Spatial Resolution Fidelity Comparison Between Energy Integrating and Deep Silicon Photon Counting CT: Implications for Pulmonary Imaging.

PURPOSE: We investigated spatial resolution loss away from isocenter for a prototype deep silicon photon-counting detector (PCD) CT scanner and compare with a clinical energy-integrating detector (EID) CT scanner. MATERIALS AND METHODS: We performed three scans on a wire phantom at four positions (isocenter, 6.7, 11.8, and 17.1 cm off isocenter). The acquisition modes were 120 kV EID CT, 120 kV high-definition (HD) EID CT, and 120 kV PCD CT. HD mode used double the projection view angles per rotation as the "regular" EID scan mode. The diameter of the wire was calculated by taking the full width of half max (FWHM) of a profile drawn over the radial and azimuthal directions of the wire. Change in wire diameter appearance was assessed by calculating the ratio of the radial and azimuthal diameter relative to isocenter. t tests were used to make pairwise comparisons of the wire diameter ratio with each acquisition and mean ratios' difference from unity. RESULTS: Deep silicon PCD CT had statistically smaller (P<0.05) changes in diameter ratio for both radial and azimuthal directions compared with both regular and HD EID modes and was not statistically different from unity (P<0.05). Maximum increases in FWMH relative to isocenter were 36%, 12%, and 1% for regular EID, HD EID, and deep silicon PCD, respectively. CONCLUSION: Deep silicon PCD CT exhibits less change in spatial resolution in both the radial and azimuthal directions compared with EID CT.

Computed Tomography Angiography: Principles and Advances.

This review describes current state-of-the-art computed tomography technology required to address human-physiology-based challenges unique to angiographic imaging. Challenges are based on the need to image a bolus of contrast agent traversing inside rapidly moving structures. This article reviews the latest methods to optimize contrast timing and minimize motion.

Needle artifact reduction during interventional CT procedures using a silver filter.

BACKGROUND: MAR algorithms have not been productized in interventional imaging because they are too time-consuming. Application of a beam hardening filter can mitigate metal artifacts and doesn't increase computational burden. We evaluate the ability to reduce metal artifacts of a 0.5 mm silver (Ag) additional filter in a Multidetector Computed Tomography (MDCT) scanner during CT-guided biopsy procedures. METHODS: A biopsy needle was positioned inside the lung field of an anthropomorphic phantom (Lungman, Kyoto Kagaku, Kyoto, Japan). CT acquisitions were performed with beam energies of 100 kV, 120 kV, 135 kV, and 120 kV with the Ag filter and reconstructed using a filtered back projection algorithm. For each measurement, the CTDIvol was kept constant at 1 mGy. Quantitative profiles placed in three regions of the artifact (needle, needle tip, and trajectory artifacts) were used to obtain metrics (FWHM, FWTM, width at - 100 HU, and absolute error in HU) to evaluate the blooming artifact, artifact width, change in CT number, and artifact range. An image quality analysis was carried out through image noise measurement. A one-way analysis of variance (ANOVA) test was used to find significant differences between the conventional CT beam energies and the Ag filtered 120 kV beam. RESULTS: The 120 kV-Ag is shown to have the shortest range of artifacts compared to the other beam energies. For needle tip and trajectory artifacts, a significant reduction of - 53.6% (p < 0.001) and - 48.7% (p < 0.001) in the drop of the CT number was found, respectively, in comparison with the reference beam of 120 kV as well as a significant decrease of up to - 34.7% in the artifact width (width at - 100 HU, p < 0.001). Also, a significant reduction in the blooming artifact of - 14.2% (FWHM, p < 0.001) and - 53.3% (FWTM, p < 0.001) was found in the needle artifact. No significant changes (p > 0.05) in image noise between the conventional energies and the 120 kV-Ag were found. CONCLUSIONS: A 0.5 mm Ag additional MDCT filter demonstrated consistent metal artifact reduction generated by the biopsy needle. This reduction may lead to a better depiction of the target and surrounding structures while maintaining image quality.

