Tomography Attenuation Research Articles

Abstract 12314: Clinical Determinants of Low Attenuation Epicardial Adipose Tissue Volume in Type 2 Diabetes

Introduction: The accumulation of excess epicardial adipose tissue (EAT) is associated with the onset of specific heart failure phenotypes. Subsets of adipocytes in EAT produce an inflammatory secretome which alters the extracellular matrix of the epicardium and impairs myocardial contractility. Lipid-laden adipocytes have a low computed tomography (CT) attenuation and can be readily identified using cardiac CT. Objective: This study sought to identify the clinical and biomarker determinants of low attenuation EAT in participants with Type 2 diabetes (T2D) at risk of heart failure. Methods: Participants with T2D and non-diabetic controls were prospectively recruited to an observational multi-modality cardiovascular imaging study. Deep learning analytics (QFAT, Cedars-Sinai) measured EAT volume and CT attenuation from cardiac CT datasets. Adipose tissue with CT attenuation values of -90 to -190 Hounsfield Units (HU) were classified as low attenuation EAT regions. Comparison was made with anthropometric and blood biomarkers to evaluate determinants of low attenuation EAT. Results: Type 2 diabetic (n=151, median age 64 (59, 69) years, 65% male) and non-diabetic individuals (n=39, median age 59 (54, 66.5) years, 59% male) were recruited. Total EAT volume indexed to body surface area was 1.6-fold higher in diabetics (62.4 (49.1, 77.7) cm 3 /m 2 vs 38.8 (29.6, 51.9) cm 3 /m 2 , p <0.01) and mean CT attenuation was lower (-77.4 +/- 5.2 HU vs -70 +/- 5.4 HU, p <0.01). Larger indexed EAT volume was associated with a lower mean CT attenuation in all participants (r = -0.839, p <0.01). Multivariate analysis identified increasing age, white ethnicity and waist circumference as independent determinants of low attenuation EAT (adjusted R 2 = 0.2003, p <0.01). No association was found with dysglycemia (HbA1c, p = 0.2), dyslipidemia (Triglycerides, p = 0.1) and subclinical inflammation (neutrophil:lymphocyte ratio, p = 0.4). Conclusions: In patients with T2D, indexed EAT volumes are 1.6-fold higher with a lower mean CT attenuation. Age, white ethnicity and waist circumference are associated with low attenuation EAT. Prospective studies are required to determine whether interventions to reduce low attenuation EAT will prevent the onset of heart failure.

Deep-learning image-reconstruction algorithm for dual-energy CT angiography with reduced iodine dose: preliminary results

To evaluate the computed tomography (CT) attenuation values, background noise, arterial depiction, and image quality in whole-body dual-energy CT angiography (DECTA) at 40 keV with a reduced iodine dose using deep-learning image reconstruction (DLIR) and compare them with hybrid iterative reconstruction (IR). Whole-body DECTA with a reduced iodine dose (200 mg iodine/kg) was performed in 22 patients, and DECTA data at 1.25-mm section thickness with 50% overlap were reconstructed at 40 keV using 40% adaptive statistical iterative reconstruction with Veo (hybrid-IR group), and DLIR at medium and high levels (DLIR-M and DLIR-H groups). The CT attenuation values of the thoracic and abdominal aortas and iliac artery and background noise were measured. Arterial depiction and image quality on axial, multiplanar reformatted (MPR), and volume-rendered (VR) images were assessed by two readers. Quantitative and qualitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H groups. The vascular CT attenuation values were almost comparable between the three groups (p=0.013-0.97), but the background noise was significantly lower in the DLIR-H group than in the hybrid-IR and DLIR-M groups (p<0.001). The arterial depictions on axial and MPR images and in almost all arteries on VR images were comparable (p=0.14-1). The image quality of axial, MPR, and VR images was significantly better in the DLIR-H group (p<0.001-0.015). DLIR significantly reduced background noise and improved image quality in DECTA at 40 keV compared with hybrid-IR, while maintaining the arterial depiction in almost all arteries.

