Eigenbin compression for reducing photon-counting CT data size.

BACKGROUND: Photon-counting CT (PCCT) systems acquire multiple spectral measurements at high spatial resolution, providing numerous image quality benefits while also increasing the amount of data that must be transferred through the gantry slip ring. PURPOSE: This study proposes a lossy method to compress photon-counting CT data using eigenvector analysis, with the goal of providing image quality sufficient for applications that require a rapid initial reconstruction, such as to confirm anatomical coverage, scan quality, and to support automated advanced applications. The eigenbin compression method was experimentally evaluated on a clinical silicon PCCT prototype system. METHODS: The proposed eigenbin method performs principal component analysis (PCA) on a set of PCCT calibration measurements. PCA finds the orthogonal axes or eigenvectors, which capture the maximum variance in the N dimensional photon-count data space, where N is the number of acquired energy bins. To reduce the dimensionality of the PCCT data, the data are linearly transformed into a lower dimensional space spanned by the M < N eigenvectors with highest eigenvalues (i.e., the vectors that account for most of the information in the data). Only M coefficients are then transferred per measurement, which we term eigenbin values. After transmission, the original N energy-bin measurements are estimated as a linear combination of the M eigenvectors. Two versions of the eigenbin method were investigated: pixel-specific and pixel-general. The pixel-specific eigenbin method determines eigenvectors for each individual detector pixel, while the more practically realizable pixel-general eigenbin method finds one set of eigenvectors for the entire detector array. The eigenbin method was experimentally evaluated by scanning a 20 cm diameter Gammex Multienergy phantom with different material inserts on a clinical silicon-based PCCT prototype. The method was evaluated with the number of eigenbins varied between two and four. In each case, the eigenbins were used to estimate the original 8-bin data, after which material decomposition was performed. The mean, standard deviation, and contrast-to-noise ratio (CNR) of values in the reconstructed basis and virtual monoenergetic images (VMI) were compared for the original 8-bin data and for the eigenbin data. RESULTS: The pixel-specific eigenbin method reduced photon-counting CT data size by a factor of four with <5% change in mean values and a small noise penalty (mean change in noise of <12%, maximum change in noise of 20% for basis images). The pixel-general eigenbin compression method reduced data size by a factor of 2.67 with <5% change in mean values and a less than 10% noise penalty in the basis images (average noise penalty ≤5%). The noise penalty and errors were less for the VMIs than for the basis images, resulting in <5% change in CNR in the VMIs. CONCLUSION: The eigenbin compression method reduced photon-counting CT data size by a factor of two to four with less than 5% change in mean values, noise penalty of less than 10%-20%, and change in CNR ranging from 15% decrease to 24% increase. Eigenbin compression reduces the data transfer time and storage space of photon-counting CT data for applications that require rapid initial reconstructions.

Sex-specific association of circulating Isthmin-1 with isolated post-challenge hyperglycemia.

Introduction: To explore the distribution of Isthmin-1 (ISM1) level and its association with isolated post-challenge hyperglycemia (IPH). Methods: A total of 522 participants without a history of diabetes were invited to attend a standard 75g 2-h oral glucose tolerance test (OGTT), and 71 subjects were further invited for a 3-h oral minimal model test. Insulin sensitivity and ß-cell function were evaluated using both HOMA and estimated from OGTT. Circulating ISM1 levels were determined by a commercially available ELISA kit. Results: A total of 76 (14.6%) participants were diagnosed as IPH, accounting for 61.3% of the newly diagnosed diabetes. ISM1 levels were significantly higher in men than in women (1.74 ng/mL versus 0.88 ng/mL). The inverse correlation between ISM1 and ß-cell function and IPH was only significant in men. After multivariate adjustment, per unit increment in ISM1 was associated with 0.68-fold (95% CI: 0.49-0.90) reduced odds ratio (OR) of IPH in men. Compared to men with the lowest ISM1 levels, the adjusted OR of IPH with the highest ISM1 levels decreased by 73% (95% CI: 0.11-0.61). Moreover, incorporation of ISM1 into the New Chinese Diabetes Risk Score (NCDRS) model yielded a substantial improvement in net reclassification improvement of 58% (95% CI: 27%-89%) and integrated discrimination improvement of 6.4% (95% CI: 2.7%-10.2%) for IPH. Conclusions: ISM1 was significantly and independently associated with IPH, and serves as a feasible biomarker for the early identification of men with high risk of IPH.

