: see text]-to-organ dose conversion coefficients ([Formula: see text] factors) were compared between TCM and ODM. ODM significantly reduced all radiosensitive organ doses ([Formula: see text]). The breast dose was reduced by [Formula: see text]. For [Formula: see text] factors, organs in the anterior region (e.g., thyroid and stomach) exhibited substantial decreases, and the medial, distributed, and posterior region saw either an increase of less than 5% or no significant change. ODM significantly reduced organ doses especially for radiosensitive superficial anterior organs such as the breasts.

Upper limits of the photon fluence rate on CT detectors: Case study on a commercial scanner.

The highest photon fluence rate that a computed tomography (CT) detector must be able to measure is an important parameter. The authors calculate the maximum transmitted fluence rate in a commercial CT scanner as a function of patient size for standard head, chest, and abdomen protocols. The authors scanned an anthropomorphic phantom (Kyoto Kagaku PBU-60) with the reference CT protocols provided by AAPM on a GE LightSpeed VCT scanner and noted the tube current applied with the tube current modulation (TCM) system. By rescaling this tube current using published measurements on the tube current modulation of a GE scanner [N. Keat, "CT scanner automatic exposure control systems," MHRA Evaluation Report 05016, ImPACT, London, UK, 2005], the authors could estimate the tube current that these protocols would have resulted in for other patient sizes. An ECG gated chest protocol was also simulated. Using measured dose rate profiles along the bowtie filters, the authors simulated imaging of anonymized patient images with a range of sizes on a GE VCT scanner and calculated the maximum transmitted fluence rate. In addition, the 99th and the 95th percentiles of the transmitted fluence rate distribution behind the patient are calculated and the effect of omitting projection lines passing just below the skin line is investigated. The highest transmitted fluence rates on the detector for the AAPM reference protocols with centered patients are found for head images and for intermediate-sized chest images, both with a maximum of 3.4 ⋅ 10(8) mm(-2) s(-1), at 949 mm distance from the source. Miscentering the head by 50 mm downward increases the maximum transmitted fluence rate to 5.7 ⋅ 10(8) mm(-2) s(-1). The ECG gated chest protocol gives fluence rates up to 2.3 ⋅ 10(8) - 3.6 ⋅ 10(8) mm(-2) s(-1) depending on miscentering. The fluence rate on a CT detector reaches 3 ⋅ 10(8) - 6 ⋅ 10(8) mm(-2) s(-1) in standard imaging protocols, with the highest rates occurring for ECG gated chest and miscentered head scans. These results will be useful to developers of CT detectors, in particular photon counting detectors.

SU‐G‐IeP3‐04: Effective Dose Measurements in Fast Kvp Switch Dual Energy Computed Tomography

Purpose:The objective of this study was two‐fold: (a) to test a new approach to approximating organ dose by using the effective energy of the combined 80kV/140kV beam in dual‐energy (DE) computed tomography (CT), and (b) to derive the effective dose (ED) in the abdomen‐pelvis protocol in DECT.Methods:A commercial dual energy CT scanner was employed using a fast‐kV switch abdomen/pelvis protocol alternating between 80 kV and 140 kV. MOSFET detectors were used for organ dose measurements. First, an experimental validation of the dose equivalency between MOSFET and ion chamber (as a gold standard) was performed using a CTDI phantom. Second, the ED of DECT scans was measured using MOSFET detectors and an anthropomorphic phantom. For ED calculations, an abdomen/pelvis scan was used using ICRP 103 tissue weighting factors; ED was also computed using the AAPM Dose Length Product (DLP) method and compared to the MOSFET value.Results:The effective energy was determined as 42.9 kV under the combined beam from half‐value layer (HVL) measurement. ED for the dual‐energy scan was calculated as 16.49 ± 0.04 mSv by the MOSFET method and 14.62 mSv by the DLP method.Conclusion:Tissue dose in the center of the CTDI body phantom was 1.71 ± 0.01 cGy (ion chamber) and 1.71 ± 0.06 (MOSFET) respectively; this validated the use of effective energy method for organ dose estimation. ED from the abdomen‐pelvis scan was calculated as 16.49 ± 0.04 mSv by MOSFET and 14.62 mSv by the DLP method; this suggests that the DLP method provides a reasonable approximation to the ED.

Chapter 1 - Computed tomography imaging and angiography – principles

The evaluation of patients with diverse neurologic disorders was forever changed in the summer of 1973, when the first commercial computed tomography (CT) scanners were introduced. Until then, the detection and characterization of intracranial or spinal lesions could only be inferred by limited spatial resolution radioisotope scans, or by the patterns of tissue and vascular displacement on invasive pneumoencaphalography and direct carotid puncture catheter arteriography. Even the earliest-generation CT scanners - which required tens of minutes for the acquisition and reconstruction of low-resolution images (128×128 matrix) - could, based on density, noninvasively distinguish infarct, hemorrhage, and other mass lesions with unprecedented accuracy. Iodinated, intravenous contrast added further sensitivity and specificity in regions of blood-brain barrier breakdown. The advent of rapid multidetector row CT scanning in the early 1990s created renewed enthusiasm for CT, with CT angiography largely replacing direct catheter angiography. More recently, iterative reconstruction postprocessing techniques have made possible high spatial resolution, reduced noise, very low radiation dose CT scanning. The speed, spatial resolution, contrast resolution, and low radiation dose capability of present-day scanners have also facilitated dual-energy imaging which, like magnetic resonance imaging, for the first time, has allowed tissue-specific CT imaging characterization of intracranial pathology.