In situ measurement of gas-borne silicon nanoparticle volume fraction and temperature by spatially and spectrally line-resolved attenuation and emission imaging

In this study, the temperature and volume fraction distributions of liquid silicon nanoparticles in the aerosol flow in gas-phase synthesis were retrieved using tomographic reconstruction of emission and extinction spectra in the 230–700 nm range. Measurements were done in an optically accessible microwave-plasma flow reactor fed with a SiH4/H2/Ar gas mixture. Optical emission and extinction spectra in the visible spectral range were captured along a line perpendicular to the flow direction covering the entire cross-section of the Si particle stream. Particle temperature and volume fraction distributions were determined and the preferred location of the silicon particles in a 1-mm thick zone at the circumference of the cylindric flow was revealed. The combined recording of line-resolved emission/extinction spectra is a promising method for spatially-resolved detection of nanoparticles in combustion or gas-phase synthesis.

Harmonization of PET image reconstruction parameters in simultaneous PET/MRI

ObjectiveSimultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems.MethodThe NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3–7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction.ResultsThe range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively.ConclusionsFor two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters.

Feasibility study of a method for identification and classification of magnesium and aluminum with ME-XRT

The identification of magnesium and aluminum in scrap metal recycling has always been a difficult point. In this paper, a material identification method of multi-energy X-ray transmission (ME-XRT) based on photon counting detector (PCD) and machine learning algorithm was proposed and used to identify and classify magnesium and aluminum. This method includes three main steps: using PCD to obtain X-ray attenuation images of five energy bins, feature extraction, and the machine learning classification. The performance of several machine learning models was compared for the fine-grained classification task. The prediction results demonstrate that the best achieved recognition rates of aluminum and magnesium are 96.43% and 98.81%, respectively.

Assessment of the inter-platform reproducibility of ultrasound attenuation examination in nonalcoholic fatty liver disease.

PurposeThis study aimed to assess the inter-platform reproducibility of ultrasound attenuation examination in patients with nonalcoholic fatty liver disease (NAFLD).MethodsBetween March 2021 and April 2021, patients with clinically suspected or known NAFLD were prospectively enrolled; each patient underwent ultrasound attenuation examinations with three different platforms (Attenuation Imaging [ATI], Canon Medical System; Tissue Attenuation Imaging [TAI], Samsung Medison; and Ultrasound-Guided Attenuation Parameter [UGAP], GE Healthcare) on the same day. The mean attenuation coefficient (AC) values of the three platforms were compared using repeated-measures analysis of variance with the Bonferroni correction. To evaluate inter-platform reproducibility, the AC values obtained for each platform were compared using Bland-Altman analysis with the calculation of 95% limits of agreement (LOA), intraclass correlation coefficients (ICCs), and coefficients of variation (CVs).ResultsForty-six patients (23 men; mean age±standard deviation, 52.3±12.4 years) were enrolled. The mean AC values showed significant differences among the three platforms (0.75±0.12, 0.80±0.11, and 0.74±0.09 dB/cm/MHz for ATI, TAI, and UGAP, respectively; P<0.001). For inter-platform reproducibility, the 95% LOAs were -0.22 to 0.11 dB/cm/MHz between ATI and TAI, -0.17 to 0.18 dB/cm/MHz between ATI and UGAP, and -0.08 to 0.20 dB/cm/MHz between TAI and UGAP, respectively. The pairwise ICCs were 0.790-0.797 in terms of absolute agreement among the three platforms; the CVs were 8.23%-9.47%.ConclusionThe AC values obtained from different ultrasound attenuation examination platforms showed significant differences, with significant inter-platform variability. Therefore, the AC values measured using different ultrasound attenuation examination techniques should not be used interchangeably for longitudinal follow-up of patients with NAFLD.

