Lifelike PixelPrint phantoms for assessing clinical image quality and dose reduction capabilities of a deep learning CT reconstruction algorithm.

Deep learning CT reconstruction (DLR) has become increasingly popular as a method for improving image quality and reducing radiation exposure. Due to their nonlinear nature, these algorithms result in resolution and noise performance which are object-dependent. Therefore, traditional CT phantoms, which lack realistic tissue morphology, have become inadequate for assessing clinical imaging performance. We propose to utilize 3D-printed PixelPrint phantoms, which exhibit lifelike attenuation profiles, textures, and structures, as a better tool for evaluating DLR performance. In this study, we evaluate a DLR algorithm (Precise Image (PI), Philips Healthcare) using a custom PixelPrint lung phantom and perform head-to-head comparisons between DLR, iterative reconstruction, and filtered back projection (FBP) with scans acquired at a broad range of radiation exposures (CTDIvol: 0.5, 1, 2, 4, 6, 9, 12, 15, 19, and 20 mGy). We compared the performance of each resultant image using noise, peak signal to noise ratio (PSNR), structural similarity index (SSIM), feature-based similarity index (FSIM), information theoretic-based statistic similarity measure (ISSM) and universal image quality index (UIQ). Iterative reconstruction at 9 mGy matches the image quality of FBP at 12 mGy (diagnostic reference level) for all metrics, demonstrating a dose reduction capability of 25%. Meanwhile, DLR matches the image quality of diagnostic reference level FBP images at doses between 4 - 9 mGy, demonstrating dose reduction capabilities between 25% and 67%. This study shows that DLR allows for reduced radiation dose compared to both FBP and iterative reconstruction without compromising image quality. Furthermore, PixelPrint phantoms offer more realistic testing conditions compared to traditional phantoms in the evaluation of novel CT technologies. This, in turn, promotes the translation of new technologies, such as DLR, into clinical practice.

Impact of scatter radiation on spectral quantification performance of first- and second-generation dual-layer spectral computed tomography.

OBJECTIVE: To assess the impact of scatter radiation on quantitative performance of first and second-generation dual-layer spectral computed tomography (DLCT) systems. METHOD: A phantom with two iodine inserts (1 and 2 mg/mL) configured to intentionally introduce high scattering conditions was scanned with a first- and second-generation DLCT. Collimation widths (maximum of 4 cm for first generation and 8 cm for second generation) and radiation dose levels were varied. To evaluate the performance of both systems, the mean CT numbers of virtual monoenergetic images (MonoEs) at different energies were calculated and compared to expected values. MonoEs at 50  versus 150 keV were plotted to assess material characterization of both DLCTs. Additionally, iodine concentrations were determined, plotted, and compared against expected values. For each experimental scenario, absolute errors were reported. RESULTS: An experimental setup, including a phantom design, was successfully implemented to simulate high scatter radiation imaging conditions. Both CT scanners illustrated high spectral accuracy for small collimation widths (1 and 2 cm). With increased collimation (4 cm), the second-generation DLCT outperformed the earlier DLCT system. Further, the spectral performance of the second-generation DLCT at an 8 cm collimation width was comparable to a 4 cm collimation on the first-generation DLCT. A comparison of the absolute errors between both systems at lower energy MonoEs illustrates that, for the same acquisition parameters, the second-generation DLCT generated results with decreased errors. Similarly, the maximum error in iodine quantification was less with second-generation DLCT (0.45  and 0.33 mg/mL for the first and second-generation DLCT, respectively). CONCLUSION: The implementation of a two-dimensional anti-scatter grid in the second-generation DLCT improves the spectral quantification performance. In the clinical routine, this improvement may enable additional clinical benefits, for example, in lung imaging.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm.

Objective. Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels.Method. The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different size extension rings to mimic a small- and medium-sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error, structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image.Results.DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25%-83% in the small phantom and by 50%-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR.Conclusion. DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose, which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

Spectral performance evaluation of a second-generation spectral detector CT.