Nutritional status affects immune function and exacerbates the severity of pulmonary tuberculosis.

Aim: To comprehensively evaluate the association and impact of nutritional status and immune function on the severity of pulmonary tuberculosis (PTB). Methods: This descriptive cross-sectional study involved 952 participants who were diagnosed with active PTB. Severe PTB involves three or more lung field infections based on chest radiography. Nutritional status was evaluated using various indicators, including body mass index (BMI), the nutritional risk screening score (NRS-2002), total protein (TP), prealbumin (PA), transferrin (TRF), and serum albumin (ALB) levels and the prognostic nutritional index (PNI). Immune dysfunction was defined as a CD4+ count <500 cells/µl or a CD4+/CD8+ ratio <1. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were also calculated. Multivariate logistic and generalized linear regression were used to assess the associations between nutritional status, immune function, the severity of PTB, and the number of infected lung fields, adjusting for age, sex, and diabetes. Mediation analysis was conducted to evaluate the extent to which immune function mediated the impact of nutritional status on the severity of PTB. Sensitivity analysis was performed to enhance the robustness of the results. Results: Compared to those in the general PTB group, patients in the severe PTB group tended to be older men with diabetes. Higher nutritional risk, higher proportion of immune dysfunction and lower lymphocyte counts were observed in the severe group. BMI and the PNI were found to be protective factors, while PLR was identified as a risk factor for disease severity. Immune dysfunction and the PLR are mediators of the relationship between nutritional status and PTB severity. When BMI, the PNI, and the PLR were combined with traditional clinical indicators, these parameters showed promising diagnostic value, and the AUC reached 0.701 (95% CI: 0.668-0.734). Conclusion: The findings suggest that nutritional status is significantly associated with the severity of PTB, and immune function mediates the effects of nutritional status on the severity of PTB. Maintaining adequate BMI, PNI levels, and immune function or reducing PLR levels helps reduce the risk of severe PTB.

Retinol binding protein 4 and type 2 diabetes: from insulin resistance to pancreatic ß-cell function.

BACKGROUND AND AIM: Retinol binding protein 4 (RBP4) is an adipokine that has been explored as a key biomarker of type 2 diabetes mellitus (T2DM) in recent years. Researchers have conducted a series of experiments to understand the interplay between RBP4 and T2DM, including its role in insulin resistance and pancreatic ß-cell function. The results of these studies indicate that RBP4 has a significant influence on T2DM and is considered a potential biomarker of T2DM. However, there have also been some controversies about the relationship between RBP4 levels and T2DM. In this review, we update and summarize recent studies focused on the relationship between RBP4 and T2DM and its role in insulin resistance and pancreatic ß-cell function to clarify the existing controversy and provide evidence for future studies. We also assessed the potential therapeutic applications of RBP4 in treating T2DM. METHODS: A narrative review. RESULTS: Overall, there were significant associations between RBP4 levels, insulin resistance, pancreatic ß-cell function, and T2DM. CONCLUSIONS: More mechanistic studies are needed to determine the role of RBP4 in the onset of T2DM, especially in terms of pancreatic ß-cell function. In addition, further studies are required to evaluate the effects of drug intervention, lifestyle intervention, and bariatric surgery on RBP4 levels to control T2DM and the role of reducing RBP4 levels in improving insulin sensitivity and pancreatic ß-cell function.