Can a ToF-PET photon attenuation reconstruction test stopping-power estimations in proton therapy? A phantom study

Objective. The aim of the phantom study was to validate and to improve the computed tomography (CT) images used for the dose computation in proton therapy. It was tested, if the joint reconstruction of activity and attenuation images of time-of-flight PET (ToF-PET) scans could improve the estimation of the proton stopping-power. Approach. The attenuation images, i.e. CT images with 511 keV gamma-rays (γCTs), were jointly reconstructed with activity maps from ToF-PET scans. The β + activity was produced with FDG and in a separate experiment with proton-induced radioactivation. The phantoms contained slabs of tissue substitutes. The use of the γCTs for the prediction of the beam stopping in proton therapy was based on a linear relationship between the γ-ray attenuation, the electron density, and the stopping-power of fast protons. Main results. The FDG based experiment showed sufficient linearity to detect a bias of bony tissue in the heuristic look-up table, which maps between x-ray CT images and proton stopping-power. γCTs can be used for dose computation, if the electron density of one type of tissue is provided as a scaling factor. A possible limitation is imposed by the spatial resolution, which is inferior by a factor of 2.5 compared to the one of the x-ray CT. γCTs can also be derived from off-line, ToF-PET scans subsequent to the application of a proton field with a hypofractionated dose level. Significance. γCTs are a viable tool to support the estimation of proton stopping with radiotracer-based ToF-PET data from diagnosis or staging. This could be of higher potential relevance in MRI-guided proton therapy. γCTs could form an alternative approach to make use of in-beam or off-line PET scans of proton-induced β + activity with possible clinical limitations due to the low number of coincidence counts.

Noninvasive assessment of hepatic steatosis using a pathologic reference standard: comparison of CT, MRI, and US-based techniques.

PurposeThe present study compared the performance of computed tomography (CT), magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF), controlled attenuation parameter (CAP), grayscale ultrasonography (US), and attenuation imaging (ATI) for the diagnosis of hepatic steatosis (HS).MethodsIn total, 120 prospectively recruited patients who underwent hepatic resection between June 2018 and June 2020 were retrospectively analyzed. CT, MRI-PDFF, CAP, grayscale US, and ATI were performed within 3 months before surgery. Diagnostic performance for HS ≥5% and HS >33% was compared using the area under the curve (AUC) of receiver operating characteristic curves. Histopathologic examinations served as the reference standard for the degree of HS.ResultsFor detecting HS ≥5%, MRI-PDFF (AUC, 0.946) significantly outperformed CT, CAP and grayscale US (AUC, 0.807, 0.829, and 0.761, respectively) (P<0.01 for all). ATI (AUC, 0.892) was the second-best modality and significantly outperformed grayscale US (P=0.001). In pairwise comparisons, there were no significant differences between the AUC of ATI and the values of MRI-PDFF, CT, or CAP (P=0.133, P=0.063, and P=0.150, respectively). For detecting HS >33%, all the modalities provided good diagnostic performance without significant differences (AUC, 0.887-0.947; P>0.05 for all).ConclusionFor detecting HS ≥5%, MRI-PDFF was the best imaging modality, while ATI outperformed grayscale US. For detecting HS >33%, all five imaging tools demonstrated good diagnostic performance.

Feasibility analysis on simultaneous electron density and attenuation coefficient reconstruction.

Creating a viable reconstruction method for Compton scatter tomography remains challenging. Accounting for scatter attenuation when the underlying attenuation map is not known is particularly challenging, and current mathematical approaches to this vary widely. This work explores a novel approach to joint scatter and attenuation image reconstruction, which leverages the underlying structural similarity between the two images and incorporates a deep learning model in an alternating iterative reconstruction scheme. A single-view computed tomography (CT) imaging procedure for recording Compton scatter is first described. A joint reconstruction model, which iterates between algebraically reconstructing scatter images and estimating the attenuation via deep learning, is then proposed. This model is tested on both a generated dataset of 2D phantom images designed to mimic human tissues as well as a realistically simulated dataset based on real CT images. Testing results yield convergence of the model and decent reconstruction quality to distinguish crucial features such as tumors and lesions, demonstrating the potential principled utilities of this configuration and deep learning approach. The model achieved a structural similarity index measure of at least 0.82 for scatter and 0.88 for attenuation reconstructions with the realistically simulated dataset. The iterative, deep learning approach outlined in this work shows potential for future efficient medical imaging procedures, reconstructing images with limited scatter information.