PURPOSE: The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities. METHODS: A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70 keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150 keV, and root mean square error (RMSE) for adipose and iron content was reported. RESULTS: Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70 keV images demonstrated reduced dependence compared to conventional images for phantom size (1 vs. 27 HU) and acquisition parameters, particularly tube voltage (4 vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44 mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49 ± 1.76% and 1.67 ± 0.84 mg/mL for adipose and iron content, respectively. CONCLUSION: The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Diagnostic accuracy of virtual non-contrast CT for aortic valve stenosis severity evaluation.

BACKGROUND: Computed tomography aortic valve calcium (AVC) score has accepted value for diagnosing and predicting outcomes in aortic stenosis (AS). Multi-energy CT (MECT) allows virtual non-contrast (VNC) reconstructions from contrast scans. We aim to compare the VNC-AVC score to the true non-contrast (TNC)-AVC score for assessing AS severity. METHODS: We prospectively included patients undergoing a MECT for transcatheter aortic valve replacement (TAVR) planning. TNC-AVC was acquired before contrast, and VNC-AVC was derived from a retrospectively gated contrast-enhanced scan. The Agatston scoring method was used for quantification, and linear regression analysis to derive adjusted-VNC values. RESULTS: Among 109 patients (55% female) included, 43% had concordant severe and 14% concordant moderate AS. TNC scan median dose-length product was 116 â€‹mGy∗cm. The median TNC-AVC was 2,107 AU (1,093-3,372), while VNC-AVC was 1,835 AU (1293-2,972) after applying the coefficient (1.46) and constant (743) terms. A strong correlation was demonstrated between methods (r â€‹= â€‹0.93; p â€‹< â€‹0.001). Using accepted thresholds (>1,300 AU for women and >2,000 AU for men), 65% (n â€‹= â€‹71) of patients had severe AS by TNC-AVC and 67% (n â€‹= â€‹73) by adjusted-VNC-AVC. After estimating thresholds for adjusted-VNC (>1,564 AU for women and >2,375 AU for men), 56% (n â€‹= â€‹61) had severe AS, demonstrating substantial agreement with TNC-AVC (κ â€‹= â€‹0.77). CONCLUSIONS: MECT-derived VNC-AVC showed a strong correlation with TNC-AVC. After adjustment, VNC-AVC demonstrated substantial agreement with TNC-AVC, potentially eliminating the requirement for an additional scan and enabling reductions in both radiation exposure and acquisition time.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm.

Objective: Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels. Approach: The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different sized extension rings to mimic a small and medium sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error (RMSE), structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image. Main Results: DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25-83% in the small phantom and by 50-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR with a non-anatomical physics phantom. Significance: DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

Phantom-based quantification of the spectral accuracy in dual-layer spectral CT for pediatric imaging at 100 kVp.

Background: To determine the spectral accuracy in detector-based dual-energy CT (DECT) at 100 kVp and wide (8 cm) collimation width for dose levels and object sizes relevant to pediatric imaging. Methods: A spectral CT phantom containing tissue-equivalent materials and iodine inserts of varying concentrations was scanned on the latest generation detector-based DECT system. Two 3D-printed extension rings were used to mimic varying pediatric patient sizes. Scans were performed at 100 and 120 kVp, 4 and 8 cm collimation widths, and progressively reduced radiation dose levels, down to 0.9 mGy CTDIvol. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were quantified and compared to their expected values for all acquisition settings and phantom sizes. Results: DECT scans at 100 kVp provided highly accurate spectral results; however, a size dependence was observed for iodine quantification. For the medium phantom configuration (15 cm diameter), measurement errors in iodine density, effective atomic number, and electron density (ED) were below 0.3 mg/mL, 0.2 and 1.8 %EDwater, respectively. The average accuracy was slightly different from scans at 120 kVp; however, not statistically significant for all configurations. Collimation width had no substantial impact. Spectral results were accurate and reliable for radiation exposures down to 0.9 mGy CTDIvol. Conclusions: Detector-based DECT at 100 kVp can provide on-demand or retrospective spectral information with high accuracy even at extremely low doses, thereby making it an attractive solution for pediatric imaging.