Technical note: A comparison of physician doses in C-Arm and CT fluoroscopy procedures.

PURPOSE: We address the misconception that the typical physician dose is higher for CT fluoroscopy (CTF) procedures compared to C-Arm procedures. METHODS: We compare physician scatter doses using two methods: a literature review of reported doses and a model based on a modified form of the dose area product (DAP). We define this modified form of DAP, "cumulative absorbed DAP," as the product of the area of the x-ray beam striking the patient, the dose rate per unit area, and the exposure time. RESULTS: The patient entrance dose rate for C-Arm fluoroscopy (0.2 mGy/s) was found to be 15 times lower than for CT fluoroscopy (3 mGy/s). A typical beam entrance area for C-Arm fluoroscopy reported in the literature was found to be 10.6 × 10.6 cm (112 cm2), whereas for CTF was 0.75 × 32 cm (24 cm2). The absorbed DAP rate for C-Arm fluoroscopy (22 mGy*cm2/s) was found to be 3.3 times lower than for CTF (72 mGy*cm2/s). The mean fluoroscopy time for C-Arm procedures (710 s) was found to be 21 times higher than for CT fluoroscopy procedures (23 s). The cumulative absorbed DAP for C-Arm procedures was found to be 9.4 times higher when compared to CT procedures (1.59 mGy*m2 vs. 0.17 mGy*m2). CONCLUSIONS: The higher fluoroscopy time in C-Arm procedures leads to a much lower cumulative DAP (i.e., physician scatter dose) in CTF procedures. This result can inform interventional physicians deciding on whether to perform inter-procedural imaging inside the room as opposed to retreating from the room.

Improving the Safety of Computed Tomography Through Automated Quality Measurement: A Radiologist Reader Study of Radiation Dose, Image Noise, and Image Quality.

OBJECTIVES: The Centers for Medicare and Medicaid Services funded the development of a computed tomography (CT) quality measure for use in pay-for-performance programs, which balances automated assessments of radiation dose with image quality to incentivize dose reduction without compromising the diagnostic utility of the tests. However, no existing quantitative method for assessing CT image quality has been validated against radiologists' image quality assessments on a large number of CT examinations. Thus to develop an automated measure of image quality, we tested the relationship between radiologists' subjective ratings of image quality with measurements of radiation dose and image noise. MATERIALS AND METHODS: Board-certified, posttraining, clinically active radiologists rated the image quality of 200 diagnostic CT examinations from a set of 734, representing 14 CT categories. Examinations with significant distractions, motion, or artifact were excluded. Radiologists rated diagnostic image quality as excellent, adequate, marginally acceptable, or poor; the latter 2 were considered unacceptable for rendering diagnoses. We quantified the relationship between ratings and image noise and radiation dose, by category, by analyzing the odds of an acceptable rating per standard deviation (SD) increase in noise or geometric SD (gSD) in dose. RESULTS: One hundred twenty-five radiologists contributed 24,800 ratings. Most (89%) were acceptable. The odds of an examination being rated acceptable statistically significantly increased per gSD increase in dose and decreased per SD increase in noise for most categories, including routine dose head, chest, and abdomen-pelvis, which together comprise 60% of examinations performed in routine practice. For routine dose abdomen-pelvis, the most common category, each gSD increase in dose raised the odds of an acceptable rating (2.33; 95% confidence interval, 1.98-3.24), whereas each SD increase in noise decreased the odds (0.90; 0.79-0.99). For only 2 CT categories, high-dose head and neck/cervical spine, neither dose nor noise was associated with ratings. CONCLUSIONS: Radiation dose and image noise correlate with radiologists' image quality assessments for most CT categories, making them suitable as automated metrics in quality programs incentivizing reduction of excessive radiation doses.

Large variation in radiation dose for routine abdomen CT: reasons for excess and easy tips for reduction.

