State-of-the-art mobile head CT scanner delivers nearly the same image quality as a conventional stationary CT scanner.

The use of mobile head CT scanners in the neurointensive care unit (NICU) saves time for patients and NICU staff and can reduce transport-related mishaps, but the reduced image quality of previous mobile scanners has prevented their widespread clinical use. This study compares the image quality of SOMATOM On.Site (Siemens Healthineers, Erlangen, Germany), a state-of-the-art mobile head CT scanner, and a conventional 64-slice stationary CT scanner. The study included 40 patients who underwent head scans with both mobile and stationary scanners. Gray and white matter signal and noise were measured at predefined locations on axial slices, and signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated. Artifacts below the cranial calvaria and in the posterior fossa were also measured. In addition, image quality was subjectively assessed by two radiologists in terms of corticomedullary differentiation, subcalvarial space, skull artifacts, and image noise. Quantitative measurements showed significantly higher image quality of the stationary CT scanner in terms of noise, SNR and CNR of gray and white matter. Artifacts measured in the posterior fossa were higher with the mobile CT scanner, but subcalvarial artifacts were comparable. Subjective image quality was rated similarly by two radiologists for both scanners in all domains except image noise, which was better for stationary CT scans. The image quality of the SOMATOM On.Site for brain scans is inferior to that of the conventional stationary scanner, but appears to be adequate for daily use in a clinical setting based on subjective ratings.

CT Arthrography of the Elbow: What Radiologists Should Know.

Computed tomography (CT) arthrography is a quickly available imaging modality to investigate elbow disorders. Its excellent spatial resolution enables the detection of subtle pathologic changes of intra-articular structures, which makes this technique extremely valuable in a joint with very tiny chondral layers and complex anatomy of articular capsule and ligaments. Radiation exposure has been widely decreased with the novel CT scanners, thereby increasing the indications of this examination. The main applications of CT arthrography of the elbow are the evaluation of capsule, ligaments, and osteochondral lesions in both the settings of acute trauma, degenerative changes, and chronic injury due to repeated microtrauma and overuse. In this review, we discuss the normal anatomic findings, technical tips for injection and image acquisition, and pathologic findings that can be encountered in CT arthrography of the elbow, shedding light on its role in the diagnosis and management of different orthopedic conditions. We aspire to offer a roadmap for the integration of elbow CT arthrography into routine clinical practice, fostering improved patient outcomes and a deeper understanding of elbow pathologies.

Protocol parameter extraction and centralization framework for comprehensive and in-depth CT protocol review and management.

CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human-readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners. In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human-readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross-protocol comparisons. The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital-wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual-energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per-system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side-by-side comparisons for protocols with similar clinical indications. In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

First clinical experience following the consensus guide for calibrating a proton stopping power ratio curve in a new proton centre.

BACKGROUND AND PURPOSE: This work introduces the first assessment of CT calibration following the ESTRO's consensus guidelines and validating the HLUT through the irradiation of biological material. METHODS: Two electron density phantoms were scanned with two CT scanners using two CT scan energies. The stopping power ratio (SPR) and mass density (MD) HLUTs for different CT scan energies were derived using Schneider's and ESTRO's methods. The comparison metric in this work is based on the Water-Equivalent Thickness (WET) difference between the treatment planning system and biological irradiation measurement. The SPR HLUTs were compared between the two calibration methods. To assess the accuracy of using MD HLUT for dose calculation in the treatment planning system, MD vs SPR HLUT was compared. Lastly, the feasibility of using a single SPR HLUT to replace two different energy CT scans was explored. RESULTS: The results show a WET difference of less than 3.5% except for the result in the Bone region between Schneider's and ESTRO's methods. Comparing MD and SPR HLUT, the results from MD HLUT show less than a 3.5% difference except for the Bone region. However, the SPR HLUT shows a lower mean absolute percentage difference as compared to MD HLUT between the measured and calculated WET difference. Lastly, it is possible to use a single SPR HLUT for two different CT scan energies since both WET differences are within 3.5%. CONCLUSION: This is the first report on calibrating an HLUT following the ESTRO's guidelines. While our result shows incremental improvement in range uncertainty using the ESTRO's guideline, the prescriptional approach of the guideline does promote harmonization of CT calibration protocols between different centres.