Serum remnant cholesterol is a potential predictor of liver stiffness in patients with nonalcoholic fatty liver disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is associated with dyslipidemia, and the connection between dyslipidemia and remnant cholesterol (RC), a component of triglyceride-rich lipoproteins, remains enigmatic. METHODS: In this cross-sectional study, our primary aim was to investigate the role of RC in the progression of NAFLD and to provide robust evidence of RC's involvement in the pathogenesis of NAFLD. We enrolled 2800 NAFLD patients from the National Health and Nutrition Examination Survey (NHANES). Logistic regression was employed to examine the relationship between serum RC levels and liver stiffness, while receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic capability of RC. RESULTS: RC exhibited an independent correlation with the extent of liver stiffness, with odds ratios (OR) of 1.02 for liver steatosis (p = 0.014) and 1.02 for liver fibrosis (p = 0.014). To predict NAFLD, the optimal RC thresholds were 17.25 mg/dL for males and 15.25 mg/dL for females in the case of liver steatosis. For advanced liver fibrosis, the best thresholds were 17.25 mg/dL for males and 16.25 mg/dL for females. CONCLUSIONS: RC demonstrated a positive correlation with the degree of liver stiffness and exhibited superior diagnostic efficacy for liver steatosis and fibrosis compared to other cholesterol indicators.

Elevated serum remnant cholesterol (RC) levels may serve as a potential indicator of metabolic diseases, including nonalcoholic fatty liver disease (NAFLD). The connection between serum RC and NAFLD has been previously undervalued. In our investigation, we examined 2800 NAFLD patients from the National Health and Nutrition Examination Survey (NHANES). Our cross-sectional study has revealed a more distinct relationship between RC and the degree of liver stiffness, especially concerning liver steatosis when compared to other cholesterol indicators. Recognizing RC's significant role in metabolic disorders may lead to innovative approaches for diagnosing and treating NAFLD patients.

RBP4-based Multimarker Score: A Prognostic Tool for Adverse Cardiovascular Events in Acute Coronary Syndrome Patients.

CONTEXT: Retinol binding protein 4 (RBP4) has been implicated in the progression of cardiovascular diseases. However, its association with major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS) remains obscure. OBJECTIVE: Here, we examined the prognostic value of baseline RBP4 and its derived multimarker score for MACEs in ACS patients. METHODS: A total of 826 patients with ACS were consecutively recruited from the department of cardiology and prospectively followed up for a median of 1.95 years (interquartile range, 1.02-3.25 years). Plasma RBP4 was measured using enzyme-linked immunosorbent assay. Adjusted associations between RBP4 and its derived multimarker score (1 point was assigned when RBP4 ≥ 38.18µg/mL, left ventricular ejection fraction [LVEF] ≤ 55%, N-terminal pro-B-type natriuretic peptide [NT-proBNP] ≥ 450 ng/L, estimated glomerular filtration rate [eGFR] ≤ 90 mL/min/1.73 m2, and age ≥60) with MACEs were analyzed. RESULTS: In total, 269 ACS patients (32.57%) experienced MACEs. When patients were grouped by multimarker score (0-1, n = 315; 2-3, n = 406; 4-5, n = 105), there was a significant graded association between RBP4-based multimarker score and risk of MACEs (intermediate score (2-3): HRadj: 1.80; 95% CI, 1.34-2.41; high score (4-5): HRadj: 3.26; 95% CI, 2.21-4.81) and its components (P < .05 for each). Moreover, the prognostic and discriminative value of the RBP4-derived multimarker score remained robust in ACS patients with various high-risk anatomical or clinical characteristics. CONCLUSION: The RBP4-derived 5-item score serves as a useful risk stratification and decision support for secondary prevention in patients with ACS.

Preparation of COF-coated nickel foam adsorbents for dispersive solid-phase extraction of 16 polycyclic aromatic hydrocarbons from Chinese herbal medicines.

Covalent organic framework coated nickel foam (NF@COF) was prepared as a sorbent for the dispersive solid phase extraction (DSPE) of polycyclic aromatic hydrocarbons (PAHs) from Chinese herbal medicines (CHMs) prior to their determination by gas chromatography-mass spectrometry (GC-MS). The structure and morphology of the as-synthesized NF@COF were characterized by different techniques. Various key parameters affecting the performance of the DSPE method, including the amount of sorbent, desorption solvent, desorption volume and time, extraction time, and sample volume, were investigated. Under the optimized conditions, NF@COF combined with GC-MS was successfully applied to the determination of 16 PAHs in CHMs. The method showed wide linearity (20-2000 ng mL-1), low limits of determination (0.3-2.7 ng mL-1), and high recoveries (78.0-124%). These results revealed that NF@COF has the potential for efficient extraction of PAHs from complex samples.