OBJECTIVE: To characterize the use and impact of radiation dose reduction techniques in actual practice for routine abdomen CT. METHODS: We retrospectively analyzed consecutive routine abdomen CT scans in adults from a large dose registry, contributed by 95 hospitals and imaging facilities. Grouping exams into deciles by, first, patient size, and second, size-adjusted dose length product (DLP), we summarized dose and technical parameters and estimated which parameters contributed most to between-protocols dose variation. Lastly, we modeled the total population dose if all protocols with mean size-adjusted DLP above 433 or 645 mGy-cm were reduced to these thresholds. RESULTS: A total of 748,846 CTs were performed using 1033 unique protocols. When sorted by patient size, patients with larger abdominal diameters had increased dose and effective mAs (milliampere seconds), even after adjusting for patient size. When sorted by size-adjusted dose, patients in the highest versus the lowest decile in size-adjusted DLP received 6.4 times the average dose (1680 vs 265 mGy-cm) even though diameter was no different (312 vs 309 mm). Effective mAs was 2.1-fold higher, unadjusted CTDIvol 2.9-fold, and phase 2.5-fold for patients in the highest versus lowest size-adjusted DLP decile. There was virtually no change in kV (kilovolt). Automatic exposure control was widely used to modulate mAs, whereas kV modulation was rare. Phase was the strongest driver of between-protocols variation. Broad adoption of optimized protocols could result in total population dose reductions of 18.6-40%. CONCLUSION: There are large variations in radiation doses for routine abdomen CT unrelated to patient size. Modification of kV and single-phase scanning could result in substantial dose reduction. CLINICAL RELEVANCE: Radiation dose-optimization techniques for routine abdomen CT are routinely under-utilized leading to higher doses than needed. Greater modification of technical parameters and number of phases could result in substantial reduction in radiation exposure to patients. KEY POINTS: • Based on an analysis of 748,846 routine abdomen CT scans in adults, radiation doses varied tremendously across patients of the same size and optimization techniques were routinely under-utilized. • The difference in observed dose was due to variation in technical parameters and phase count. Automatic exposure control was commonly used to modify effective mAs, whereas kV was rarely adjusted for patient size. Routine abdomen CT should be performed using a single phase, yet multi-phase was common. • kV modulation by patient size and restriction to a single phase for routine abdomen indications could result in substantial reduction in radiation doses using well-established dose optimization approaches.

CT acquisition parameter selection in the real world: impacts on radiation dose and variation amongst 155 institutions.

OBJECTIVE: Quantify the relationship between CT acquisition parameters and radiation dose, how often parameters are adjusted in real-world practice, and their degree of contribution to real-world dose distribution. Identify discrepancies between parameters that are impactful in theory and impactful in practice. METHODS: This study analyses 1.3 million consecutive adult routine abdomen exams performed between November 2015 and Jan 2021 included in the University of California, San Francisco International CT Dose Registry of 155 institutions. We calculated geometric standard deviation (gSD) for five parameters (kV, mAs, spiral pitch, number of phases, scan length) to assess variation in practice. A Gaussian mixed regression model was performed to predict the radiation dose-length product (DLP) using the parameters. Three conceptualizations of "impact" were computed for each parameter. To reflect the theoretical impact, we predict the increase in DLP per 10% (and 15%) increase in the parameter. To reflect the real-world practical impact, we predict the increase in DLP per gSD increase in the parameter. RESULTS: Among studied examinations, mAs, number of phases, and scan length were frequently manipulated (gSD 1.52-1.70); kV was rarely manipulated (gSD 1.07). Theoretically, kV is the most impactful parameter (29% increase in DLP per 10% increase in kV, versus 5-9% increase for other parameters). In real-world practice, kV is less impactful; for each gSD increase in kV, the DLP increases by 20%, versus 22-69% for other parameters. CONCLUSION: Despite the potential impact of kV on radiation dose, this parameter is rarely manipulated in common practice and this potential remains untapped. CLINICAL RELEVANCE STATEMENT: CT beam energy (kV) modulation has the potential to strongly reduce radiation over-dosage to the patient, theoretically more so than similar degrees of modulation in other CT acquisition parameters. Despite this, beam energy modulation rarely occurs in practice, leaving its potential untapped. KEY POINTS: • The relationship between CT acquisition parameter selection and radiation dose roughly coincided with established theoretical understanding. • CT acquisition parameters differ from each other in frequency and magnitude of manipulation, with beam energy (kV) being rarely manipulated. • Beam energy (kV) has the potential to substantially impact radiation dose, but because it is rarely manipulated, it is the least impactful CT acquisition parameter affecting radiation dose in practice.