Principles and applications of multienergy CT: Report of AAPM Task Group 291.

In x-ray computed tomography (CT), materials with different elemental compositions can have identical CT number values, depending on the mass density of each material and the energy of the detected x-ray beam. Differentiating and classifying different tissue types and contrast agents can thus be extremely challenging. In multienergy CT, one or more additional attenuation measurements are obtained at a second, third or more energy. This allows the differentiation of at least two materials. Commercial dual-energy CT systems (only two energy measurements) are now available either using sequential acquisitions of low- and high-tube potential scans, fast tube-potential switching, beam filtration combined with spiral scanning, dual-source, or dual-layer detector approaches. The use of energy-resolving, photon-counting detectors is now being evaluated on research systems. Irrespective of the technological approach to data acquisition, all commercial multienergy CT systems circa 2020 provide dual-energy data. Material decomposition algorithms are then used to identify specific materials according to their effective atomic number and/or to quantitate mass density. These algorithms are applied to either projection or image data. Since 2006, a number of clinical applications have been developed for commercial release, including those that automatically (a) remove the calcium signal from bony anatomy and/or calcified plaque; (b) create iodine concentration maps from contrast-enhanced CT data and/or quantify absolute iodine concentration; (c) create virtual non-contrast-enhanced images from contrast-enhanced scans; (d) identify perfused blood volume in lung parenchyma or the myocardium; and (e) characterize materials according to their elemental compositions, which can allow in vivo differentiation between uric acid and non-uric acid urinary stones or uric acid (gout) or non-uric acid (calcium pyrophosphate) deposits in articulating joints and surrounding tissues. In this report, the underlying physical principles of multienergy CT are reviewed and each of the current technical approaches are described. In addition, current and evolving clinical applications are introduced. Finally, the impact of multienergy CT technology on patient radiation dose is summarized.

High correlation between radiation dose estimates for 256-slice CT obtained by highly parallelized hybrid Monte Carlo computation and solid-state metal-oxide semiconductor field-effect transistor measurements in physical anthropomorphic phantoms.

PURPOSE: Accurate, patient-specific radiation dosimetry for CT scanning is critical to optimize radiation doses and balance dose against image quality. While Monte Carlo (MC) simulation is often used to estimate doses from CT, comparison of estimates to experimentally measured values is lacking for advanced CT scanners incorporating novel design features. We aimed to compare radiation dose estimates from MC simulation to doses measured in physical anthropomorphic phantoms using metal-oxide semiconductor field-effect transistors (MOSFETs) in a 256-slice CT scanner. METHODS: Fifty MOSFETs were placed in organs within tissue-equivalent anthropomorphic adult and pediatric radiographic phantoms, which were scanned using a variety of chest, cardiac, abdomen, brain, and whole-body protocols on a 256-slice system. MC computations were performed on voxelized CT reconstructions of the phantoms using a highly parallel MC tool developed specifically for diagnostic X-ray energies and rapid computation. Doses were compared between MC estimates and physical measurements. RESULTS: The average ratio of MOSFET to MC dose in the in-field region was close to 1 (range, 0.96-1.12; mean ± SD, 1.01 ± 0.04), indicating outstanding agreement between measured and simulated doses. The difference between measured and simulated doses tended to increase with distance from the in-field region. The error in the MC simulations due to the limited number of simulated photons was less than 1%. The errors in the MOSFET dose determinations in the in-field region for a single scan were mainly due to the calibration method and were typically about 6% (8% if the error in the reading of the ionization chamber that was used for the MOSFET calibration was included). CONCLUSIONS: Radiation dose estimation using a highly parallelized MC method is strongly correlated with experimental measurements in physical adult and infant anthropomorphic phantoms for a wide range of scans performed on a 256-slice CT scanner. Incorporation into CT scanners of radiation-dose distribution estimation, employing the scanner's reconstructed images of the patient, may offer the potential for accurate patient-specific CT dosimetry.

