Feasibility and accuracy of dual-layer spectral detector computed tomography for quantification of gadolinium: a phantom study.
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ABSTRACT:
SUBMITTER: van Hamersvelt RW
PROVIDER: S-EPMC5544796 | biostudies-other | 2017 Sep
REPOSITORIES: biostudies-other
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Project description:BackgroundTo 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.MethodsA 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.ResultsDECT 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.ConclusionsDetector-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.
| S-EPMC9929380 | biostudies-literature
Project description:BackgroundVirtual monoenergetic images (VMIs) at a low energy level can improve image quality when the amount of iodinated contrast media (CM) is reduced. The purpose was to evaluate the feasibility of using an extremely low CM volume and injection rate in cerebral computed tomography angiography (CTA) on a dual-layer spectral detector computed tomography (CT).MethodsPatients who were clinically suspected of intracranial aneurysm or cerebrovascular diseases were included in our study (from June to November 2022). In this prospective study, 80 patients were randomly enrolled into group A (8 mL of CM with a 1-mL/s flow rate) or group B (40 mL of CM with 4-mL/s flow rate). The VMIs at 40-70 keV in group A and polychromatic conventional images in the 2 groups were reconstructed. CT attenuation, image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated via the t-test or Mann-Whitney test (2 groups), while analysis of variance or Kruskal-Wallis test (multiple groups). Subjective image quality was assessed on a 5-point scale.ResultsIn group A, the subjective image quality score, CT attenuation, and CNR of the internal carotid artery (ICA) and middle cerebral artery (MCA) were the highest on VMIs at 40 keV. The image noise on VMIs at 40 keV was 5.08±0.84 Hounsfield units. The subjective image quality score, CT value of the ICA, MCA, and cerebral parenchyma on VMIs at 40 keV in group A were similar to those in group B (all P values >0.05). Compared to those in group B, the VMIs at 40 keV in group A demonstrated a significantly higher mean SNR and CNR of the ICA (mean SNR: 46.22±20.18 vs. 34.32±12.40, P=0.002; CNR: 55.47±13.43 vs. 46.18±12.30, P=0.002) and MCA [SNR: 13.66 (9.78, 20.29) vs. 9.99 (7.53, 14.00), P=0.003; CNR: 47.00±12.71 vs. 39.45±10.47, P=0.005].ConclusionsCerebral CTA on VMIs at 40 keV with 8 mL of CM and a 1-mL/s injection rate can provide diagnostic image quality.
| S-EPMC10784050 | biostudies-literature
Project description:Dual-energy CT allows for the reconstruction of virtual non-contrast (VNC) images. VNC images have the potential to replace true non-contrast scans in various clinical applications. This study investigated the quantitative accuracy of VNC attenuation images considering different parameters for acquisition and reconstruction. An abdomen phantom with 7 different tissue types (different combinations of 3 base materials and 5 iodine concentrations) was scanned using a spectral detector CT (SDCT). Different phantom sizes (S, M, L), volume computed tomography dose indices (CTDIvol 10, 15, 20 mGy), kernel settings (soft, standard, sharp), and denoising levels (low, medium, high) were tested. Conventional and VNC images were reconstructed and analyzed based on regions of interest (ROI). Mean and standard deviation were recorded and differences in attenuation between corresponding base materials and VNC was calculated (VNCerror). Statistic analysis included ANOVA, Wilcoxon test and multivariate regression analysis. Overall, the VNCerror was -?1.4?±?6.1 HU. While radiation dose, kernel setting, and denoising level did not influence VNCerror significantly, phantom size, iodine content and base material had a significant effect (e.g. S vs. M: -?1.2?±?4.9 HU vs. -?2.1?±?6.0 HU; 0.0 mg/ml vs. 5.0 mg/ml: -?4.0?±?3.5 HU vs. 5.1?±?5.0 HU and 35-HU-base vs. 54-HU-base: -?3.5?±?4.4 HU vs. 0.7?±?6.5; all p???0.05). The overall accuracy of VNC images from SDCT is high and independent from dose, kernel, and denoising settings; however, shows a dependency on patient size, base material, and iodine content; particularly the latter results in small, yet, noticeable differences in VNC attenuation.