Training-Free Artifact Detection Method for Radio Tomographic Imaging Based Device-Free Localization

Radio tomographic imaging (RTI) is a promising device-free localization (DFL) method by reconstructing an attenuation image from the variations of received signal strength (RSS) measurements. Targets are considered to be at positions of some pixels with local maximums in the attenuation image. However, the number of local maximums generally exceeds the number of real targets, which will lead to large localization errors. The local maximum which does not have its corresponding real target is defined as an “artifact”. Through our analysis, two causes for artifacts are concluded: 1) multi-path interference: RSS measurements for links that are far from the targets may have variations due to multi-path interference, even though these links are not blocked by the targets. 2) intersecting affected links: the affected links blocked by different targets may intersect within the monitoring area, fabricating artifacts. At a position of artifact, there seems to be a target whose interference effect on links is similar to that of a real target. The quality of the attenuation image will deteriorate because of the above two inevitable influencing factors. To alleviate the effect of artifacts, a training-free artifact detection method is proposed. We formulate the artifact detection problem in the attenuation image as a multi-component optimization problem combing the information of feature links and the density of intersection points. The alternating direction method of multipliers (ADMM) is used to derive a closed-form solution. Experiments are conducted to validate the advantages of the proposed artifact detection method.

X-ray bi-prism interferometry-A design study of proposed novel hardware.

Advances in X-ray phase-contrast imaging can obtain excellent soft-tissue contrast of phase-shift, attenuation, and small-angle scatter. Here, we present fringe patterns for different design parameters of X-ray bi-prism interferometry imaging systems. Our aim is to develop bi-prism interferometry imaging systems with excellent polychromatic performance that produce high-contrast fringes with spatially incoherent X-ray illumination. We also introduce a novel X-ray tube design that uses temporal multiplexing to provide simultaneous virtual "electronic phase stepping" that replace "mechanical phase stepping" popular with grating-based interferometry setups. In our investigation, we develop expressions for the irradiance distribution pattern of a bi-prism interferometer composed of multiple point sources and multiple bi-prisms. These expressions are used to plot fringe patterns for X-ray design parameters, including size of point source, number of point sources, and point source separation, and bi-prism design parameters including material, angle, number of bi-prisms, period, and bi-prism array to X-ray source and detector distances. Results show that the fringe patterns for a bi-prism interferometry system are not longitudinally periodic as with grating interferometers that produce a Talbot-Lau carpet. It is also shown that at 59keV X-rays the bi-prism material should be something comparable to nickel to obtain reasonable fringe visibility. The irradiance distribution pattern demonstrates that bi-prism interferometry may provide comparable or improved fringe visibility to that of gratings. Special care is given to present our findings within the context of previous advancements. A single-shot image acquisition approach using a temporal multiplexed, high-power X-ray source provides virtual electronic phase stepping without focal spot sweeping. This provides multiple images, each at the same exposure and the same projection view, from different fringe locations that allow one to derive the attenuation, phase, and dark-field images of the sample without mechanical phase stepping of a grating.

Sn attenuation tomography of southeastern Tibet: new constraints on lithospheric mantle deformation

SUMMARY We have formulated a 2-D Sn attenuation tomographic model to investigate the uppermost mantle shear wave Q and its tectonic implications beneath southeastern Tibet near Namche Barwa. To achieve our objective, we first compute interstation Q values using the two station method (TSM) analysis on 618 station pairs obtained from 26 regional earthquakes (Mw ≥5.5) with epicentral distances ranging from 5° to 15° recorded at 47 seismic stations belonging to the Namche Barwa network (XE network, 2003−2004). Furthermore, the QSn tomographic model is generated by utilizing these interstation Q values. QSn values are varying from 101 to 490 in the region. The tomography image reveals high attenuation (≤200 Q values) in the central region. Regions of low attenuation (&amp;gt;200 Q values) are observed in the southern part and in some small regions beneath the northern side of the study area. Consecutive high-low-high QSn values have been observed in the south part of the Lhasa block. The obtained QSn values, along with the prior isotropic Pn velocity model of the study area, indicate that the scattering effect is causing significant Sn wave energy dissipation due to structural heterogeneity present in the uppermost mantle beneath the region. This may be the result of the break-up of the subducting Indian Plate beneath the area.