Magneto-acousto-electrical tomography using nonlinearly frequency-modulated ultrasound.

Objective. In this study, nonlinearly frequency-modulated (NLFM) ultrasound was applied to magneto-acousto-electrical tomography (MAET) to increase the dynamic range of detection.Approach. Generation of NLFM signals using window function method-based on the principle of stationary phase-and piecewise linear frequency modulation method-based on the genetic algorithm-was discussed. The MAET experiment systems using spike, linearly frequency-modulated (LFM), or NLFM pulse stimulation were constructed, and three groups of MAET experiments on saline agar phantom samples were carried out to verify the performance-respectively the sensitivity, the dynamic range, and the longitudinal resolution of detection-of MAET using NLFM ultrasound in comparison to that using LFM ultrasound. Based on the above experiments, a pork sample was imaged by ultrasound imaging method, spike MAET method, LFM MAET method, and NLFM MAET method, to compare the imaging accuracy.Main results. The experiment results showed that, through sacrificing very little main-lobe width of pulse compression or equivalently the longitudinal resolution, the MAET using NLFM ultrasound achieved higher signal-to-interference ratio (and therefore higher detection sensitivity), lower side-lobe levels of pulse compression (and therefore larger dynamic range of detection), and large anti-interference capability, compared to the MAET using LFM ultrasound.Significance. The applicability of the MAET using NLFM ultrasound was proved in circumferences where sensitivity and dynamic range of detection were mostly important and slightly lower longitudinal resolution of detection was acceptable. The study furthered the scheme of using coded ultrasound excitation toward the clinical application of MAET.

Objective image quality assurance in cone-beam CT: Test methods, analysis, and workflow in longitudinal studies.

BACKGROUND: Standards for image quality evaluation in multi-detector CT (MDCT) and cone-beam CT (CBCT) are evolving to keep pace with technological advances. A clear need is emerging for methods that facilitate rigorous quality assurance (QA) with up-to-date metrology and streamlined workflow suitable to a range of MDCT and CBCT systems. PURPOSE: To evaluate the feasibility and workflow associated with image quality (IQ) assessment in longitudinal studies for MDCT and CBCT with a single test phantom and semiautomated analysis of objective, quantitative IQ metrology. METHODS: A test phantom (CorgiTM Phantom, The Phantom Lab, Greenwich, New York, USA) was used in monthly IQ testing over the course of 1 year for three MDCT scanners (one of which presented helical and volumetric scan modes) and four CBCT scanners. Semiautomated software analyzed image uniformity, linearity, contrast, noise, contrast-to-noise ratio (CNR), 3D noise-power spectrum (NPS), modulation transfer function (MTF) in axial and oblique directions, and cone-beam artifact magnitude. The workflow was evaluated using methods adapted from systems/industrial engineering, including value stream process modeling (VSPM), standard work layout (SWL), and standard work control charts (SWCT) to quantify and optimize test methodology in routine practice. The completeness and consistency of DICOM data from each system was also evaluated. RESULTS: Quantitative IQ metrology provided valuable insight in longitudinal quality assurance (QA), with metrics such as NPS and MTF providing insight on root cause for various forms of system failure-for example, detector calibration and geometric calibration. Monthly constancy testing showed variations in IQ test metrics owing to system performance as well as phantom setup and provided initial estimates of upper and lower control limits appropriate to QA action levels. Rigorous evaluation of QA workflow identified methods to reduce total cycle time to ∼10 min for each system-viz., use of a single phantom configuration appropriate to all scanners and Head or Body scan protocols. Numerous gaps in the completeness and consistency of DICOM data were observed for CBCT systems. CONCLUSION: An IQ phantom and test methodology was found to be suitable to QA of MDCT and CBCT systems with streamlined workflow appropriate to busy clinical settings.

Technical and clinical considerations of a physical liver phantom for CT radiomics analysis.