Correcting Posterior Paraspinal Muscle Computed Tomography Density for Intravenous Contrast Material Independent of Sex and Vascular Phase.

PURPOSE: Intravenous contrast poses challenges to computed tomography (CT) muscle density analysis. We developed and tested corrections for contrast-enhanced CT muscle density to improve muscle analysis and the utility of CT scans for the assessment of myosteatosis. MATERIALS AND METHODS: Using retrospective images from 240 adults who received routine abdominal CT imaging from March to November 2020 with weight-based iodine contrast, we obtained paraspinal muscle density measurements from noncontrast (NC), arterial, and venous-phase images. We used a calibration sample to develop 9 different mean and regression-based corrections for the effect of contrast. We applied the corrections in a validation sample and conducted equivalence testing. RESULTS: We evaluated 140 patients (mean age 52.0 y [SD: 18.3]; 60% female) in the calibration sample and 100 patients (mean age 54.8 y [SD: 18.9]; 60% female) in the validation sample. Contrast-enhanced muscle density was higher than NC by 8.6 HU (SD: 6.2) for the arterial phase (female, 10.4 HU [SD: 5.7]; male, 6.0 HU [SD:6.0]) and by 6.4 HU [SD:8.1] for the venous phase (female, 8.0 HU [SD: 8.6]; male, 4.0 HU [SD: 6.6]). Corrected contrast-enhanced and NC muscle density was equivalent within 3 HU for all correctionns. The -7.5 HU correction, independent of sex and phase, performed well for arterial (95% CI: -0.18, 1.80 HU) and venous-phase data (95% CI: -0.88, 1.41 HU). CONCLUSIONS: Our validated correction factor of -7.5 HU renders contrast-enhanced muscle density statistically similar to NC density and is a feasible rule-of-thumb for clinicians to implement.

Consumable Material Waste and Workflow Efficiency Comparison Between Multi-use Syringeless and Single-use Syringe-Based Injectors in Computed Tomography.

RATIONALE AND OBJECTIVES: Syringeless power injectors obviate the need for reloading iodinated contrast media (ICM) and plastic consumable pistons between exams. This study evaluates the potential time and material waste (ICM, plastic, saline, and total) saved using a multi-use syringeless injector (MUSI) compared to a single-use syringe-based injector (SUSI). MATERIALS AND METHODS: Two observers recorded technologist time spent using a SUSI and a MUSI over three clinical workdays. CT technologists (n = 15) were polled on their experience between the systems using a 5-point Likert scale survey. ICM, plastic, and saline waste data from each system were collected. A mathematical model was created to estimate total and categorical waste from each injector system over a 16-week period. RESULTS: On average, CT technologists spent 40.5 seconds less per exam with MUSI compared to SUSI (p < .001). Technologists rated MUSI work efficiency, user-friendliness, and overall satisfaction (strongly or somewhat improved) higher relative to SUSI (p < .05). Iodine waste was 31.3 L and 0.0 L for SUSI and MUSI, respectively. Plastic waste was 467.7 kg and 71.9 kg for SUSI and MUSI, respectively. Saline waste was 43.3 L and 52.5 L for SUSI and MUSI, respectively. Total waste was 555.0 kg and 124.4 kg for SUSI and MUSI respectively. CONCLUSION: Switching from SUSI to MUSI resulted in a 100%, 84.6%, and 77.6% reduction in ICM, plastic, and total waste. This system may fortify institutional endeavors toward green radiology initiatives. The potential time saved administering contrast using MUSI may improve CT technologist efficiency.