Diagnostic performance of ultrasound attenuation imaging for assessing low-grade hepatic steatosis.

To investigate the diagnostic performance of attenuation imaging (ATI) for the assessment of low-grade hepatic steatosis using liver biopsy as the reference standard. The study included 57 potential donor candidates for living liver transplantation who underwent ATI, transient elastography (TE), and liver biopsy for evaluation of hepatic steatosis between February 2020 and April 2020. The attenuation coefficient (AC) from ATI and the controlled attenuation parameter (CAP) from TE were measured for each participant in a random and blind manner. The histologic hepatic fat fraction (HFF) was graded (S0, < 5%; S1, 5-33%; S2, 33-66%; S3, > 66%). The accuracy of ATI for diagnosing hepatic steatosis was compared with that of CAP using ROC analysis. Correlations between AC and HFF were evaluated, and factors affecting AC were determined by linear regression analysis. The median HFF was 3% (range: 0-35%), with 31 (54.4%), 24 (42.0%), and 2 (3.5%) participants being graded as S0, S1, and S2, respectively. The AUCs for the ROCs of AC and CAP for the detection of hepatic steatosis were 0.808 (95% CI: 0.682-0.900) and 0.829 (95% CI: 0.706-0.916), respectively, with the difference not being statistically significant (p = 0.762). AC showed 61.5% of sensitivity and 90.3% of specificity. AC was positively correlated with HFF (p < 0.001). HFF was the only factor significantly affecting AC. ATI showed moderate sensitivity and high specificity in the diagnosis and quantification of hepatic steatosis in low-grade steatosis without fibrosis. Only HFF significantly affected AC. • Attenuation imaging showed moderate sensitivity and high specificity performance in the diagnosis and quantification of hepatic steatosis in low-grade steatosis without fibrosis. • The diagnostic performance of the attenuation coefficient by attenuation imaging did not significantly differ from that of the controlled attenuation parameter by transient elastography in quantifying low-grade steatosis. • The histopathologically determined hepatic fat fraction was the only factor significantly affecting the attenuation coefficient.

Model-data-driven image reconstruction with neural networks for ultrasound computed tomography breast imaging

With the goal of developing an accurate and fast image reconstruction algorithm for ultrasound computed tomography, we combine elements of model- and data-driven approaches and propose a learned method which addresses the disadvantages of both approaches. We design a deep neural network which accounts for a nonlinear forward operator and primal-dual algorithm by its inherent network architecture. The network is trained end-to-end, with ultrasound pressure field data as input to get directly an optimized reconstruction of speed of sound and attenuation images. The training and test data are based on a set of Optical and Acoustic Breast Phantom Database, where we use the image as ground truth and simulate pressure field data according to our forward model. Extensive experiments show that our method achieves significant improvements over state-of-the-art reconstruction methods in this field. Experiments show that the proposed algorithm improves the measures structural similarity measure (SSIM) from 0.74 to 0.95 and root mean squared error (RMSE) from 0.13 to 0.09 on average concerning the speed of sound reconstruction, while it improves the SSIM from 0.60 to 0.94 and RMSE from 0.24 to 0.10 on average in attenuation reconstruction.