Experimental Comparison of Continuous-Wave and Frequency-Domain Fluorescence Tomography in a Commercial Multi-Modal Scanner.

The performance evaluation of a variety of small animal tomography measurement approaches and algorithms for recovery of fluorescent absorption cross section has not been conducted. Herein, we employed an intensified CCD system installed in a commercial small animal CT (Computed Tomography) scanner to compare image reconstructions from time-independent, continuous wave (CW) measurements and from time-dependent, frequency domain (FD) measurements in a series of physical phantoms specifically designed for evaluation. Comparisons were performed as a function of (1) number of projections, (2) the level of preprocessing filters used to improve the signal-to-noise ratio (SNR), (3) endogenous heterogeneity of optical properties, as well as in the cases of (4) two fluorescent targets and (5) a mouse-shaped phantom. Assessment of quantitative recovery of fluorescence absorption cross section was performed using a fully parallel, regularization-free, linear reconstruction algorithm with diffusion approximation (DA) and high order simplified spherical harmonics ( SPN) approximation to the radiative transport equation (RTE). The results show that while FD measurements may result in superior image reconstructions over CW measurements, data acquisition times are significantly longer, necessitating further development of multiple detector/source configurations, improved data read-out rates, and detector technology. FD measurements with SP3 reconstructions enabled better quantitative recovery of fluorescent target strength, but required increased computational expense. Despite the developed parallel reconstruction framework being able to achieve more than 60 times speed increase over sequential implementation, further development in faster parallel acceleration strategies for near-real time and real-time image recovery and more precise forward solution is necessary.

Detection of the spatial accuracy of a magnetic resonance and surgical computed tomography scanner in the region of surgical interest

In image-guided surgeries (IGSs) and radiology, images are the main source of information. As image data provide the differentiation between normal and abnormal tissues in the human, the images need to be reliable and they need to provide accurate spatial representation of the patient. This research concentrates on the accuracy assessment of IGS devices in general and then specifically on the spatial accuracy of a common magnetic resonance (MR) imager and a mobile three-dimensional surgical computed tomography (CT) scanner. The accuracy assessment tool had been designed to be universal and to enable its use in the hospital setting. In this study, it was used in detecting the spatial accuracy of a commercial surgical CT scanner, the O-arm, and a 1.5-T MR imager. The results show the tendency of magnetic resonance imaging to produce slight decreases in spatial accuracy toward the fringes of the images from the isocenter. Furthermore, the results indicate that the accuracy of both scanners was within pixel size and thus highly accurate in the region of surgical interest of this study.

A stoichiometric calibration method for dual energy computed tomography

The accuracy of radiotherapy dose calculation relies crucially on patient composition data. The computed tomography (CT) calibration methods based on the stoichiometric calibration of Schneider et al (1996 Phys. Med. Biol. 41 111–24) are the most reliable to determine electron density (ED) with commercial single energy CT scanners. Along with the recent developments in dual energy CT (DECT) commercial scanners, several methods were published to determine ED and the effective atomic number (EAN) for polyenergetic beams without the need for CT calibration curves. This paper intends to show that with a rigorous definition of the EAN, the stoichiometric calibration method can be successfully adapted to DECT with significant accuracy improvements with respect to the literature without the need for spectrum measurements or empirical beam hardening corrections. Using a theoretical framework of ICRP human tissue compositions and the XCOM photon cross sections database, the revised stoichiometric calibration method yields Hounsfield unit (HU) predictions within less than ±1.3 HU of the theoretical HU calculated from XCOM data averaged over the spectra used (e.g., 80 kVp, 100 kVp, 140 kVp and 140/Sn kVp). A fit of mean excitation energy (I-value) data as a function of EAN is provided in order to determine the ion stopping power of human tissues from ED–EAN measurements. Analysis of the calibration phantom measurements with the Siemens SOMATOM Definition Flash dual source CT scanner shows that the present formalism yields mean absolute errors of (0.3 ± 0.4)% and (1.6 ± 2.0)% on ED and EAN, respectively. For ion therapy, the mean absolute errors for calibrated I-values and proton stopping powers (216 MeV) are (4.1 ± 2.7)% and (0.5 ± 0.4)%, respectively. In all clinical situations studied, the uncertainties in ion ranges in water for therapeutic energies are found to be less than 1.3 mm, 0.7 mm and 0.5 mm for protons, helium and carbon ions respectively, using a generic reconstruction algorithm (filtered back projection). With a more advanced method (sinogram affirmed iterative technique), the values become 1.0 mm, 0.5 mm and 0.4 mm for protons, helium and carbon ions, respectively. These results allow one to conclude that the present adaptation of the stoichiometric calibration yields a highly accurate method for characterizing tissue with DECT for ion beam therapy and potentially for photon beam therapy.