CT Number Accuracy and Association With Object Size: A Phantom Study Comparing Energy-Integrating Detector CT and Deep Silicon Photon-Counting Detector CT.

BACKGROUND. Variable beam hardening based on patient size causes variation in CT numbers for energy-integrating detector (EID) CT. Photon-counting detector (PCD) CT more accurately determines effective beam energy, potentially improving CT number reliability. OBJECTIVE. The purpose of the present study was to compare EID CT and deep silicon PCD CT in terms of both the effect of changes in object size on CT number and the overall accuracy of CT numbers. METHODS. A phantom with polyethylene rings of varying sizes (mimicking patient sizes) as well as inserts of different materials was scanned on an EID CT scanner in single-energy (SE) mode (120-kV images) and in rapid-kilovoltage-switching dual-energy (DE) mode (70-keV images) and on a prototype deep silicon PCD CT scanner (70-keV images). ROIs were placed to measure the CT numbers of the materials. Slopes of CT number as a function of object size were computed. Materials' ideal CT number at 70 keV was computed using the National Institute of Standards and Technology XCOM Photon Cross Sections Database. The root mean square error (RMSE) between measured and ideal numbers was calculated across object sizes. RESULTS. Slope (expressed as Hounsfield units per centimeter) was significantly closer to zero (i.e., less variation in CT number as a function of size) for PCD CT than for SE EID CT for air (1.2 vs 2.4 HU/cm), water (-0.3 vs -1.0 HU/cm), iodine (-1.1 vs -4.5 HU/cm), and bone (-2.5 vs -10.1 HU/cm) and for PCD CT than for DE EID CT for air (1.2 vs 2.8 HU/cm), water (-0.3 vs -1.0 HU/cm), polystyrene (-0.2 vs -0.9 HU/cm), iodine (-1.1 vs -1.9 HU/cm), and bone (-2.5 vs -6.2 HU/cm) (p < .05). For all tested materials, PCD CT had the smallest RMSE, indicating CT numbers closest to ideal numbers; specifically, RMSE (expressed as Hounsfield units) for SE EID CT, DE EID CT, and PCD CT was 32, 44, and 17 HU for air; 7, 8, and 3 HU for water; 9, 10, and 4 HU for polystyrene; 31, 37, and 13 HU for iodine; and 69, 81, and 20 HU for bone, respectively. CONCLUSION. For numerous materials, deep silicon PCD CT, in comparison with SE EID CT and DE EID CT, showed lower CT number variability as a function of size and CT numbers closer to ideal numbers. CLINICAL IMPACT. Greater reliability of CT numbers for PCD CT is important given the dependence of diagnostic pathways on CT numbers.

A Characterization of Deep Learning Reconstruction Applied to Dual-Energy Computed Tomography Monochromatic and Material Basis Images.

OBJECTIVE: Advancements in computed tomography (CT) reconstruction have enabled image quality improvements and dose reductions. Previous advancements have included iterative and model-based reconstruction. The latest image reconstruction advancement uses deep learning, which has been evaluated for polychromatic imaging only. This article characterizes a commercially available deep learning imaging reconstruction applied to dual-energy CT. METHODS: Monochromatic, iodine basis, and water basis images were reconstructed with filtered back projection (FBP), iterative (ASiR-V), and deep learning (DLIR) methods in a phantom experiment. Slice thickness, contrast-to-noise ratio, modulation transfer function, and noise power spectrum metrics were used to characterize ASiR-V and DLIR relative to FBP over a range of dose levels, phantom sizes, and iodine concentrations. RESULTS: Slice thicknesses for ASiR-V and DLIR demonstrated no statistically significant difference relative to FBP for all measurement conditions. Contrast-to-noise ratio performance for DLIR-high and ASiR-V 40% at 2 mg I/mL on 40-keV images were 162% and 30% higher than FBP, respectively. Task-based modulation transfer function measurements demonstrated no clinically significant change between FBP and ASiR-V and DLIR on monochromatic or iodine basis images. CONCLUSIONS: Deep learning image reconstruction enabled better image quality at lower monochromatic energies and on iodine basis images where image contrast is maximized relative to polychromatic or high-energy monochromatic images. Deep learning image reconstruction did not demonstrate thicker slices, decreased spatial resolution, or poor noise texture (ie, "plastic") relative to FBP.