| S-EPMC7725817 | biostudies-literature
Project description:BackgroundIt is difficult to distinguish the pathological grade of lung adenocarcinoma (LUAD) with traditional computed tomography (CT). The aim of this study was to assess tumor differentiation by dual-layer spectral detector CT combined with morphological parameters.MethodsIn this prospective study, a total of 67 patients with pathologically diagnosed LUAD were enrolled: 39 patients in the well- and moderately-differentiated group (14 and 25 patients, respectively) and 28 patients in the poorly-differentiated group. Morphological parameters, non-enhanced CT number, double-enhanced CT number, effective atomic number, monoenergetic CT images (40 and 70 keV), iodine density, and thoracic aorta iodine density of tumors were measured. The slope of the spectral curve and normalized iodine density were calculated. The diagnostic efficiency of the spectral parameters alone, and the combined spectral and morphological parameters were obtained by statistical analysis.ResultsThe morphological signs of LUAD (the vessel convergence sign, bronchus encapsulated air sign, and liquefactive necrosis) were higher in the poorly-differentiated group than in the well-moderately-differentiated group (57.1% vs. 30.8%, 40.0%; 60.7% vs. 28.2%, 32.0%; 64.3% vs. 28.2%, 24.0%; all P<0.05). There were significant differences in normalized iodine density (arterial phase: 0.10±0.04 vs. 0.12±0.05, 0.13±0.04; venous phase: 0.31±0.07 vs. 0.39±0.17, 0.40±0.17) among the poorly-differentiated group and moderately-differentiated group as well as the well-differentiated group (all P<0.05). Receiver operating characteristic (ROC) curves of the poorly-differentiated group and well-moderately-differentiated group showed that the normalized iodine density had the best diagnostic efficiency in the arterial phase, with an area under the curve (AUC) of 0.817, sensitivity of 92.9%, and specificity of 82.1% (P<0.001). The AUC increased to 0.916 when the morphological parameters were included, and sensitivity and specificity were 96.4% and 82.1% (P<0.001), respectively.ConclusionsThe parameters of dual-layer spectral detector CT can help discriminate the pathological grade of LUAD. Among the spectral parameters, the normalized iodine density in the arterial phase has the best diagnostic efficiency, and the combination of spectral and morphological parameters improves the pathological grading of LUAD.
| S-EPMC9403580 | biostudies-literature
Project description:BackgroundCoronary atherosclerosis is a chronic inflammatory condition. Pericoronary adipose tissue (PCAT) attenuation is closely related to coronary inflammation. This study aimed to investigate the relationship between PCAT attenuation parameters and coronary atherosclerotic heart disease (CAD) using dual-layer spectral detector computed tomography (SDCT).MethodsThis cross-sectional study included eligible patients who underwent coronary computed tomography angiography using SDCT at the First Affiliated Hospital of Harbin Medical University between April 2021 and September 2021. Patients were classified as CAD (with coronary artery atherosclerotic plaque) or non-CAD (without coronary artery atherosclerotic plaque). Propensity score matching was used to match the two groups. The fat attenuation index (FAI) was used to quantify PCAT attenuation. The FAI was measured on conventional images (120 kVp) and virtual monoenergetic images (VMI) by semiautomatic software. The slope of the spectral attenuation curve (λ) was calculated. Regression models were established to evaluate the predictive value of PCAT attenuation parameters for CAD.ResultsA total of 45 patients with CAD and 45 patients without CAD were enrolled. The PCAT attenuation parameters in the CAD group were significantly higher than those in the non-CAD group (all P values <0.05). The PCAT attenuation parameters of vessels with or without plaques in the CAD group were higher than those of vessels without plaques in the non-CAD group (all P values <0.05). In the CAD group, the PCAT attenuation parameters of vessels with plaques were slightly higher than those of vessels without plaques (all P values >0.05). In receiver operating characteristic curve analysis, the FAIVMI model achieved an area under the curve (AUC) of 0.8123 for discriminating between patients with and without CAD, which was higher than those of the FAI120 kVp model (AUC =0.7444) and the λ model (AUC =0.7230). However, the combined model of FAIVMI, FAI120 kVp, and λ obtained the best performance (AUC =0.8296) of all the models.ConclusionsPCAT attenuation parameters obtained using dual-layer SDCT can aid in distinguishing patients with and without CAD. By detecting increases in PCAT attenuation parameters, it might be possible to predict the formation of atherosclerotic plaques before they appear.