A Triple-Modality Ultrasound Computed Tomography Based on Full-Waveform Data for Industrial Processes

Ultrasound computed tomography (USCT) is gaining interests in many application areas in industrial processes. The recent scientific research focuses on the possible uses of USCT for varied fields of industry such as flow monitoring in pipes, non-destructive inspection, and monitoring of stirred tanks chemical processes. Until now, most transmission tomography (UTT) and reflection tomography (URT) have been demonstrated individually for these applications. A full waveform USCT contain large amount of information on process under evaluation. The developed approach in this paper is focusing on demonstration of a triple modality USCT. First, an optimised transmission image is formed by fusion of time-of-flight (TOF) and acoustic attenuation (AA) images. Secondly, a reflection image is being optimised by using the information from the transmission image. This triple modality method enables integration of a shape-based approach obtained by URT mode with the quantitative image-based approach UTT mode. A delicate combination of the different information provided by various features of the full-wave signal offers optimal and increased spatial resolution and provides complementary information. Verification tests have been implemented using experimental phantoms of different combinations, sizes, and shapes, to investigate the qualitative imaging features. Moreover, experiments with different concentrations solutions further validate the quantitative traits to benefit from both reflection and transmission modes. This work displays the potential of the full-waveform USCT for industrial applications.

Anelasticity and Lateral Heterogeneities in Earth's Upper Mantle: Impact on Surface Displacements, Self‐Attraction and Loading, and Ocean Tide Dynamics

AbstractSurface displacement and self‐attraction and loading (SAL) elevation induced by ocean tides are known to be affected by material properties of the solid Earth. Recent studies have shown that, in addition to elasticity, anelasticity considerably impacts surface displacements due to ocean tide loading (OTL). We employ consistent 3D seismic elastic and attenuation tomography models to construct 3D elastic and anelastic earth models, and derive corresponding averaged 1D elastic/anelastic models. We apply these models to systematically study the impact of anelasticity and lateral heterogeneity on M2 OTL displacements and SAL elevation. We find that neglecting lateral heterogeneities highly underestimates displacements and SAL elevation in mid‐ocean‐ridge regions and in some coastal areas of North and Central America. In comparison to PREM, 3D anelastic models can increase the predicted amplitudes of the vertical displacement and SAL elevation by up to 1.5 mm. The increased amplitudes reduce the discrepancy between GPS‐observed OTL displacements and their predictions based on PREM in places like Cornwall (England), Brittany (France), and the Ryukyu Islands (Japan). Applying our results to ocean tides, we discover that the impact on ocean tide dynamics exceeds the predicted SAL elevation correction with an RMS of about 1 mm, reaching an RMS of more than 5 mm in areas like North Atlantic or East Pacific. Due to the fact that such a value reaches the accuracy of modern data‐constrained tidal models, we regard the impact of anelastic shear relaxation as significant in tidal modeling.

The most appropriate region-of-interest position for attenuation coefficient measurement in the evaluation of liver steatosis.

Attenuation imaging (ATI) is a new noninvasive ultrasound technique for assessing steatosis grade (S). However, validated region-of-interest (ROI) sampling strategies are not currently available. We investigated the diagnostic performance of various ATI-ROI positions for determining histopathologic S in patients with nonalcoholic fatty liver disease (NAFLD). This retrospective study included 105 patients with biopsy-proven NAFLD. All attenuation coefficient (AC, dB/cm/MHz) measurements were obtained by the same hepatologist using a commercially available ultrasound system on the same day as liver biopsy. Mean (± standard deviation) age and body mass index of the patients were 53 (± 18) years and 27.1 (± 4.1) kg/m2, respectively. The numbers of patients with steatosis affecting < 5%, 5-33%, 33-66%, and > 66% of hepatocytes were 8, 50, 29, and 18, respectively. The ATI-ROI was placed at three different positions for AC measurement using a dedicated workstation: the upper edge of the area ROI, twice the depth of the liver capsule, and the lower edge of the area ROI. Diagnostic performance was evaluated using the area under the receiver-operating characteristic curve (AUC). The AUCs of AC at the three ATI-ROI positions were 0.734 (95% confidence interval [CI]: 0.470-0.998), 0.750 (0.639-0.861), and 0.878 (0.788-0.968) for S ≥ 1; 0.503 (0.392-0.615), 0.824 (0.741-0.907), and 0.809 (0.724-0.895) for S ≥ 2; and 0.606 (0.486-0.726), 0.849 (0.767-0.932), and 0.737 (0.626-0.848) for S = 3, respectively. For accurate steatosis grade assessment, the ATI-ROI should not be placed at the upper edge of the area ROI.