OBJECTIVE: This study identifies key characteristics to help build a physical liver computed tomography (CT) phantom for radiomics harmonization; particularly, the higher-order texture metrics. MATERIALS AND METHODS: CT scans of a radiomics phantom comprising of 18 novel 3D printed inserts with varying size, shape, and material combinations were acquired on a 64-slice CT scanner (Brilliance 64, Philips Healthcare). The images were acquired at 120 kV, 250 mAs, CTDIvol of 16.36 mGy, 2 mm slice thickness, and iterative noise-reduction reconstruction (iDose, Philips Healthcare, Andover, MA). Radiomics analysis was performed using the Cancer Imaging Phenomics Toolkit (CaPTk), following automated segmentation of 3D regions of interest (ROI) of the 18 inserts. The findings were compared to three additional ROI obtained of an anthropomorphic liver phantom, a patient liver CT scan, and a water phantom, at comparable imaging settings. Percentage difference in radiomic metrics values between phantom and tissue was used to assess the biological equivalency and <10% was used to claim equivalent. RESULTS: The HU for all 18 ROI from the phantom ranged from -30 to 120 which is within clinically observed HU range of the liver, showing that our phantom material (T3-6B) is representative of biological CT tissue densities (liver) with >50% radiomic features having <10% difference from liver tissue. Based on the assessment of the Neighborhood Gray Tone Difference Matrix (NGTDM) metrics it is evident that the water phantom ROI show extreme values compared to the ROIs from the phantom. This result may further reinforce the difference between a structureless quantity such as water HU values and tissue HU values found in liver. CONCLUSION: The 3-D printed patterns of the constructed radiomics phantom cover a wide span of liver tissue textures seen in CT images. Using our results, texture metrics can be selectively harmonized to establish clinically relevant and reliable radiomics panels.

Performance characteristics of the 5-ring GE Discovery MI PET/CT scanner using AAPM TG-126 report.

AIM: To report on the performance characteristics of the 5-ring GE Discovery MI PET/CT systems using the AAPM TG-126 report and compare these results to NEMA NU 2-2012 where applicable. MATERIALS AND METHODS: TG-126 testing was performed on two GE 5-Rings Discovery MI scanners. Tests performed included spatial resolution, PET/CT image-registration accuracy, sensitivity, count rate performance, accuracy of corrections, image contrast, scatter/attenuation correction, and image uniformity. All acquired data were analyzed using scanner console or free software tools as described by TG-126 and the results were then compared to published NEMA NU 2-2012 values. RESULTS: Both scanners gave similar resolution results for TG-126 and NEMA NU 2-2012 and were within manufacturer specifications. Image-registration accuracy between PET and CT using our clinical protocol showed excellent results with values ≤1 mm. Sensitivity using TG-126 was 19.43 cps/kBq while for NEMA the value was 20.73 cps/kBq. The peak noise-equivalent counting rate was 2174 kcps at 63.1 kBq/mL and is not comparable to NEMA NU 2-2012 due to differences in phantoms and methods used to measure and calculate this parameter. The accuracy of corrections for count losses for TG-126 were expressed in SUV values and found to be within 10% of the expected SUV measurement of 1. Image contrast and scatter/attenuation correction using the TG-126 method gave acceptable results. Image uniformity assessment resulted in values within the recommended ± 5% limits. CONCLUSION: These results show that the 5-ring GE Discovery MI PET/CT scanner testing using TG-126 is reproducible and has similar results to NEMA NU 2-2012 tests where applicable. We hope these results start to form the basis to compare PET/CT systems using TG-126.

The environmental impact of energy consumption and carbon emissions in radiology departments: a systematic review.