| S-EPMC10167438 | biostudies-literature
Project description:BackgroundKi-67 and human epidermal growth factor receptor 2 (HER2) are key biomarkers in evaluating the prognosis of colorectal adenocarcinoma (CRAC). The purpose of this study was to investigate the value of quantitative parameters in dual-layer spectral detector computed tomography (SDCT) for evaluating the expression of Ki-67 and HER2 in CRAC.MethodsIn this retrospective, cross-sectional study, 88 eligible patients with pathologically confirmed CRAC were selected from Taicang Hospital of Traditional Chinese Medicine between May 2021 and April 2023. The study participants underwent enhanced SDCT of the whole abdomen within 2 weeks before to surgery, did not receive antitumor therapy, and had complete immunohistochemical (IHC) indexes. Patients with nonadenocarcinoma pathologic types, poor quality of spectral CT images, or no complete immunohistochemistry results were excluded. Spectral parameters including CT values at 40 and 100 keV, effective atomic number, iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP) were analyzed for their value in distinguishing between the high and low expression of Ki-67 and HER2-positive and -negative status in CRAC. The statistical significance of the SDCT parameters between the different groups of Ki-67 expression and those of HER2 status was assessed with the Mann-Whitney test. Spearman correlation analysis was used to analyze the correlation between the SDCT parameters and the extent of Ki-67 expression and HER2 expression status. The receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated.ResultsThe SDCT parameters of CT values at 40 keV, effective atomic number, IC, and the λHU in the VP showed significant differences between the Ki-67 high- and low-expression groups in CRAC (P=0.035, P=0.041, P=0.036, and P=0.044, respectively), with AUCs of 0.639 [95% confidence interval (CI): 0.512-0.766], 0.634 (95% CI: 0.508-0.761), 0.638 (95% CI: 0.510-0.766), and 0.633 (95% CI: 0.504-0.762), respectively. The expression of CRAC Ki-67 was positively correlated with CT values at 40 keV (r=0.227; P=0.034), effective atomic number (r=0.219; P=0.040), IC (r=0.225; P=0.035), and the λHU in VP (r=0.216; P=0.043). SDCT parameter values showed no statistical difference between negative and positive expression in HER2 (all P values >0.05). There was no significant correlation between SDCT parameters and the expression of HER2 in CRAC (all P values >0.05).ConclusionsThe quantitative parameters of SDCT in the VP provide valuable information for distinguishing between the low expression and high expression of Ki-67 in CRAC.