The role of advanced reconstruction algorithms in cardiac CT.

Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice.

Calibration and error analysis of metal-oxide-semiconductor field-effect transistor dosimeters for computed tomography radiation dosimetry.

PURPOSE: Metal-oxide-semiconductor field-effect transistors (MOSFETs) serve as a helpful tool for organ radiation dosimetry and their use has grown in computed tomography (CT). While different approaches have been used for MOSFET calibration, those using the commonly available 100 mm pencil ionization chamber have not incorporated measurements performed throughout its length, and moreover, no previous work has rigorously evaluated the multiple sources of error involved in MOSFET calibration. In this paper, we propose a new MOSFET calibration approach to translate MOSFET voltage measurements into absorbed dose from CT, based on serial measurements performed throughout the length of a 100-mm ionization chamber, and perform an analysis of the errors of MOSFET voltage measurements and four sources of error in calibration. METHODS: MOSFET calibration was performed at two sites, to determine single calibration factors for tube potentials of 80, 100, and 120 kVp, using a 100-mm-long pencil ion chamber and a cylindrical computed tomography dose index (CTDI) phantom of 32 cm diameter. The dose profile along the 100-mm ion chamber axis was sampled in 5 mm intervals by nine MOSFETs in the nine holes of the CTDI phantom. Variance of the absorbed dose was modeled as a sum of the MOSFET voltage measurement variance and the calibration factor variance, the latter being comprised of three main subcomponents: ionization chamber reading variance, MOSFET-to-MOSFET variation and a contribution related to the fact that the average calibration factor of a few MOSFETs was used as an estimate for the average value of all MOSFETs. MOSFET voltage measurement error was estimated based on sets of repeated measurements. The calibration factor overall voltage measurement error was calculated from the above analysis. RESULTS: Calibration factors determined were close to those reported in the literature and by the manufacturer (~3 mV/mGy), ranging from 2.87 to 3.13 mV/mGy. The error σV of a MOSFET voltage measurement was shown to be proportional to the square root of the voltage V: σV=cV where c = 0.11 mV. A main contributor to the error in the calibration factor was the ionization chamber reading error with 5% error. The usage of a single calibration factor for all MOSFETs introduced an additional error of about 5-7%, depending on the number of MOSFETs that were used to determine the single calibration factor. The expected overall error in a high-dose region (~30 mGy) was estimated to be about 8%, compared to 6% when an individual MOSFET calibration was performed. For a low-dose region (~3 mGy), these values were 13% and 12%. CONCLUSIONS: A MOSFET calibration method was developed using a 100-mm pencil ion chamber and a CTDI phantom, accompanied by an absorbed dose error analysis reflecting multiple sources of measurement error. When using a single calibration factor, per tube potential, for different MOSFETs, only a small error was introduced into absorbed dose determinations, thus supporting the use of a single calibration factor for experiments involving many MOSFETs, such as those required to accurately estimate radiation effective dose.

Practical considerations for optimizing cardiac computed tomography protocols for comprehensive acquisition prior to transcatheter aortic valve replacement.