Determination of polycyclic aromatic hydrocarbons in Chinese herbal medicines by gas chromatography-mass spectrometry with graphene-functionalized nickel foam.

Graphene-functionalized nickel foam (NF) sorbent materials were prepared and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy and Thermogravimetric analysis. For the separation and detection of polycyclic aromatic hydrocarbons (PAHs) in five Chinese medicine samples, namely dandelion, fructus aurantii, peppermint, mulberry leaf and embryo chrysanthemum, a method combining dispersive micro-solid phase extraction and gas chromatography-mass spectrometry (GC-MS) was developed. Four conditions affecting the extraction efficiency, such as the type of desorption solvent, the amount of sorbent, the extraction time and the volume of water sample, were optimized. The results of the methodological validation showed that NF@SiO2@G was able to adsorb PAHs well and with good reproducibility. All analytes showed good linearity in the concentration range of 20-2000 ng/mL with coefficient of determination R2≥0.9956. The limit of detection was 0.98-13.34 ng/mL, and the limit of quantification ranged from 3.25 to 44.47 ng/mL. Both the intra-day and inter-day precision were lower than 15.46%, and the spiked recoveries were in the range of 75.5-118.4%. The total contents of the 16 PAHs contained in these five Chinese herbal medicines (CHMs) were varied from 450 to 1557 µg/kg. The results indicated that the graphene-functionalized NF sorbent combined with GC-MS can effectively detect PAHs in CHMs.

Alterations of NMR-Based Lipoprotein Profile Distinguish Unstable Angina Patients with Different Severity of Coronary Lesions.

Non-invasive detection of unstable angina (UA) patients with different severity of coronary lesions remains challenging. This study aimed to identify plasma lipoproteins (LPs) that can be used as potential biomarkers for assessing the severity of coronary lesions, determined by the Gensini score (GS), in UA patients. We collected blood plasma from 67 inpatients with angiographically normal coronary arteries (NCA) and 230 UA patients, 155 of them with lowGS (GS ≤ 25.4) and 75 with highGS (GS > 25.4), and analyzed it using proton nuclear magnetic resonance spectroscopy to quantify 112 lipoprotein variables. In a logistic regression model adjusted for four well-known risk factors (age, sex, body mass index and use of lipid-lowering drugs), we tested the association between each lipoprotein and the risk of UA. Combined with the result of LASSO and PLS-DA models, ten of them were identified as important LPs. The discrimination with the addition of selected LPs was evaluated. Compared with the basic logistic model that includes four risk factors, the addition of these ten LPs concentrations did not significantly improve UA versus NCA discrimination. However, thirty-two selected LPs showed notable discrimination power in logistic regression modeling distinguishing highGS UA patients from NCA with a 14.9% increase of the area under the receiver operating characteristics curve. Among these LPs, plasma from highGS patients was enriched with LDL and VLDL subfractions, but lacked HDL subfractions. In summary, we conclude that blood plasma lipoproteins can be used as biomarkers to distinguish UA patients with severe coronary lesions from NCA patients.

Flavonifractor plautii Protects Against Elevated Arterial Stiffness.