| S-EPMC10784054 | biostudies-literature
Project description:Background and aims The triglyceride-glucose (TyG) index is a reliable alternative marker for insulin resistance (IR). Pericoronary adipose tissue (PCAT) can indirectly reflect coronary inflammation. IR and coronary inflammation play a key role in the development and progression of coronary atherosclerosis. Therefore, this study investigated the relationships between the TyG index, PCAT and atherosclerotic plaque characteristics to explore whether IR might lead to coronary artery atherosclerosis progression by inducing coronary inflammation. Methods We retrospectively collected data on patients with chest pain who underwent coronary computed tomography angiography using spectral detector computed tomography at our institution from June to December 2021. The patients were grouped based on their TyG index levels: T1 (low), T2 (medium), and T3 (high). Each patient was assessed for total plaque volume, plaque load, maximum stenosis, the plaque component volume proportion, high-risk plaques(HRPs), and plaque characteristics (including low attenuation plaques, positive remodeling, a napkin ring sign, and spot calcification). PCAT quantification was performed on the proximal right coronary artery using the fat attenuation index (FAI) measured from a conventional multicolor computed tomography image (FAI120kVp), a spectral virtual single-energy image (FAI40keV), and the slope of the spectral HU curve (λHU). Results We enrolled 201 patients. The proportion of patients with maximum plaque stenosis, positive remodeling, low-density plaques, and HRPs increased as the TyG index level increased. Moreover, the FAI40keV and λHU significantly differed among the three groups, and we identified good positive correlations between FAI40keV and λHU and the TyG index (r = 0.319, P <0.01 and r = 0.325, P <0.01, respectively). FAI120kVp did not significantly differ among the groups. FAI40keV had the highest area under the curve, with an optimal cutoff value of −130.5 HU for predicting a TyG index value of ≥9.13. The multivariate linear regression analysis demonstrated that FAI40keV and λHU were independently positively related to a high TyG index level (standardized regression coefficients: 0.117 [P <0.001] and 0.134 [P <0.001], respectively). Conclusions Patients with chest pain and a higher TyG index level were more likely to have severe stenosis and HRPs. Moreover, FAI40keV and λHU had good correlations with the serum TyG index, which may noninvasively reflect PCAT inflammation under insulin resistance. These results could help explain the mechanism of plaque progression and instability in patients with insulin resistance might be related to IR-induced coronary inflammation.
| S-EPMC10206237 | biostudies-literature
Project description:ObjectiveTo construct and validate a prediction model based on dual-layer detector spectral CT (DLCT) and clinico-radiologic features to predict the microsatellite instability (MSI) status of gastric cancer (GC) and to explore the relationship between the prediction results and patient prognosis.MethodsA total of 264 GC patients who underwent preoperative DLCT examination were randomly allocated into the training set (n = 187) and validation set (n = 80). Clinico-radiologic features and DLCT parameters were used to build the clinical and DLCT model through multivariate logistic regression analysis. A combined DLCT parameter (CDLCT) was constructed to predict MSI. A combined prediction model was constructed using multivariate logistic regression analysis by integrating the significant clinico-radiologic features and CDLCT. The Kaplan-Meier survival analysis was used to explore the prognostic significant of the prediction results of the combined model.ResultsIn this study, there were 70 (26.52%) MSI-high (MSI-H) GC patients. Tumor location and CT_N staging were independent risk factors for MSI-H. In the validation set, the area under the curve (AUC) of the clinical model and DLCT model for predicting MSI status was 0.721 and 0.837, respectively. The combined model achieved a high prediction efficacy in the validation set, with AUC, sensitivity, and specificity of 0.879, 78.95%, and 75.4%, respectively. Survival analysis demonstrated that the combined model could stratify GC patients according to recurrence-free survival (p = 0.010).ConclusionThe combined model provides an efficient tool for predicting the MSI status of GC noninvasively and tumor recurrence risk stratification after surgery.Critical relevance statementMSI is an important molecular subtype in gastric cancer (GC). But MSI can only be evaluated using biopsy or postoperative tumor tissues. Our study developed a combined model based on DLCT which could effectively predict MSI preoperatively. Our result also showed that the combined model could stratify patients according to recurrence-free survival. It may be valuable for clinicians in choosing appropriate treatment strategies to avoid tumor recurrence and predicting clinical prognosis in GC.Key points• Tumor location and CT_N staging were independent predictors for MSI-H in GC. • Quantitative DLCT parameters showed potential in predicting MSI status in GC. • The combined model integrating clinico-radiologic features and CDLCT could improve the predictive performance. • The prediction results could stratify the risk of tumor recurrence after surgery.