OBJECTIVES: Energy consumption and carbon emissions from medical equipment like CT/MRI scanners and workstations contribute to the environmental impact of healthcare facilities. The aim of this systematic review was to identify all strategies to reduce energy use and carbon emissions in radiology. METHODS: In June 2023, a systematic review (Medline/Embase/Web of Science) was performed to search original articles on environmental sustainability in radiology. The extracted data include environmental sustainability topics (e.g., energy consumption, carbon footprint) and radiological devices involved. Sustainable actions and environmental impact in radiology settings were analyzed. Study quality was assessed using the QualSyst tool. RESULTS: From 918 retrieved articles, 16 met the inclusion criteria. Among them, main topics were energy consumption (10/16, 62.5%), life-cycle assessment (4/16, 25.0%), and carbon footprint (2/16, 12.5%). Eleven studies reported that 40-91% of the energy consumed by radiological devices can be defined as "nonproductive" (devices "on" but not working). Turning-off devices during idle periods 9/16 (56.2%) and implementing workflow informatic tools (2/16, 12.5%) were the sustainable actions identified. Energy-saving strategies were reported in 8/16 articles (50%), estimating annual savings of thousand kilowatt-hours (14,180-171,000 kWh). Cost-savings were identified in 7/16 (43.7%) articles, ranging from US $9,225 to 14,328 per device. Study quality was over or equal the 80% of high-quality level in 14/16 (87.5%) articles. CONCLUSION: Energy consumption and environmental sustainability in radiology received attention in literature. Sustainable actions include turning-off radiological devices during idle periods, favoring the most energy-efficient imaging devices, and educating radiological staff on energy-saving practices, without compromising service quality. RELEVANCE STATEMENT: A non-negligible number of articles - mainly coming from North America and Europe - highlighted the need for energy-saving strategies, attention to equipment life-cycle assessment, and carbon footprint reduction in radiology, with a potential for cost-saving outcome. KEY POINTS: • Energy consumption and environmental sustainability in radiology received attention in the literature (16 articles published from 2010 to 2023). • A substantial portion (40-91%) of the energy consumed by radiological devices was classified as "non-productive" (devices "on" but not working). • Sustainable action such as shutting down devices during idle periods was identified, with potential annual energy savings ranging from 14,180 to 171,000 kWh.

Mobile imaging trailers: A scoping review of CT and MRI modalities.

INTRODUCTION: Mobile Imaging Trailers enable moving diagnostic imaging equipment between locations requiring very little setup and configuration, example given CT-scanners and MRI-scanners. However, despite the apparent benefits of utilising these imaging capabilities, very little research on the subject exists. This study aims at gaining an overview of the current state of the literature, using the scoping review methodology. METHODS: The systematic literature search was conducted in three databases: Scopus, Embase and PubMed. Included sources were extracted based on the objectives of the scoping review, and inspired by the by PRISMA-ScR. RESULTS: 29 papers were included. CONCLUSION: The results of the review showed that three general categories of research on this subject exist - trailers used in research, trailers as the object of research and trailers as an element or tool of the research. Of these, the most prevalent one used is the latter - trailers used as an element or tool of the research. This; however, is an issue for the use of trailers in a clinical setting, as very little research has been conducted on how they might be used and how they compare to fixed installations. As seen during the recent COVID-19 pandemic, the potentials for the use of MITs are immense; however, with the current lack of knowledge and understanding, the full potential has not been realised, suggesting further research should be focused in this area. IMPLICATIONS FOR PRACTICE: This study has shown that the limited research in the area does point towards a few benefits of MITs; however, there is a clear lack of sufficient research on the field to say this with confidence.

Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study.

We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computedZvalues were compared and the robustness of the approach based on the materials' composition was confirmed. Finally, the calibration method was compared with a previous method by Bourqueet al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.

Cardiac-induced motion of the pancreas and its effect on image quality of ultrahigh-resolution CT.

Recent advancements in diagnostic CT detector technology have made it possible to resolve anatomical features smaller than 20 LP/cm, referred to as ultra-high-resolution (UHR) CT. Subtle biological motions that did not affect standard-resolution (SR) CT may not be neglected in UHR. This study aimed to quantify the cardiac-induced motion of the pancreas and simulate its impact on the image quality of UHR-CT. We measured the displacement of the head of the pancreas in three healthy volunteers using Displacement Encoding with Stimulated Echoes (DENSE) MRI. The results were used to simulate SR- and UHR-CT acquisitions affected by pancreatic motion.We found pancreatic displacement in the 0.24-1.59 mm range during one cardiac cycle across the subjects. The greatest displacement was observed in the anterior-posterior direction. The time to peak displacement varied across subjects. Both SR and UHR images showed reduced image quality, as measured by radial modulation transfer function, due to cardiac-induced motion, but the motion artifacts caused more severe degradation in UHR acquisitions. Our investigation of cardiac-induced pancreatic displacement reveals its potential to degrade both standard and UHR-CT scans. To fully utilize the improvement in spatial resolution offered by UHR-CT, the effects of cardiac-induced motion in the abdomen need to be understood and corrected.Relevance statement Advancements in CT detector technology have enhanced CT scanner spatial resolution to approximately 100 µm. Consequently, previously ignored biological motions such as the cardiac-induced motion of the pancreas now demand attention to fully utilize this improved resolution.