BACKGROUND: Dysbiosis of gut microbiota plays a pivotal role in vascular dysfunction and microbial diversity was reported to be inversely correlated with arterial stiffness. However, the causal role of gut microbiota in the progression of arterial stiffness and the specific species along with the molecular mechanisms underlying this change remain largely unknown. METHODS: Participants with elevated arterial stiffness and normal controls free of medication were matched for age and sex. The microbial composition and metabolic capacities between the 2 groups were compared with the integration of metagenomics and metabolomics. Subsequently, Ang II (angiotensin II)-induced and humanized mouse model were employed to evaluate the protective effect of Flavonifractor plautii (F plautii) and its main effector cis-aconitic acid. RESULTS: Human fecal metagenomic sequencing revealed a significantly high abundance and centrality of F plautii in normal controls, which was absent in the microbial community of subjects with elevated arterial stiffness. Moreover, blood pressure only mediated part of the effect of F plautii on lower arterial stiffness. The microbiome of normal controls exhibited an enhanced capacity for glycolysis and polysaccharide degradation, whereas, those of subjects with increased arterial stiffness were characterized by increased biosynthesis of fatty acids and aromatic amino acids. Integrative analysis with metabolomics profiling further suggested that increased cis-aconitic acid served as the main effector for the protective effect of F plautii against arterial stiffness. Replenishment with F plautii and cis-aconitic acid improved elastic fiber network and reversed increased pulse wave velocity through the suppression of MMP-2 (matrix metalloproteinase-2) and inhibition of MCP-1 (monocyte chemoattractant protein-1) and NF-κB (nuclear factor kappa-B) activation in both Ang II-induced and humanized model of arterial stiffness. CONCLUSIONS: Our translational study identifies a novel link between F plautii and arterial function and raises the possibility of sustaining vascular health by targeting gut microbiota.

Sleep Factors in Relation to Metabolic Dysfunction-Associated Fatty Liver Disease in Middle-Aged and Elderly Chinese.

CONTEXT: Accumulating evidence implies that sleep disturbance is involved in metabolic disorders. OBJECTIVE: We comprehensively evaluated the association between various dimensions of sleep behaviors and the risk for metabolic dysfunction-associated fatty liver disease (MAFLD). METHODS: In this cross-sectional study of 5011 participants with self-reported sleep behaviors and radiologically diagnosed MAFLD, a comprehensive healthy sleep score was generated to evaluate the associations between sleep behaviors and MAFLD risk using multivariate logistic regression adjusting for demographics, lifestyles, medication, and metabolic comorbidities. Furthermore, mediation analysis was utilized to assess the extent to which obesity explains the effect of sleep quality on MAFLD risk. RESULTS: Late bedtime, snoring, and daytime napping for over 30 minutes significantly associated with an increased risk of MAFLD, with odds ratios (OR) of 1.37 (95% CI 1.10, 1.70), 1.59 (95% CI 1.33, 1.91), and 1.17 (95% CI 1.02, 1.35), respectively, after full adjustments including obesity. Participants with disturbance in nighttime sleep and prolonged daytime napping showed the highest risk for MAFLD (OR 2.38, 95% CI 1.73, 3.27). Each additional increase of healthy sleep score was associated with a 16% reduction in MAFLD risk. Further stratified analysis revealed that people with a sedentary lifestyle and central obesity experienced more prominent adverse effects from poor sleep quality than others. Moreover, obesity accounted for only 20.77% of the total effect of sleep quality on MAFLD risk. CONCLUSIONS: Sleep behaviors, both cumulatively and individually, are associated with MAFLD risk. Public health awareness and strategies should be encouraged to curb MAFLD.

Prevalence and risk factors of metabolic associated fatty liver disease in the contemporary South China population.