How Do Cancer-Specific Computed Tomography Protocols Compare With the American College of Radiology Dose Index Registry? An Analysis of Computed Tomography Dose at 2 Cancer Centers.

BACKGROUND: Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey. METHODS: A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2. RESULTS: Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology. CONCLUSIONS: We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

Factors Contributing to Computed Tomography Trauma Scan Times at a Tertiary Center: Improving Emergency Department Trauma Imaging Workflow Through Targeted Interventions.

PURPOSES: The aims of the study are to identify factors contributing to computed tomography (CT) trauma scan turnaround time variation and to evaluate the effects of an automated intervention on time metrics. METHODS: Throughput metrics were captured via picture archiving and communication system from January 1, 2018, to December 16, 2019, and included 17,709 CT trauma scans from our institution. Initial data showed that imaging technologist variation played a significant role in trauma imaging turnaround time. In December 2019, we implemented a 2-pronged intervention: (1) educational intervention to techs and (2) modified trauma CT abdomen/pelvis to autogenerate and autosend reformats to picture archiving and communication system. A total of 13,169 trauma CT scans were evaluated from the postintervention period taking place from January 2020 to March 2021. Throughput metrics such as last image to first report interval and emergency department length of stay were captured and compared with performing technologist, time of day, and weekday versus weekend scans. RESULTS: Substantial variability among trauma CT scans was observed. For CT trauma abdomen/pelvis, the interval from last image to initial report decreased from 26.4 to 24.0 minutes ( P = 0.001) while the interval between first and last image time decreased from 11.4 to 4.2 minutes ( P < 0.001). Emergency department length of stay also decreased from 3.9 to 3.7 hours ( P < 0.0001) in the postintervention period. Variation among imaging technologist was statistically significant and became less significant after intervention ( P = 0.09, P = 0.54). CONCLUSIONS: Factors such as imaging technologist variability, time of day, and day of the week of trauma scans played a significant role in CT trauma turnaround time variability. Automation interventions can help with efficiency in image turnaround time.

Percutaneous CT-Guided Abdominal and Pelvic Biopsies: Comparison of an Electromagnetic Navigation System and CT Fluoroscopy.

PURPOSE: To compare electromagnetic navigation (EMN) with computed tomography (CT) fluoroscopy for guiding percutaneous biopsies in the abdomen and pelvis. MATERIALS AND METHODS: A retrospective matched-cohort design was used to compare biopsies in the abdomen and pelvis performed with EMN (consecutive cases, n = 50; CT-Navigation; Imactis, Saint-Martin-d'Hères, France) with those performed with CT fluoroscopy (n = 100). Cases were matched 1:2 (EMN:CT fluoroscopy) for target organ and lesion size (±10 mm). RESULTS: The population was well-matched (age, 65 vs 65 years; target size, 2.0 vs 2.1 cm; skin-to-target distance, 11.4 vs 10.7 cm; P > .05, EMN vs CT fluoroscopy, respectively). Technical success (98% vs 100%), diagnostic yield (98% vs 95%), adverse events (2% vs 5%), and procedure time (33 minutes vs 31 minutes) were not statistically different (P > .05). Operator radiation dose was less with EMN than with CT fluoroscopy (0.04 vs 1.2 µGy; P < .001), but patient dose was greater (30.1 vs 9.6 mSv; P < .001) owing to more helical scans during EMN guidance (3.9 vs 2.1; P < .001). CT fluoroscopy was performed with a mean of 29.7 tap scans per case. In 3 (3%) cases, CT fluoroscopy was performed with gantry tilt, and the mean angle out of plane for EMN cases was 13.4°. CONCLUSIONS: Percutaneous biopsies guided by EMN and CT fluoroscopy were closely matched for technical success, diagnostic yield, procedure time, and adverse events in a matched cohort of patients. EMN cases were more likely to be performed outside of the gantry plane. Radiation dose to the operator was higher with CT fluoroscopy, and patient radiation dose was higher with EMN. Further study with a wider array of procedures and anatomic locations is warranted.