Transcatheter aortic valve replacement (TAVR) is performed frequently in patients with severe, symptomatic aortic stenosis who are at high risk or inoperable for open surgical aortic valve replacement. Computed tomography angiography (CTA) has become the gold standard imaging modality for pre-TAVR cardiac anatomic and vascular access assessment. Traditionally, cardiac CTA has been most frequently used for assessment of coronary artery stenosis, and scanning protocols have generally been tailored for this purpose. Pre-TAVR CTA has different goals than coronary CTA and the high prevalence of chronic kidney disease in the TAVR patient population creates a particular need to optimize protocols for a reduction in iodinated contrast volume. This document reviews details which allow the physician to tailor CTA examinations to maximize image quality and minimize harm, while factoring in multiple patient and scanner variables which must be considered in customizing a pre-TAVR protocol.

Absence of coronary sinus tributaries in ischemic cardiomyopathy: An insight from multidetector computed tomography cardiac venographic study.

OBJECTIVE: Cardiac resynchronization therapy (CRT) is an important therapeutic strategy in heart failure. However, there is a high incidence of lead implantation failure and suboptimal response, particularly in ischemic cardiomyopathy. This failure rate may partly be secondary to lack of suitable coronary sinus branches for lead implantation. We sought to assess the presence of coronary sinus (CS) tributaries in patients with ischemic and non-ischemic cardiomyopathy. MATERIALS AND METHODS: Multidetector computed tomography (MDCT) was performed in 100 patients: 25 coronary artery bypass graft (CABG) patients with impaired left ventricular ejection fraction (LVEF), 25 CABG patients with preserved LVEF, 25 patients with non-ischemic cardiomyopathy, and 25 controls. The presence of the CS and its tributaries, including the posterior interventricular vein (PIV), posterolateral vein (PLV), left marginal vein (LMV), and the anterior interventricular vein (AIV) was assessed. RESULTS: The CS, PIV, and AIV were demonstrated in all patients, whereas presence of a PLV and LMV was identified in 68% and 48% of CABG patients with impaired LVEF, 96% and 68% of CABG patients with preserved LVEF, 92% and 80% of patients with non-ischemic cardiomyopathy, and 100% and 80% of controls (p = 0.001 and 0.046 for PLV and LMV, respectively). CONCLUSIONS: This is the first report to demonstrate that the posterolateral vein and left middle vein, branches of the coronary sinus, are detectable in a significantly smaller number of CABG patients with impaired LVEF compared to controls, CABG with preserved LVEF, and non-ischemic cardiomyopathy. The absence of CS tributary veins in ischemic cardiomyopathy potentially hinders proper lead implantation and results in suboptimal CRT response.

A pilot study of patient-specific cardiovascular MDCT dose maps and their utility in estimating patient-specific organ and effective doses in obese patients.

BACKGROUND: Estimates of effective dose (E) for cardiovascular CT are obtained from a scanner-provided dose metric, the dose-length product (DLP), and a conversion factor. These estimates may not adequately represent the risk of a specific scan to obese adults. OBJECTIVE: Our objective was to create dose maps sensitive to patient size and anatomy in the irradiated region from a patient's own CT images and compare measured E (EDoseMap) to doses determined from standard DLP conversion (EDLP) in obese adults. METHODS: 21 obese patients (mean body mass index, 39 kg/m(2)) underwent CT of the pulmonary veins, thoracic aorta, or coronary arteries. DLP values were converted to E. A Monte Carlo tool was used to simulate X-ray photon interaction with virtual phantoms created from each patient's image set. Organ doses were determined from dose maps. EDoseMap was computed as a weighted sum of organ doses multiplied by tissue-weighting factors. RESULTS: EDLP (mean ± SD, 5.7 ± 3.3 mSv) was larger than EDoseMap (3.4 ± 2.4 mSv) (difference = 2.3; P < .001). CONCLUSION: Dose maps derived from patient CT images yielded lower effective doses than DLP conversion methods. Considering over all patient size, organ size, and tissue composition could lead to better dose metrics for obese patients.

Manual, semiautomated, and fully automated measurement of the aortic annulus for planning of transcatheter aortic valve replacement (TAVR/TAVI): analysis of interchangeability.