BACKGROUND: As a newly proposed diagnosis, data on the prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is rare. We aimed to assess the prevalence and risk factors of MAFLD using new definition in the contemporary South China population. METHODS: In this population based, cross sectional study, a total of 5377 participants aged 30-79 years old were recruited from the South China between 2018 and 2019. MAFLD was diagnosed in subjects who have both hepatic steatosis and metabolic disorders according to the newly international expert consensus. The total prevalence of MAFLD and prevalence by sex and age was estimated. Demographic characteristics, history of disease, and lifestyle were recorded by participants on a questionnaire. Abdominal ultrasonography was performed and evaluated by experienced sonographers. Multivariable logistic regression was used to calculate the odds ratios (ORs) of MAFLD. RESULTS: Overall prevalence of MAFLD was 29.2% (95% confidence interval [CI] 28.0% to 30.5%). Prevalence was higher in women (31.7%) than in men (25.5%; p < 0.001 for sex difference) and in subjects aged 50 years or older (30.7%) than in those aged 30-49 years (19.8%; p < 0.001 for age difference). In participants diagnosed with MAFLD, the prevalence of overweight/obesity was up to 90.5%, type 2 diabetes (T2DM) and metabolic dysregulation were 25.0% and 62.2%, respectively. Risk factors for MAFLD included overweight/obesity (OR = 4.67; 95% CI, 3.76-5.83), T2DM (OR = 2.41, 95% CI, 1.68-3.47), hypertriglyceridemia (OR = 2.42, 95% CI, 2.03-2.87), high school education (OR = 1.50, 95% CI, 1.23-1.82), high income (OR = 1.22, 95% CI, 1.05-1.42). A lower risk of MAFLD was associated with high physical activity equivalent (OR = 0.71, 95% CI, 0.60-0.85). A U-shaped association of frequency of soups and ORs of MAFLD was found, the adjusted ORs (95% CI) of lower and higher frequency of soups were 1.58 (1.32-1.89) and 1.36 (1.13-1.63), respectively. CONCLUSIONS: Our results showed a high prevalence of MAFLD in the general adult population in South China. Obesity has the greatest impact on MAFLD, physical activity and moderate consumption of soups might be the potential protective factors of MAFLD.

Intermittent Fasting Improves Cardiometabolic Risk Factors and Alters Gut Microbiota in Metabolic Syndrome Patients.

CONTEXT: Intermittent fasting (IF) is an effective strategy to improve cardiometabolic health. OBJECTIVE: The objective of this work is to examine the effects of IF on cardiometabolic risk factors and the gut microbiota in patients with metabolic syndrome (MS). DESIGN AND SETTING: A randomized clinical trial was conducted at a community health service center. PATIENTS: Participants included adults with MS, age 30 to 50 years. INTERVENTION: Intervention consisted of 8 weeks of "2-day" modified IF. MAIN OUTCOME MEASURE: Cardiometabolic risk factors including body composition, oxidative stress, inflammatory cytokines, and endothelial function were assessed at baseline and at 8 weeks. The diversity, composition, and functional pathways of the gut microbiota, as well as circulating gut-derived metabolites, were measured. RESULTS: Thirty-nine patients with MS were included: 21 in the IF group and 18 in the control group. On fasting days, participants in the IF group reduced 69% of their calorie intake compared to nonfasting days. The 8-week IF significantly reduced fat mass, ameliorated oxidative stress, modulated inflammatory cytokines, and improved vasodilatory parameters. Furthermore, IF induced significant changes in gut microbiota communities, increased the production of short-chain fatty acids, and decreased the circulating levels of lipopolysaccharides. The gut microbiota alteration attributed to the IF was significantly associated with cardiovascular risk factors and resulted in distinct genetic shifts of carbohydrate metabolism in the gut community. CONCLUSION: IF induces a significant alteration of the gut microbial community and functional pathways in a manner closely associated with the mitigation of cardiometabolic risk factors. The study provides potential mechanistic insights into the prevention of adverse outcomes associated with MS.

Performance evaluation of computed tomography systems: Summary of AAPM Task Group 233.

BACKGROUND: The rapid development and complexity of new x-ray computed tomography (CT) technologies and the need for evidence-based optimization of image quality with respect to radiation and contrast media dose call for an updated approach towards CT performance evaluation. AIMS: This report offers updated testing guidelines for testing CT systems with an enhanced focus on the operational performance including iterative reconstructions and automatic exposure control (AEC) techniques. MATERIALS AND METHODS: The report was developed based on a comprehensive review of best methods and practices in the scientific literature. The detailed methods include the assessment of 1) CT noise (magnitude, texture, nonuniformity, inhomogeneity), 2) resolution (task transfer function under varying conditions and its scalar reflections), 3) task-based performance (detectability, estimability), and 4) AEC performance (spatial, noise, and mA concordance of attenuation and exposure modulation). The methods include varying reconstruction and tube current modulation conditions, standardized testing protocols, and standardized quantities and metrology to facilitate tracking, benchmarking, and quantitative comparisons. RESULTS: The methods, implemented in cited publications, are robust to provide a representative reflection of CT system performance as used operationally in a clinical facility. The methods include recommendations for phantoms and phantom image analysis. DISCUSSION: In line with the current professional trajectory of the field toward quantitation and operational engagement, the stated methods offer quantitation that is more predictive of clinical performance than specification-based approaches. They can pave the way to approach performance testing of new CT systems not only in terms of acceptance testing (i.e., verifying a device meets predefined specifications), but also system commissioning (i.e., determining how the system can be used most effectively in clinical practice). CONCLUSION: We offer a set of common testing procedures that can be utilized towards the optimal clinical utilization of CT imaging devices, benchmarking across varying systems and times, and a basis to develop future performance-based criteria for CT imaging.