Electrocardiographic Gating and Cerebral Perfusion Computed Tomography Option-Set Prevalence and Utilization Data From 62 Institutions in the United States.

OBJECTIVES: To provide the radiology community with data to address the question: "Compared with peer institutions, is my institution efficiently using its electrocardiographic (ECG) gating and cerebral perfusion-capable computed tomography (CT) scanners?" METHODS: In this retrospective study, we analyze 6 months of scanner utilization data from 62 institutions (299 locations, 507 scanners) to identify scanners capable of performing ECG gating and perfusion CT studies. We report the number of ECG gating/perfusion-capable scanners and locations as a function of the total number of locations and scanners in each institution. We additionally regress the number of ECG-gated and perfusion examinations on (1) the number of locations/scanners capable of performing these examinations and (2) the fraction of the institution's CT examination volume that requires ECG gating or perfusion. We provide look-up tables so an institution can compare its ECG-gated/perfusion examination volume to other institutions with similar ECG-gated/perfusion examination fractions and capable scanners. RESULTS: We detected an effect of both ECG-gating examination fraction and the number of ECG gating-capable scanners on ECG-gated examination volume ( χ21 = 77.5 [ P < 0.001] and χ21 = 64.2 [ P < 0.001], respectively). Similar results were obtained for perfusion examination fraction and perfusion-capable scanners as they relate to perfusion examination volume ( χ21 = 51.6 [ P < 0.001] and χ21 = 45.2 [ P < 0.001], respectively). The number of ECG gating/perfusion-capable scanners and locations within an institution were found to positively correlate with both the total number of locations and scanners within an institution ( P < 0.001 for all hypothesis tests). CONCLUSIONS: The study provides multi-institutional data on ECG gating and perfusion examination volumes that can be used to inform CT purchasing decisions.

Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.

Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more advanced CT scanners, FBP has become increasingly obsolete. Higher image noise and more artifacts are especially noticeable in lower-dose CT imaging using FBP. This performance gap was partly addressed by model-based iterative reconstruction (MBIR). Yet, its "plastic" image appearance and long reconstruction times have limited widespread application. Hybrid iterative reconstruction partially addressed these limitations by blending FBP with MBIR and is currently the state-of-the-art reconstruction technique. In the past 5 years, deep learning reconstruction (DLR) techniques have become increasingly popular. DLR uses artificial intelligence to reconstruct high-quality images from lower-dose CT faster than MBIR. However, the performance of DLR algorithms relies on the quality of data used for model training. Higher-quality training data will become available with photon-counting CT scanners. At the same time, spectral data would greatly benefit from the computational abilities of DLR. This review presents an overview of the principles, technical approaches, and clinical applications of DLR, including metal artifact reduction algorithms. In addition, emerging applications and prospects are discussed.

Photon count rates estimated from 1980 clinical CT scans.

