Dynamic fluence field modulation in computed tomography using multiple aperture devices

To investigate whether iterative reconstruction (IR) in cerebral CT perfusion (CTP) allows for 50% dose reduction while maintaining image quality (IQ). A total of 48 CTP examinations were reconstructed into a standard dose (150 mAs) with filtered back projection (FBP) and half-dose (75 mAs) with two strengths of IR (middle and high). Objective IQ (quantitative perfusion values, contrast-to-noise ratio (CNR), penumbra, infarct area and penumbra/infarct (P/I) index) and subjective IQ (diagnostic IQ on a four-point Likert scale and overall IQ binomial) were compared among the reconstructions. Half-dose CTP with high IR level had, compared with standard dose with FBP, similar objective (grey matter cerebral blood volume (CBV) 4.4 versus 4.3 mL/100 g, CNR 1.59 versus 1.64 and P/I index 0.74 versus 0.73, respectively) and subjective diagnostic IQ (mean Likert scale 1.42 versus 1.49, respectively). The overall IQ in half-dose with high IR level was scored lower in 26-31%. Half-dose with FBP and with the middle IR level were inferior to standard dose with FBP. With the use of IR in CTP imaging it is possible to examine patients with a half dose without significantly altering the objective and diagnostic IQ. The standard dose with FBP is still preferable in terms of subjective overall IQ in about one quarter of patients. • Computed tomography perfusion (CTP) is increasingly important in ischaemia imaging. • Radiation exposure of CTP is a drawback. • Iterative reconstruction (IR) allows reduction of radiation dose in unenhanced head CT. • CTP IR enables 50% dose reduction without altering objective and diagnostic quality.

Many technical updates have been made in multi-detector CT. To evaluate image quality and radiation dose of high-pitch second- and third-generation dual-source chest CT angiography and to assess the effects of different levels of advanced modeled iterative reconstruction (ADMIRE) in newborns and children. Chest CT angiography (70 kVp) was performed in 42 children (age 158 ± 267 days, range 1-1,194 days). We evaluated subjective and objective image quality, and radiation dose with filtered back projection (FBP) and different strength levels of ADMIRE. For comparison were 42 matched controls examined with a second-generation 128-slice dual-source CT-scanner (80 kVp). ADMIRE demonstrated improved objective and subjective image quality (P < .01). Mean signal/noise, contrast/noise and subjective image quality were 11.9, 10.0 and 1.9, respectively, for the 80 kVp mode and 11.2, 10.0 and 1.9 for the 70 kVp mode. With ADMIRE, the corresponding values for the 70 kVp mode were 13.7, 12.1 and 1.4 at strength level 2 and 17.6, 15.6 and 1.2 at strength level 4. Mean CTDIvol, DLP and effective dose were significantly lower with the 70-kVp mode (0.31 mGy, 5.33 mGy*cm, 0.36 mSv) compared to the 80-kVp mode (0.46 mGy, 9.17 mGy*cm, 0.62 mSv; P < .01). The third-generation dual-source CT at 70 kVp provided good objective and subjective image quality at lower radiation exposure. ADMIRE improved objective and subjective image quality.

The purpose of this article is to study the added value of model-based iterative reconstruction (MBIR) on metal artifact reduction on CT compared with standard filtered back projection (FBP). Ex vivo imaging was performed on several metal implants. Datasets were reconstructed with standard FBP and MBIR algorithms. The sizes of the artifacts surrounding the metal implant were recorded and compared. In vivo imaging was performed on 62 patients with metal implants. Each dataset was reconstructed with FBP and MBIR algorithms. Objective image quality was assessed by measuring the size of the artifact generated by the metal implant. Subjective image quality was graded on a 3-point scale, taking into account the visibility of the bone-metal interface, as well as the visibility of the neighboring soft tissues. Ex vivo analysis yielded a reduction of 82% in the size of the artifact when using the MBIR algorithm, compared with the FBP algorithm. The mean (SD) size of the artifacts was 1.4 ± 0.8 and 0.25 ± 0.06 cm(2) with FBP and MBIR, respectively. In vivo, the mean size of the artifacts decreased from 7.3 ± 1.5 cm(2) to 4.0 ± 0.9 cm(2) for FBP and MBIR, respectively (p = 0.012). The subjective image quality analysis showed an equal or better bone-metal interface of MBIR algorithm in 85% of cases. Visibility of the soft tissue surrounding the metal implant was determined to be equal or better in 97% of cases in which MBIR was used. This study shows that the MBIR algorithm allows a clear reduction of metal artifacts on CT images and, hence, a better analysis of the soft tissue surrounding the metal implant compared with FBP.