Development and tuning of models for accurate simulation of CT spatial resolution using CatSim.

Objective. We sought to systematically evaluate CatSim's ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically used x-ray techniques.Approach.Using a 64-detector-row clinical scanner, we scanned two phantoms designed to evaluate spatial resolution in the projection and image domains. These empirical scans were performed over the standard clinically used range of x-ray techniques (kV, and mA). We extracted projection data from the scanner, and we reconstructed images. For the CatSim simulations, we developed digital phantoms to represent the phantoms used in the empirical scans. We developed a new, realistic model for the x-ray source focal spot, and we empirically tuned a published model for the x-ray detector temporal response. We applied these phantoms and models to simulate scans equivalent to the empirical scans, and we reconstructed the simulated projections using the same methods used for the empirical scans. For the empirical and simulated scans, we qualitatively and quantitatively compared the projection-domain and image-domain point-spread functions (PSFs) as well as the image-domain modulation transfer functions. We reported four quantitative metrics and the percent error between the empirical and simulated results.Main Results.Qualitatively, the PSFs matched well in both the projection and image domains. Quantitatively, all four metrics generally agreed well, with most of the average errors substantially less than 5% for all x-ray techniques. Although the errors tended to increase with decreasing kV, we found that the CatSim simulations agreed with the empirical scans within limits required for the anticipated applications of CatSim.Significance.The new focal spot model and the new detector temporal response model are significant contributions to CatSim because they enabled achieving the desired level of agreement between empirical and simulated results. With these new models and this validation, CatSim users can be confident that the spatial resolution represented by simulations faithfully represents results that would be obtained by a real scanner, within reasonable, known limits. Furthermore, users of CatSim can vary parameters including but not limited to system geometry, focal spot size/shape and detector parameters, beyond the values available in physical scanners, and be confident in the results. Therefore, CatSim can be used to explore new hardware designs as well as new scanning and reconstruction methods, thus enabling acceleration of improved CT scan capabilities.

Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.

BACKGROUND: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contrast structures. PURPOSE: The z-flying focal spot (zFFS) is a well-established hardware-based solution that aims to double the sampling rate in longitudinal direction and therefore reduce aliasing artifacts. However, given the technical complexity of the zFFS, this work proposes a deep learning-based approach as an alternative solution. METHODS: We propose a supervised learning approach to perform a mapping between input projections and the corresponding rows required for double sampling in the z-direction. We present a comprehensive evaluation using both a clinical dataset obtained using raw data from 40 real patient scans acquired with zFFS and a synthetic dataset consisting of 100 simulated spiral scans using a phantom specifically designed for our problem. For the clinical dataset, we utilized 32 scans as training set and 8 scans as validation set, whereas for the synthetic dataset, we used 80 scans for training and 20 scans for validation purposes. Both qualitative and quantitative assessments are conducted on a test set consisting of nine real patient scans and six phantom measurements to validate the performance of our approach. A simulation study was performed to investigate the robustness against different scan configurations in terms of detector collimation and pitch value. RESULTS: In the quantitative comparison based on clinical patient scans from the test set, all network configurations show an improvement in the root mean square error (RMSE) of approximately 20% compared to neglecting the doubled longitudinal sampling by the zFFS. The results of the qualitative analysis indicate that both clinical and synthetic training data can reduce windmill artifacts through the application of a correspondingly trained network. Together with the qualitative results from the test set phantom measurements it is emphasized that a training of our method with synthetic data resulted in superior performance in windmill artifact reduction. CONCLUSIONS: Deep learning-based raw data interpolation has the potential to enhance the sampling in z-direction and thus minimize aliasing effects, as it is the case with the zFFS. Especially a training with synthetic data showed promising results. While it may not outperform zFFS, our method represents a beneficial solution for CT scanners lacking the necessary hardware components for zFFS.