BACKGROUND: Preprocedural 3-dimensional CT imaging of the aortic annular plane plays a critical role for transcatheter aortic valve replacement (TAVR) planning; however, manual reconstructions are complex. Automated analysis software may improve reproducibility and agreement between readers but is incompletely validated. METHODS: In 110 TAVR patients (mean age, 81 years; 37% female) undergoing preprocedural multidetector CT, automated reconstruction of the aortic annular plane and planimetry of the annulus was performed with a prototype of now commercially available software (syngo.CT Cardiac Function-Valve Pilot; Siemens Healthcare, Erlangen, Germany). Fully automated, semiautomated, and manual annulus measurements were compared. Intrareader and inter-reader agreement, intermodality agreement, and interchangeability were analyzed. Finally, the impact of these measurements on recommended valve size was evaluated. RESULTS: Semiautomated analysis required major correction in 5 patients (4.5%). In the remaining 95.5%, only minor correction was performed. Mean manual annulus area was significantly smaller than fully automated results (P < .001 for both readers) but similar to semiautomated measurements (5.0 vs 5.4 vs 4.9 cm(2), respectively). The frequency of concordant recommendations for valve size increased if manual analysis was replaced with the semiautomated method (60% agreement was improved to 82.4%; 95% confidence interval for the difference [69.1%-83.4%]). CONCLUSIONS: Semiautomated aortic annulus analysis, with minor correction by the user, provides reliable results in the context of TAVR annulus evaluation.

Adaptation of contrast injection protocol to tube potential for cardiovascular CT.

OBJECTIVE: The purpose of this study was to investigate and validate adaptation of a cardiovascular CT angiography contrast injection protocol for lower tube potential. MATERIALS AND METHODS: Eighty-three patients evaluated for thoracic aortic disease with a 256-MDCT scanner were imaged at 120 kV (group 1) or 100 kV (group 2) with the same contrast protocol (90 mL iopromide 370 mg I/mL at 3.5 mL/s). A pharmacokinetic model was validated and used to simulate aortic attenuation in group 2 patients with 20%, 33%, and 44% reduction in contrast volume. A 44% volume reduction was applied to 50 additional patients who underwent imaging at 100 kV (group 3). Patient characteristics, scanning and radiation parameters, and objective and subjective image indexes were compared among groups. RESULTS: Group 2 patients had higher mean aortic blood attenuation (399±61 HU) than group 1 patients (281±48 HU) (p<0.001) but similar image noise. Group 3 and group 1 patients had similar mean aortic attenuation and noise. Subjective assessment of image quality indicated that group 3 and group 1 had comparable percentages of images with good or excellent diagnostic confidence scores (reader 1, 98% vs 96%; reader 2, 96% vs 96%). CONCLUSION: Lower tube potential (100 kV) for cardiothoracic CT could be accompanied by a 44% reduction in contrast volume with satisfactory aortic blood-pool attenuation in most patients. More personalized adaptation of the contrast protocol that takes into account patient characteristics and tube potential is necessary to ensure sufficient contrast enhancement for all patients.

Patient-centered imaging: shared decision making for cardiac imaging procedures with exposure to ionizing radiation.

The current paper details the recommendations arising from an NIH-NHLBI/NCI-sponsored symposium held in November 2012, aiming to identify key components of a radiation accountability framework fostering patient-centered imaging and shared decision-making in cardiac imaging. Symposium participants, working in 3 tracks, identified key components of a framework to target critical radiation safety issues for the patient, the laboratory, and the larger population of patients with known or suspected cardiovascular disease. The use of ionizing radiation during an imaging procedure should be disclosed to all patients by the ordering provider at the time of ordering, and reinforced by the performing provider team. An imaging protocol with effective dose ≤3 mSv is considered very low risk, not warranting extensive discussion or written informed consent. However, a protocol effective dose >20 mSv was proposed as a level requiring particular attention in terms of shared decision-making and either formal discussion or written informed consent. Laboratory reporting of radiation dosimetry is a critical component of creating a quality laboratory fostering a patient-centered environment with transparent procedural methodology. Efforts should be directed to avoiding testing involving radiation, in patients with inappropriate indications. Standardized reporting and diagnostic reference levels for computed tomography and nuclear cardiology are important for the goal of public reporting of laboratory radiation dose levels in conjunction with diagnostic performance. The development of cardiac imaging technologies revolutionized cardiology practice by allowing routine, noninvasive assessment of myocardial perfusion and anatomy. It is now incumbent upon the imaging community to create an accountability framework to safely drive appropriate imaging utilization.