Association of Serum Retinol-Binding Protein 4 Levels and the Risk of Incident Type 2 Diabetes in Subjects With Prediabetes.

OBJECTIVE: To explore the association of serum retinol-binding protein 4 (RBP4) levels and risk for the development of type 2 diabetes in individuals with prediabetes. RESEARCH DESIGN AND METHODS: A population-based prospective study was conducted among 1,011 Chinese participants with prediabetes (average age 55.6 ± 7.2 years). Incident type 2 diabetes was diagnosed according to the American Diabetes Association 2010 criteria. Serum RBP4 levels were measured using a commercially available ELISA. We analyzed the association of serum RBP4 levels with the risk of incident type 2 diabetes using the Cox proportional hazards model. RESULTS: During a median follow-up period of 3.1 years, 153 participants developed incident type 2 diabetes. A U-shaped association was observed between serum RBP4 levels and the risk of incident type 2 diabetes, with the lowest risk in the RBP4 range of 31-55 µg/mL. Multivariate Cox regression model analysis showed that serum RBP4 levels <31 µg/mL and RBP4 levels >55 µg/mL were associated with an increased risk of incident type 2 diabetes. The adjusted hazard ratios (95% CI) were 2.01 (1.31-3.09) and 1.97 (1.32-2.93), respectively, after adjusting for age, sex, BMI, waist circumference, γ-glutamyltransferase, HOMA of insulin resistance index, fasting plasma glucose, 2-h plasma glucose, and glycated hemoglobin (HbA1c) levels. CONCLUSIONS: A U-shaped relationship exists between serum RBP4 levels and the risk of incident type 2 diabetes in subjects with prediabetes.

Small dense LDL cholesterol is associated with metabolic syndrome traits independently of obesity and inflammation.

BACKGROUND: Small dense LDL cholesterol (sdLDL-c) has been established to be highly associated with metabolic disorder. However, the relationship between circulating sdLDL-c and the presence of metabolic syndrome (MetS) has not been fully established. METHODS: A total of 1065 Chinese males (45.07 ± 11.08 years old) without diabetes and general obesity was recruited into a population-based, cross-sectional study. The MetS was defined based on the updated National Cholesterol Education Program/ Adult Treatment Panel III criteria for Asian Americans. Serum sdLDL-c concentration was measured by a homogeneous assay method and its relationship with MetS and its traits was investigated. RESULTS: Serum sdLDL-c concentrations increased gradually with increasing numbers of MetS components (p < 0.001) and the proportion of patients with MetS increased gradually with increasing sdLDL-c levels (p for trend< 0.001). For the second, third, and fourth sdLDL-c quartiles versus the first, the OR (95% CI) for MetS were 4.47(2.41,8.28), 5.47(2.97,10.07) and 8.39(4.58,15.38) (p < 0.001 for trend) after multivariate adjustment. The stratified analysis conducted according to LDL-c levels showed that the OR between serum sdLDL-c levels and MetS was greater in those LDL-c levels lower than 3.3 mmol/L (OR = 22.97; 95% CI, 7.64-69.09) than in those LDL-c levels higher than 3.3 mmol/L (OR = 17.49; 95% CI, 4.43-68.98). Mediation analysis showed sdLDL-c mediated 38.6% of the association of waist circumference with triglycerides, while the association between sdLDL-c and MetS components did not mediate by hsCRP. CONCLUSIONS: This study found that high sdLDL-c concentrations were associated with the presence of MetS independently of central obesity and inflammation.