Possible improvements in effective fill factor using X-ray fluorescent interpixel reflectors.

BACKGROUND: The spatial resolution of energy-integrating diagnostic CT scanners is limited by interpixel reflectors on the detector, which optically isolate pixels but create dead space. Because the width of the reflector cannot easily be decreased, fill factor diminishes as resolution increases. PURPOSE: We propose loading (or mixing) a high-Z element into the reflectors, causing the reflectors to be X-ray fluorescent. Re-emitted characteristic X-rays could be detected in adjacent pixels, increasing the effective fill factor and compensating for fill factor loss with higher-resolution detectors. The purpose of this work is to understand the physical principles of this approach and to analyze its effectiveness using Monte Carlo simulations. METHODS: Detector pixels were modeled using the GEANT4 Monte Carlo package. The width of the reflector was kept constant at 0.1 mm throughout, and we considered pixel pitches between 0.5 and 1 mm. The pixelated scintillator material was gadolinium oxysulfide, 3 mm thick. The baseline reflector material was chosen to be acrylic, and varying concentrations of a high-Z element were loaded into the material. We assumed that the optical characteristics of pixels were ideal (no absorption within pixels, perfect reflection at boundaries). The detector was irradiated uniformly with 10,000 X-ray photons to estimate its spectral response. The figure of merit was the variance of the detector signal at zero frequency normalized to that of an ideal single-bin photon-counting detector with 100% fill factor. Sensitivity analyses were conducted to understand the effect of varying the high-Z element concentration and the spectrum. RESULTS: Initial simulations suggested that a k-edge near 50 keV would be ideal. Gd was therefore selected as the high-Z material. The relative variances for a conventional energy integrating detector without Gd at 1 mm pixel pitch (81% fill factor) and 0.5 mm pixel pitch (64% fill factor) were 1.38 and 1.74, compared to 1.00 for an ideal photon counting detector, implying a 26% variance penalty for 0.5 mm pitch. When 1 g/cm3 Gd was loaded into the interpixel reflector, the relative variance improved to 1.27 and 1.43, respectively, implying that the variance penalty for including Gd together with 0.5 mm pitch is only 4%. Performance was nearly maximized at 1.0 g/cm3 of Gd, but a concentration of 0.5 g/cm3 of Gd showed most of the benefit. Improvements depend weakly on kV, with lower kV associated with higher improvements. An external anti-scatter grid was not modeled in our simulations and would reduce the expected benefit, depending greatly on the pitch and dimensionality of the anti-scatter grid. CONCLUSIONS: The losses in fill factor associated with smaller pixel pitch can be reduced if Gd or a similar element could be loaded into the interpixel reflector. These improvements in noise efficiency are yet to be verified experimentally.

Ultra-low dose CT scanning for PET/CT.