BACKGROUND: All photon counting detectors have a characteristic count rate over which their performance degrades. Degradation in the clinical setting takes the form of increased noise, reduced material quantification accuracy, and image artifacts. Count rate is a function of patient attenuation, beam filtration, scanner geometry, and X-ray technique. PURPOSE: To guide protocol and technology development in the photon counting space, knowledge of clinical count rates spanning the complete range of clinical indications and patient sizes is needed. In this paper, we use clinical data to characterize the range of computed tomography (CT) count rates. METHODS: We retrospectively gathered 1980 patient exams spanning the entire body (head/neck/chest/abdomen/extremity) and sampled 36 951 axial image slices. We assigned the tissue labels air/lung/fat/soft tissue/bone to each voxel for each slice using CT number thresholds. We then modeled four different bowtie filters, 70/80/100/120/140 kV spectra, and a range of mA values. We forward-projected each slice to obtain detector-incident count rates, using the geometry of a GE Revolution Apex scanner. Our analysis divided the detector into thirds: the central one-third, one-third of the detector split into two equal regions adjacent to the central third, and the final one-third divided equally between the outer detector edges. We report the 99th percentile of counts to mimic the upper limits of count rates making passing through a patient as a function of patient water equivalent diameter. We also report the percentage of patient scans, by body region, over different count rate thresholds for all combinations of bowtie and beam energy. RESULTS: For routine exam types, we recorded count rates of approximately 3.5 × 108  counts/mm2 /s in the torso, extremities, and brain. For neck scans, we observed count rates near 6 × 108  counts/mm2 /s. Our simulations of 1000 mA, appropriately mimicking the mA needs for fast pediatric, fast thoracic, and cardiac scanning, resulted in count rates of over 10 × 108  counts/mm2 /s for the torso, extremities, and brain. At 1000 mA, for the neck region, we observed count rates close to 2 × 109  counts/mm2 /s. Importantly, we saw only a small change in maximum count rate needs over patient size, which we attribute to patient mis-positioning with respect to the bowtie filters. As expected, combinations of kV and bowtie filter with higher beam energies and wider/less attenuating bowtie fluence profiles lead to higher count rates relative to lower energies. The 99th-50th percentile count rate changed the most for the torso region, with a maximum variation of 3.9 × 108 to 1.2 × 107  counts/mm2 /s. The head/neck/extremity regions had less than a 50% change in count rate from the 99th to 50th percentiles. CONCLUSIONS: Our results are the first to use a large patient cohort spanning all body regions to characterize count rates in CT. Our results should be useful in helping researchers understand count rates as a function of body region and mA for various combinations of bowtie filter designs and beam energies. Our results indicate clinical rates >1 × 109  counts/mm2 /s, but they do not predict the image quality impact of using a detector with lower characteristic count rates.

The effect of computed tomography parameters on sarcopenia and myosteatosis assessment: a scoping review.

Computed tomography (CT) is a valuable assessment method for muscle pathologies such as sarcopenia, cachexia, and myosteatosis. However, several key underappreciated scan imaging parameters need consideration for both research and clinical use, specifically CT kilovoltage and the use of contrast material. We conducted a scoping review to assess these effects on CT muscle measures. We reviewed articles from PubMed, Scopus, and Web of Science from 1970 to 2020 on the effect of intravenous contrast material and variation in CT kilovoltage on muscle mass and density. We identified 971 articles on contrast and 277 articles on kilovoltage. The number of articles that met inclusion criteria for contrast and kilovoltage was 11 and 7, respectively. Ten studies evaluated the effect of contrast on muscle density of which nine found that contrast significantly increases CT muscle density (arterial phase 6-23% increase, venous phase 19-57% increase, and delayed phase 23-43% increase). Seven out of 10 studies evaluating the effect of contrast on muscle area found significant increases in area due to contrast (≤2.58%). Six studies evaluating kilovoltage on muscle density found that lower kilovoltage resulted in a higher muscle density (14-40% increase). One study reported a significant decrease in muscle area when reducing kilovoltage (2.9%). The use of contrast and kilovoltage variations can have dramatic effects on skeletal muscle analysis and should be considered and reported in CT muscle analysis research. These significant factors in CT skeletal muscle analysis can alter clinical and research outcomes and are therefore a barrier to clinical application unless better appreciated.