Quantitative assessment of fatty liver using ultrasound attenuation imaging.

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, with an incidence of 20-40% worldwide, making it a major healthcare problem. Because NAFLD can progress to liver fibrosis and cirrhosis through non-alcoholic steatohepatitis, early detection and monitoring of hepatic steatosis are essential for management of NAFLD patients. Even though conventional B-mode ultrasound (US) has been widely used for the evaluation of NAFLD owing to its safety and easy accessibility, its subjective nature and limited accuracy in detecting mild steatosis are major limitations. To overcome the current limitations of conventional B-mode US, attenuation imaging (ATI) based on two-dimensional B-mode US has been developed. ATI can quantitatively assess the degree of hepatic steatosis by calculating the attenuation coefficient, which reflects the degree of US beam attenuation transmitted into the liver tissue. After the first study was published in 2019, several clinical studies using ATI to evaluate hepatic steatosis have reported promising results. In this review, the basic physics, measurement protocol, and reported diagnostic accuracy of ATI in evaluating hepatic steatosis will be discussed.

Diagnostic accuracy of ultrasound-guided attenuation parameter as a noninvasive test for steatosis in non-alcoholic fatty liver disease.

The purpose of this study was to evaluate the diagnostic accuracy of the ultrasound-guided attenuation parameter (UGAP) using the LOGEQ E10 for hepatic steatosis in non-alcoholic fatty liver disease (NAFLD) patients and directly compare UGAP with attenuation imaging (ATI) and controlled attenuation parameter (CAP). We prospectively analyzed 105 consecutive patients with NAFLD who underwent UGAP, ATI, CAP, and liver biopsy on the same day between October 2019 and April 2021. The diagnostic ability of the UGAP-determined attenuation coefficient (AC) was evaluated using receiver operating characteristic (ROC) curve analysis, and its correlation with ATI-determined AC values or CAP values was investigated. The success rate of UGAP was 100%. The median IQR/med obtained by UGAP was 4.0%, which was lower than that of ATI and CAP (P < 0.0001). The median ACs obtained by UGAP for grades S0 (control), S1, S2, and S3 were 0.590, 0.670, 0.750, and 0.845dB/cm/MHz, respectively, demonstrating a stepwise increase with increasing hepatic steatosis severity (P < 0.0001). The areas under the ROC curve of UGAP for identifying ≥ S1, ≥ S2, and S3 were 0.890, 0.906, and 0.912, respectively, which were significantly better than the results obtained with CAP for identifying S3. Furthermore, the correlation coefficient between UGAP-AC and ATI-AC values was 0.803 (P < 0.0001), indicating a strong relationship. Our results indicate that UGAP has high diagnostic accuracy for detecting and grading hepatic steatosis in patients with NAFLD.

Dosimetry on first clinical dark-field chest radiography.

The purpose of this study was to evaluate the dose characteristic for patient examinations at the first clinical X-ray dark-field chest radiography system and to determine whether the effective patient dose is within a clinically acceptable dose range. A clinical setup for grating-based dark-field chest radiography was constructed and commissioned, operating at a tube voltage of 70kVp. Thermoluminescent dosimeter (TLD) measurements were conducted using an anthropomorphic phantom modeling the reference person to obtain a conversion coefficient relating dose area product (DAP) to effective patient dose at the dark-field system. For 92 patients, the DAP values for posterior-anterior measurements were collected at the dark-field system. Using the previously determined conversion coefficient, the effective dose was calculated. A reference person, modeled by an anthropomorphic phantom, receives an effective dose of 35µSv. For the examined patients, a mean effective dose of 39µSv was found. The effective dose at the clinical dark-field radiography system, generating both attenuation and dark-field images, is within the range of reported standard dose values for chest radiography.