BACKGROUND: The use of computed tomography (CT) for attenuation correction (AC) in whole-body PET/CT can result in a significant contribution to radiation exposure. This can become a limiting factor for reducing considerably the overall radiation exposure of the patient when using the new long axial field of view (LAFOV) PET scanners. However, recent CT technology have introduced features such as the tin (Sn) filter, which can substantially reduce the CT radiation dose. PURPOSE: The purpose of this study was to investigate the ultra-low dose CT for attenuation correction using the Sn filter together with other dose reduction options such as tube current (mAs) reduction. We explore the impact of dose reduction in the context of AC-CT and how it affects PET image quality. METHODS: The study evaluated a range of ultra-low dose CT protocols using five physical phantoms that represented a broad collection of tissue electron densities. A long axial field of view (LAFOV) PET/CT scanner was used to scan all phantoms, applying various CT dose reduction parameters such as reducing tube current (mAs), increasing the pitch value, and applying the Sn filter. The effective dose resulting from the CT scans was determined using the CTDIVol reported by the scanner. Several voxel-based and volumes of interest (VOI)-based comparisons were performed to compare the ultra-low dose CT images, the generated attenuation maps, and corresponding PET images against those images acquired with the standard low dose CT protocol. Finally, two patient datasets were acquired using one of the suggested ultra-low dose CT settings. RESULTS: By incorporating the Sn filter and adjusting mAs to the lowest available value, the radiation dose in CT images of PBU-60 phantom was significantly reduced; resulting in an effective dose of nearly 2% compared to the routine low dose CT protocols currently in clinical use. The assessment of PET images using VOI and voxel-based comparisons indicated relative differences (RD%) of under 6% for mean activity concentration (AC) in the torso phantom and patient dataset and under 8% for a source point in the CIRS phantom. The maximum RD% value of AC was 14% for the point source in the CIRS phantom. Increasing the tube current from 6 mAs to 30 mAs in patients with high BMI, or with arms down, can suppress the photon starvation artifact, whilst still preserving a dose reduction of 90%. CONCLUSIONS: Introducing a Sn filter in CT imaging lowers radiation dose by more than 90%. This reduction has minimal effect on PET image quantification at least for patients without Body Mass Index (BMI) higher than 30. Notably, this study results need validation using a larger clinical PET/CT dataset in the future, including patients with higher BMI.

Task-based assessment of resolution properties of CT images with a new index using deep convolutional neural network.

In this study, we propose a method for obtaining a new index to evaluate the resolution properties of computed tomography (CT) images in a task-based manner. This method applies a deep convolutional neural network (DCNN) machine learning system trained on CT images with known modulation transfer function (MTF) values to output an index representing the resolution properties of the input CT image [i.e., the resolution property index (RPI)]. Sample CT images were obtained for training and testing of the DCNN by scanning the American Radiological Society phantom. Subsequently, the images were reconstructed using a filtered back projection algorithm with different reconstruction kernels. The circular edge method was used to measure the MTF values, which were used as teacher information for the DCNN. The resolution properties of the sample CT images used to train the DCNN were created by intentionally varying the field of view (FOV). Four FOV settings were considered. The results of adapting this method to the filtered back projection (FBP) and hybrid iterative reconstruction (h-IR) images indicated highly correlated values with the MTF10% in both cases. Furthermore, we demonstrated that the RPIs could be estimated in the same manner under the same imaging conditions and reconstruction kernels, even for other CT systems, where the DCNN was trained on CT systems produced by the same manufacturer. In conclusion, the RPI, which is a new index that represents the resolution property using the proposed method, can be used to evaluate the resolution of a CT system in a task-based manner.

Savings in CT Net Scan Energy Consumption: Assessment Using Dose Report Metrics and Comparison With Savings in Idle State Energy Consumption.

BACKGROUND. CT scanners' net scan state (i.e., image acquisition period) represents a potential target for energy savings through protocol adjustments. However, gauging CT energy savings is difficult without installing costly energy monitors. OBJECTIVE. The purpose of this article was to assess correlations between CT dose report metrics and energy consumption during the system net scan state and to compare theoretic energy savings from matching percentage reductions in energy consumption during net scan and idle system states. METHODS. Current sensors were installed on a single CT scanner. A phantom was scanned at varying kilovoltage settings and effective tube current-rotation time settings. A retrospective assessment was performed in 32 patients (mean age, 61.2 ± 17.9 [SD] years; 17 men, 15 women) who underwent 32 single-energy noncontrast abdominopelvic CT examinations from September 22, 2021, to September 27, 2021, on the same scanner. Correlations between dose report metrics and net scan energy consumption were assessed in the phantom and clinical scans, and equations were generated to derive net scan energy consumption from DLP. An additional retrospective assessment was performed in 1355 patients (mean age, 59.3 ± 16.9 years; 663 men, 692 women) who underwent 1728 single-energy noncontrast abdominopelvic CT examinations from January 1, 2021, through December 31, 2021, on the same scanner to estimate net scan energy consumption per examination. This information was integrated with literature-derived values to compare estimated annual national energy savings resulting from 20% reductions in net scan and idle state energy consumption. RESULTS. Net scan energy consumption in the phantom scans showed high linear correlation with DLP (R2 = 0.87), and, in the clinical scans, high linear correlation with CTDIvol (R2 = 0.89) and very high linear correlation with DLP (R2 = 0.92). When combining mean DLP in examinations performed in the 1-year interval, an equation relating DLP and net scan energy consumption and literature values estimated that annual national energy savings was 14.9 times greater (40,437,870 kWh/2,704,000 kWh) by targeting the idle state rather than net scan state. CONCLUSION. CT net scan energy savings can be inferred from reductions in dose report metrics. However, targeting net scan energy consumption has modest impact relative to targeting idle state energy consumption. CLINICAL IMPACT. Environmental sustainability efforts should target the idle state energy consumption of CT.