| S-EPMC10509117 | biostudies-literature
Project description:To determine the accuracy of iodine quantification with dual energy computed tomography (DECT) in two high-end CT systems with different spectral imaging techniques.Five tubes with different iodine concentrations (0, 5, 10, 15, 20 mg/ml) were analysed in an anthropomorphic thoracic phantom. Adding two phantom rings simulated increased patient size. For third-generation dual source CT (DSCT), tube voltage combinations of 150Sn and 70, 80, 90, 100 kVp were analysed. For dual layer CT (DLCT), 120 and 140 kVp were used. Scans were repeated three times. Median normalized values and interquartile ranges (IQRs) were calculated for all kVp settings and phantom sizes.Correlation between measured and known iodine concentrations was excellent for both systems (R = 0.999-1.000, p < 0.0001). For DSCT, median measurement errors ranged from -0.5% (IQR -2.0, 2.0%) at 150Sn/70 kVp and -2.3% (IQR -4.0, -0.1%) at 150Sn/80 kVp to -4.0% (IQR -6.0, -2.8%) at 150Sn/90 kVp. For DLCT, median measurement errors ranged from -3.3% (IQR -4.9, -1.5%) at 140 kVp to -4.6% (IQR -6.0, -3.6%) at 120 kVp. Larger phantom sizes increased variability of iodine measurements (p < 0.05).Iodine concentration can be accurately quantified with state-of-the-art DECT systems from two vendors. The lowest absolute errors were found for DSCT using the 150Sn/70 kVp or 150Sn/80 kVp combinations, which was slightly more accurate than 140 kVp in DLCT.• High-end CT scanners allow accurate iodine quantification using different DECT techniques. • Lowest measurement error was found in scans with largest photon energy separation. • Dual-source CT quantified iodine slightly more accurately than dual layer CT.
| S-EPMC5544802 | biostudies-other
Project description:PurposeThis study aimed to evaluate the differences between pericoronary adipose tissue (PCAT) attenuation at different measured locations in evaluating coronary atherosclerosis using spectral computed tomography (CT) and to explore valuable imaging indicators.MethodsA total of 330 patients with suspicious coronary atherosclerosis were enrolled and underwent coronary CT angiography with dual-layer spectral detector CT (SDCT). Proximal and peri-plaque fat attenuation index (FAI) of stenosis coronary arteries were measured using both conventional images (CIs) and virtual monoenergetic images (VMIs) ranging from 40 keV to 100 keV. The slopes of the spectral attenuation curve (λ) of proximal and peri-plaque PCAT at three different monoenergetic intervals were calculated. Additionally, peri-plaque FAI on CI and virtual non-contrast images, and effective atomic number were measured manually.ResultsA total of 231 coronary arteries with plaques and lumen stenosis were finally enrolled. Peri-plaque FAICI and FAIVMI were significantly higher in severe stenosis than in mild and moderate stenosis (p < 0.05), while peri-plaque λ, proximal FAI, and proximal λ were not statistically different. Proximal FAI, peri-plaque FAI, and peri-plaque λ were significantly higher in low-density non-calcified plaque (LD-NCP) and non-calcified plaque (NCP) than in calcified plaque (p < 0.01). Peri-plaque FAI was the highest in the LD-NCP group, while proximal FAI was the highest in the NCP group. In severe stenosis and in LD-NCP, peri-plaque FAI was significantly higher than proximal FAI (p < 0.05). The manually measured parameters related to peri-plaque PCAT attenuation had a positive correlation with the results of peri-plaque FAI measured automatically.ConclusionPeri-plaque PCAT has more value in assessing coronary atherosclerosis than proximal PCAT. Peri-plaque PCAT attenuation is expected to be used as a standard biomarker for evaluating plaque vulnerability and hemodynamic characteristics.
| S-EPMC10964482 | biostudies-literature