ObjectivesTo evaluate the diagnostic performance and image quality of an iterative model-based reconstruction (IMR) using a 100-kVp protocol for the assessment of heavily calcified coronary vessels, compared to those of filtered back projection (FBP) and hybrid iterative technique (iDose4), and also compared to those of IMR with standard 120 kVp protocol.MethodsAmong patients with Agatston scores ≥ 400 who had undergone both coronary CT angiography (CCTA) and invasive coronary angiography (ICA), age- and sex-matched patients with body mass index < 30 were retrospectively enrolled from CCTA with low-kVp protocol (100 kVp, n = 30) and with standard-kVp protocol (120 kVp, n = 30). Image data were all reconstructed with FBP, iDose4, and IMR. In each dataset, the objective and subjective image quality, and diagnostic accuracy (> 50% in luminal reduction as compared with ICA) were assessed.ResultsIMR showed better objective and subjective image quality than FBP and iDose4 in both 100 kVp and 120 kVp groups (all p < 0.05). IMR showed a significantly improved all diagnostic performance compared with FBP (p < 0.05). Compared with iDose4, IMR significantly improved positive predictive value (85.0% vs. 80.5%; p < 0.05). There was no significant difference in image quality and diagnostic performance using IMR between the 100 kVp and 120 kVp groups.Conclusions100 kVp IMR may be useful for the assessment of heavily calcified coronary vessels, providing better diagnostic performance than FBP or iDose4 at the same dose, while maintaining similar diagnostic accuracy to 120 kVp IMR.

Improving head and neck CTA with hybrid and model-based iterative reconstruction techniques

Ultra-low dose abdominal MDCT: Using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study

To evaluate the effect of low tube voltage (100 kV) combined with adaptive statistical iterative reconstruction-V (ASIR-V) on the visualization and image quality of the Adamkiewicz artery (AKA). One hundred patients were prospectively enrolled and randomly assigned into two groups (both n = 50). Group A (100 kV) was reconstructed with filtered back projection (FBP) and ASIR-V from 10% to 100% with 10% intervals. Group B (120 kV) was only reconstructed with FBP. The objective image quality was evaluated by using CT values of the aorta (CTAorta), background noise, signal-to-noise ratio of the descending aorta (SNRAorta), and contrast-to-noise ratio of the spinal cord (CNRSpinal cord). The subjective image quality and visualization scores of the AKA were assessed on a 5-point scale. CTAorta was significantly higher in Group A than in Group B (p < 0.001). When ASIR-V weights were ≥60%, significant differences were found in the background noise, SNRAorta, and CNRSpinal cord between the two groups (all p < 0.05). In Group A, compared with FBP, the subjective score gradually increased as ASIR-V increased to 80%, which decreased when ASIR-V exceeded 80%. The visualization scores of the AKA (≥60%) and the ability to detect vessel continuity (≥80%) gradually increased as the ASIR-V weights increased (p < 0.05). The effective radiation dose was reduced by about 40.36% in Group A compared to Group B. compared with conventional scanning protocol, using a combination of low tube voltage (100 kV) and 80% ASIR-V protocol could not only increase the visualization of the AKA, but also improve image quality and reduce the radiation doses.

The aims of this study were to compare a commercially available reconstruction algorithm (iDose4) with filtered back projection (FBP) in terms of image quality (IQ) for both retrospective electrocardiographically gated and prospective electrocardiographically triggered cardiac computed tomographic angiography (CCTA) protocols and to evaluate the achievable radiation dose reduction. A total cohort of 58 patients underwent either prospective CTCA or retrospective CTCA with full or reduced tube current-time product (in milliampere-second) protocol on a 64-slice multidetector computed tomographic scanner. All images were reconstructed with FBP, whereas the reduced milliampere-second images were also reconstructed using 2 levels (levels 4 and 6) of iDose4. Subjective and objective IQ was evaluated. Dose reductions of 43% in the retrospective CCTA protocol and 27% in the prospective CCTA protocol were achieved without compromising IQ. In the prospective CCTA protocol, the reduced-dose images were highly scored; thus, additional reduction of exposure settings is feasible. In the retrospective acquisition, dose reduction has led to similar IQ scores between the reduced-dose iDose4 images and the full-dose FBP images. Considering different reconstructions (FBP, iDose-L4 and -L6) of the same acquisition data, increase in iDose4 level resulted in less noisy images. A slight improvement was also noticed in all IQ indices; however, this improvement was not statistically significant for both acquisition protocols. This study demonstrated that the application of iDose at CCTA facilitates significant radiation dose reduction by maintaining diagnostic quality. The combination of iDose4 with prospective acquisition is able to significantly reduce effective dose associated with CTCA at values of approximately 2 mSv and even lower.