A systematic task-based image quality assessment of photon-counting and energy integrating CT as a function of reconstruction kernel and phantom size.

BACKGROUND: Image quality of photon-counting and energy integrating CT scanners changes with object size, dose to the object, and kernel selection. PURPOSE: To comprehensively compare task-generic image quality of photon-counting CT (PCCT) and energy integrating CT (EICT) systems as a function of phantom size, dose, and reconstruction kernel. METHODS: A size-variant phantom (Mercury Phantom 3.0) was used to characterize the image quality of PCCT and EICT systems as a function of object size. The phantom contained five cylinders attached by slanted tapered sections. Each cylinder contained two sections: one uniform for noise, and the other with inserts for spatial resolution and contrast measurements. The phantom was scanned on Siemens' SOMATOM Force and NAEOTOM Alpha at 1.18 and 7.51 mGy without tube current modulation. CTDIvol was matched across two systems by setting the required tube currents, else, all other acquisition settings were fixed. CT sinograms were reconstructed using FBP and iterative (ADMIRE2 - Force; QIR2 - Alpha) algorithms with Body regular (Br) kernels. Noise Power Spectrum (NPS), Task Transfer Function (TTF), contrast-to-noise ratio (CNR), and detectability index (d') for a task of identifying 2-mm disk were evaluated based on AAPM TG-233 metrology using imQuest, an open-source software package. Averaged noise frequency (fav ) and 50% cut-off frequency for TTF (f50 ) were used as scalar metrics to quantify noise texture and spatial resolution, respectively. The difference between image quality metrics' measurements was calculated as IQPCCT - IQEICT . RESULTS: From Br40 (soft) to Br64 (sharp), f50 for air insert increased from 0.35 mm-1  ± 0.04 (standard deviation) to 0.76 mm-1  ± 0.17, 0.34 mm-1  ± 0.04 to 0.77 mm-1  ± 0.17, 0.37 mm-1  ± 0.02 to 0.95 mm-1  ± 0.17 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively, when averaged over all sizes and dose levels. Similarly, from Br40 to Br64, noise magnitude increased from 10.86 HU ± 7.12 to 38.61 HU ± 18.84, 10.94 HU ± 7.08 to 38.82 HU ± 18.70, 13.74 HU ± 11.02 to 52.11 HU ± 26.22 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively. The difference in fav was consistent across all sizes and dose levels. PCCT-70keV-VMI showed better consistency in contrast measurements for iodine and bone inserts than PCCT-T3D and EICT; however, PCCT-T3D had higher contrast for both inserts. From Br40 to Br64, considering all sizes and dose levels, CNR for iodine insert decreased from 52.30 ± 46.44 to 12.18 ± 10.07, 40.42 ± 33.42 to 9.48 ± 7.16, 39.94 ± 37.60 to 7.84 ± 6.67 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively. CONCLUSIONS: Both PCCT image types, T3D and 70-keV-VMI exhibited similar or better noise, contrast, CNR than EICT when comparing kernels with similar names. For 512 × 512 matrix, PCCT's sharp kernels had lower resolution than EICT's sharp kernels. For all image quality metrics, except extreme low, every dose condition had a similar set of IQ-matching kernels. It suggests that considering patient size and dose level to determine IQ-matching kernel pairs across PCCT and EICT systems may not be imperative while translating protocols, except when the signal to the detector is extremely low.