CT automated exposure control using a generalized detectability index.

PURPOSE: Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index ( d gen ' ) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches. METHODS: This study proposes a task-based automated exposure control (AEC) method using a generalized detectability index ( d gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' metric is calculated using lookup tables of task-based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in-house iterative reconstruction algorithm with different regularization strengths (IR1-IR4). The task-based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d gen ' and noise standard deviation. The performance of the proposed d gen ' -AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images. RESULTS: The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d gen ' predicted by the lookup table and d ' measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans. CONCLUSIONS: A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.

Application of fractal dimension for quantifying noise texture in computed tomography images.

PURPOSE: Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. METHODS: The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120 kV and 25 and 90 mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box-counting algorithm applied to images of the uniform section of ACR phantom. The two-dimensional Noise Power Spectrum (NPS) and one-dimensional-radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS-peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. RESULTS: Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank-order coefficient of 0.98 (P-value < 0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64 × 64 pixels or one ROI of 128 × 128 pixels. Fractal dimension was found to be sensitive to non-noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. CONCLUSIONS: Fractal dimension correlated with the NPS-peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64 × 64-pixel ROIs or one 128 × 128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images.

Assessing computed tomography image quality for combined detection and estimation tasks.

Maintaining or even improving image quality while lowering patient dose is always the desire in clinical computed tomography (CT) imaging. Iterative reconstruction (IR) algorithms have been designed to allow for a reduced dose while maintaining or even improving an image. However, we have previously shown that the dose-saving capabilities allowed with IR are different for different clinical tasks. The channelized scanning linear observer (CSLO) was applied to study clinical tasks that combine detection and estimation when assessing CT image data. The purpose of this work is to illustrate the importance of task complexity when assessing dose savings and to move toward more realistic tasks when performing these types of studies. Human-observer validation of these methods will take place in a future publication. Low-contrast objects embedded in body-size phantoms were imaged multiple times and reconstructed by filtered back projection (FBP) and an IR algorithm. The task was to detect, localize, and estimate the size and contrast of low-contrast objects in the phantom. Independent signal-present and signal-absent regions of interest cropped from images were channelized by the dense-difference of Gauss channels for CSLO training and testing. Estimation receiver operating characteristic (EROC) curves and the areas under EROC curves (EAUC) were calculated by CSLO as the figure of merit. The one-shot method was used to compute the variance of the EAUC values. Results suggest that the IR algorithm studied in this work could efficiently reduce the dose by [Formula: see text] while maintaining an image quality comparable to conventional FBP reconstruction warranting further investigation using real patient data.

Design of a practical model-observer-based image quality assessment method for x-ray computed tomography imaging systems.

The use of a channelization mechanism on model observers not only makes mimicking human visual behavior possible, but also reduces the amount of image data needed to estimate the model observer parameters. The channelized Hotelling observer (CHO) and channelized scanning linear observer (CSLO) have recently been used to assess CT image quality for detection tasks and combined detection/estimation tasks, respectively. Although the use of channels substantially reduces the amount of data required to compute image quality, the number of scans required for CT imaging is still not practical for routine use. It is our desire to further reduce the number of scans required to make CHO or CSLO an image quality tool for routine and frequent system validations and evaluations. This work explores different data-reduction schemes and designs an approach that requires only a few CT scans. Three different kinds of approaches are included in this study: a conventional CHO/CSLO technique with a large sample size, a conventional CHO/CSLO technique with fewer samples, and an approach that we will show requires fewer samples to mimic conventional performance with a large sample size. The mean value and standard deviation of areas under ROC/EROC curve were estimated using the well-validated shuffle approach. The results indicate that an 80% data reduction can be achieved without loss of accuracy. This substantial data reduction is a step toward a practical tool for routine-task-based QA/QC CT system assessment.