Image Quality Assessment in Torso Phantom Comparing Effects of Varying Automatic Current Modulation with Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction Techniques in CT

Computed tomography perfusion (CTP) and computed tomography angiography (CTA) are valuable tools for diagnosing acute ischemic stroke (AIS). It is essential to obtain high-quality CTP and CTA images in short time. This study aimed to evaluate the image quality and diagnostic performance of brain CTP and CTA images generated from CTP reconstructed by a deep learning image reconstruction (DLIR) algorithm on patients with AIS. The study prospectively enrolled 54 patients with suspected AIS undergoing non-contrast CT and CTP within 24 hours. CTP datasets were reconstructed with three levels of adaptive statistical iterative reconstruction-Veo algorithm [ASIR-V 0% with filtered back projection (FBP), ASIR-V 40%, and ASIR-V 80%] and three levels of DLIR, including low (DLIR-L), medium (DLIR-M), and high (DLIR-H). CTA images were generated using the CTP datasets at the peak arterial phase. Objective parameters including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and noise reduction rate. Subjective evaluation was assessed according to Abels scoring system. Perfusion parameters and detection accuracy for infarction core lesions were evaluated. The objective and subjective image quality of CTA images were also evaluated. All reconstructions produced similar CT values (P>0.05). With the increase of ASIR-V and DLIR reconstruction strength, image noise decreased, while SNR and CNR increased for CTP images, especially in white matter. DLIR-H, DLIR-M, and ASIR-V80% yielded higher subjective scores than did ASIR-V40% and FBP. DLIR-H provided the highest noise reduction rate and detection accuracy. No significant difference was found in conventional parameters, the volume of infarct core, or ischemic penumbra among the 6 groups (P>0.05). The objective evaluation of reconstructed CTA images was comparable in DLIR-H, DLIR-M, and ASIR-V80% (P>0.05). The subjective scores of the DLIR-H and DLIR-M images were higher than those of the other groups, especially ASIR-V40% and FBP (P<0.05). Compared with FBP and ASIR-V40%, DLIR-H, DLIR-M, and ASIR-V80% improved the overall image quality of CTP and CTA images to varying degrees. Furthermore, DLIR-H and DLIR-M showed the best performance. DLIR-H is the best choice in diagnosing AIS with improved detection accuracy for cerebral infarction. Reconstructing CTA images using CTP datasets could reduce contrast agent and radiation dose.

Model-based Iterative Reconstruction in Low-radiation-dose Computed Tomography Colonography: Preoperative Assessment in Patients with Colorectal Cancer

The paper addresses the problem of on-off spacecraft relative control in sliding mode for autonomous on-orbit servicing operations under actuator amplitude limits, action discreteness, and parametric uncertainties. The goal is to develop and assess an approach that combines sliding-mode control with modern reinforcement-learning methods tailored for resource-constrained onboard implementation. Relative motion dynamics is formulated in an orbital coordinate frame with normalized states and discretized in time. Binary actions with pulse-width modulation, subject to constraints on the thrust level, pulse duration, and duty cycle, represent the impulsive nature of actuation. We propose a combined synthesis in which the sliding-surface parameters and switching rules are tuned via proximal policy optimization within an actor-critic architecture. The actor and critic are implemented as neural networks that approximate the policy and the value function, respectively. The actor neural network takes the state vector as input information and outputs the mean and standard deviation of the parameters of the sliding mode control law. The value function penalizes both the state error and control effort, thus enabling a trade-off among the response speed, accuracy, and propellant consumption. Two uncoupled agents are designed to control spacecraft relative orbital motion in in-plane and out-of-plane directions independently. The proximal policy optimization hyperparameters are selected to ensure a trade-off among the learning time, stability, and control performance. The reinforcement-learning agents are trained and analyzed considering four cases that differ in the thrust levels and weighting matrices. The quality functional combines state deviation and thrust use penalties, thus enabling a trade-off among the response speed, accuracy, and propellant consumption. The results confirm the potential of this approach for autonomous spacecraft control under constraints and uncertainty. Compared with reported baselines, the trained agent shows superior robustness to plant-parameter uncertainty, which we attribute to the inherent robust properties of sliding-mode control. These findings have the potential to improve the efficiency and autonomy of on-orbit servicing operations.