High-pitch ECG-synchronized pulmonary CT angiography versus standard CT pulmonary angiography: a prospective randomized study.

OBJECTIVE: The purpose of this study was to compare high-pitch ECG-synchronized pulmonary CT angiography (CTA) with standard pulmonary CTA with regard to radiation dose and image quality in patients with suspected pulmonary embolism. SUBJECTS AND METHODS: This prospective study was approved by the institutional review board, and participants provided informed consent. Patients with suspected pulmonary embolism (60% women; mean age, 57 ± 14 years) were randomized to undergo high-pitch ECG-synchronized pulmonary CTA (n = 26) or standard pulmonary CTA (n = 21). Two independent readers assessed subjective image quality of pulmonary arteries, cardiovascular structures, and pulmonary parenchyma. Signal intensity (SI) was measured in one segmental and three central pulmonary arteries. RESULTS: High-pitch ECG-synchronized pulmonary CTA showed higher SI (p < 0.001) for pulmonary arteries. Image quality scores indicated improvement in assessment of cardio-vascular structures (p < 0.001), minimization of motion of central (p < 0.001) pulmonary arteries, and an increase in pulmonary arterial enhancement (p = 0.01) with high-pitch ECG-synchronized pulmonary CTA. Image quality scores for lung assessment were higher for standard pulmonary CTA (p < 0.001). The amount of contrast agent administered was similar between techniques (p = 0.86). Radiation dose was lower for high-pitch ECG-synchronized pulmonary CTA (p < 0.001). CONCLUSION: High-pitch ECG-synchronized pulmonary CTA provides higher pulmonary arterial SI, decreased motion of central pulmonary arteries, and improved assessment of cardiovascular structures with similar contrast dose and lower radiation compared with standard pulmonary CTA.

Adaptation of the contrast injection protocol to tube potential for cardiovascular computed tomography.

To investigate the adaptation of the contrast injection protocol for lower tube potential at cardiovascular computed tomography (CT) angiography, this study analyzed 83 patients (56 100kV vs. 27 120kV) imaged with a prospectively ECG-triggered axial technique for evaluation of aortic disease on a 256-slice CT scanner from 4/10/12 to 5/23/12. A custom algorithm was used to select tube potential and tube current based on patient size. The same contrast injection protocol (contrast concentration 370 mgI/mL, flow rate = 3.5 mL/s, volume = 90 mL) was applied to both cohorts. A Bae-Heiken-Brink pharmacokinetic model was utilized to simulate attenuation in the aorta for the applied contrast protocol in both cohorts and for 3 reduced volumes in the 100kV cohort (A: 72mL, -20%; B: 60mL, -33%; C: 50mL, -44%). Quantitative analysis revealed that 100kV cohort had significantly higher contrast attenuation and signal-to-noise ratio than the 120kV cohort but similar image noise. Simulation of protocol A and B in the 100kV cohort yielded significantly higher attenuation than that measured from the 120kV cohort (p<0.05); attenuation with protocol C showed no significant difference. Simulation results demonstrated that the amount of contrast material can be reduced by as much as 44% for 100 compared to 120 kV imaging but still yielded similar aortic attenuation. A prospective, randomized study should be conducted to validate the performance of the proposed contrast injection protocol at 100kV.