ObjectiveTo assess the lesion conspicuity and image quality in CT evaluation of small (≤ 3 cm) hepatocellular carcinomas (HCCs) using automatic tube voltage selection (ATVS) and automatic tube current modulation (ATCM) with or without iterative reconstruction.Materials and MethodsOne hundred and five patients with 123 HCC lesions were included. Fifty-seven patients were scanned using both ATVS and ATCM and images were reconstructed using either filtered back-projection (FBP) (group A1) or sinogram-affirmed iterative reconstruction (SAFIRE) (group A2). Forty-eight patients were imaged using only ATCM, with a fixed tube potential of 120 kVp and FBP reconstruction (group B). Quantitative parameters (image noise in Hounsfield unit and contrast-to-noise ratio of the aorta, the liver, and the hepatic tumors) and qualitative visual parameters (image noise, overall image quality, and lesion conspicuity as graded on a 5-point scale) were compared among the groups.ResultsGroup A2 scanned with the automatically chosen 80 kVp and 100 kVp tube voltages ranked the best in lesion conspicuity and subjective and objective image quality (p values ranging from < 0.001 to 0.004) among the three groups, except for overall image quality between group A2 and group B (p = 0.022). Group A1 showed higher image noise (p = 0.005) but similar lesion conspicuity and overall image quality as compared with group B. The radiation dose in group A was 19% lower than that in group B (p = 0.022).ConclusionCT scanning with combined use of ATVS and ATCM and image reconstruction with SAFIRE algorithm provides higher lesion conspicuity and better image quality for evaluating small hepatic HCCs with radiation dose reduction.

This work addresses the problem of experimentally reproducing the orbital relative motion on a planar floating spacecraft simulator testbed. Floating spacecraft simulators are characterized by double-integrator dynamics on their three degrees of freedom. In this paper, the Clohessy–Wiltshire planar dynamics is scaled down, and it is emulated using an autonomous floating vehicle actuated using compressed-air thrusters. The dynamics scaling criteria are determined through the use of the Pi theorem; subsequently, the problem of accurate actuation of the equivalent transport acceleration and Coriolis acceleration is solved. Three different thrust modulation strategies (namely, pulse-width modulation, delta sigma modulation, and hybrid pulse-width delta sigma modulation) have been used to achieve an accurate conversion of the requested continuous-thrust time histories into sequences of actuated fixed-thrust pulses. The performances of the resulting system are evaluated through a set of simulations by comparing the nominal spacecraft trajectories with the correspondent equivalent floating simulator trajectories. Finally, a set of experimental results is presented.

The article investigates the task of spacecraft relative control using reactive actuators, the output of which has two states, “on” or “off”. For cases where the resolution of the thrusters does not provide an accurate approximation of linear control laws using a pulse-width thrust modulator, the possibility of applying reinforcement learning methods for direct finding of control laws that map the state vector and the on-off thruster commands has been investigated. To implement such an approach, a model of controlled relative motion of two satellites in the form of a Markov decision process was obtained. The intelligent agent is presented in the form of “actor” and “critic” neural networks, and the architecture of these modules is defined. It is proposed to use a cost function with variable weights of control actions, which allows for optimizing the number of thruster firings explicitly. To improve the control performance, it is proposed to use an extended input vector for the “actor” and “critic” neural networks of the intelligent agent, which, in addition to the state vector, also includes information about the control action on the previous control step and the control step number. To reduce the training time, the agent was pre-trained on the data obtained using conventional control algorithms. Numerical results demonstrate that the reinforcement learning methodology allows the agent to outperform the results provided by the linear controller with the pulse-width modulator in terms of control accuracy, response time, and number of thruster firings.