Liver fat volume fraction measurements based on multi-material decomposition algorithm in patients with nonalcoholic fatty liver disease: the influences of blood vessel, location, and iodine contrast.

BACKGROUND: In recent years, spectral CT-derived liver fat quantification method named multi-material decomposition (MMD) is playing an increasingly important role as an imaging biomarker of hepatic steatosis. However, there are various measurement ways with various results among different researches, and the impact of measurement methods on the research results is unknown. The aim of this study is to evaluate the reproducibility of liver fat volume fraction (FVF) using MMD algorithm in nonalcoholic fatty liver disease (NAFLD) patients when taking blood vessel, location, and iodine contrast into account during measurement. METHODS: This retrospective study was approved by the institutional ethics committee, and the requirement for informed consent was waived because of the retrospective nature of the study. 101 patients with NAFLD were enrolled in this study. Participants underwent non-contrast phase (NCP) and two-phase enhanced CT scanning (late arterial phase (LAP) and portal vein phase (PVP)) with spectral mode. Regions of interest (ROIs) were placed at right posterior lobe (RPL), right anterior lobe (RAL) and left lateral lobe (LLL) to obtain FVF values on liver fat images without and with the reference of enhanced CT images. The differences of FVF values measured under different conditions (ROI locations, with/without enhancement reference, NCP and enhanced phases) were compared. Friedman test was used to compare FVF values among three phases for each lobe, while the consistency of FVF values was assessed between each two phases using Bland-Altman analysis. RESULTS: Significant difference was found between FVF values obtained without and with the reference of enhanced CT images. There was no significant difference about FVF values obtained from NCP images under the reference of enhanced CT images between any two lobes or among three lobes. The FVF value increased after the contrast injection, and there were significant differences in the FVF values among three scanning phases. Poor consistencies of FVF values between each two phases were found in each lobe by Bland-Altman analysis. CONCLUSION: MMD algorithm quantifying hepatic fat was reproducible among different lobes, while was influenced by blood vessel and iodine contrast.

The interaction effect of depressive symptoms and inflammation on the occurrence of cardiovascular diseases.

BACKGROUND: Whether there was an interaction effect between depressive symptoms and inflammation on the occurrence of cardiovascular diseases (CVDs) was unclear. METHODS: In this cross-sectional study, 3346 participants in the National Health and Nutrition Examination Survey (NHANES) were included. Multivariable regression analysis was performed to explore the associations of depressive symptoms or inflammation with CVDs. The attributable proportion of interaction (API), and synergy index (SI) were applied for evaluating the statistical significance of the interaction effect. RESULTS: Depressive symptoms were associated with 2.31-fold risk of CVDs [odds ratio (OR) = 2.31, 95 % confidence interval (CI): 1.47-3.62). The increased risk of CVDs was observed in people with neutrophil to lymphocyte ratio (NLR) ≥1.88 group (OR = 1.36, 95%CI: 1.01-1.85) and neutrophil/[white blood cell (WBC)-neutrophil] ≥1.35 (OR = 1.52, 95%CI: 1.12-2.07) after adjusting for confounders. The interaction effect of depressive symptoms and high NLR on the risk of CVDs was statistically significant with an OR value of 2.60 (95%CI: 1.43-4.70) compared to low NLR and no depressive symptoms group after adjusting for confounders. The API was 0.66 (95%CI: 0.44-0.89) and SI was 4.23 (95%CI: 2.08-8.59). The interaction effect of depressive symptoms and high neutrophil/(WBC-neutrophil) was associated with the risk of CVDs compared to low neutrophil/(WBC-neutrophil) and no depressive symptoms group (OR = 3.59, 95%CI: 2.00-6.45). The API was 0.78 (95%CI: 0.63-0.93) and SI was 6.75 (95%CI: 3.55-12.82). CONCLUSION: There was an interaction effect of depressive symptoms and inflammation on the occurrence of CVDs.

Association of Blood Amyloid Beta-Protein 1-42 with Poststroke Cognitive Impairment: A Systematic Review and Meta-Analysis.

Background: Increases in blood of amyloid beta-protein (Aß) have been noted in patients with Alzheimer's dementia (AD). Recent studies have shown that blood amyloid beta-protein 1-42 (Aß1-42) level is closely related to poststroke cognitive impairment (PSCI), which may be the influencing factor and even a predictor of PSCI. The aim of this systematic review was to synthesize the evidence for the association of cognitive impairment among PSCI. Methods: PubMed (MEDLINE), EMBASE, Cochrane Library, the Cochrane Central Register of Controlled Trial (CENTRAL), CNKI, and WanFang data were searched. Case-control, cohort, and cross-sectional studies that evaluated the association between blood Aß1-42 and PSCI were included irrespective of language and date of publication. The outcomes of this review consisted of (1) any dementia, (2) any cognitive impairment, and (3) any cognitive impairment no dementia, which were assessed at least 3 months (90 days) after stroke. Exposure of interest was blood Aß1-42 level (including serum and plasma). Results: Of 617 records retrieved, 8 studies (6 case-control and 2 cohort studies) involving 931 stroke patients were included for further analysis. 8 studies with 931 subjects explored the correlation between Aß1-42 and PSCI. PSCI was reported in 457 patients, and the pooled SMD of amyloid beta-protein 1-42 was -0.96 (95% CI -1.10~-0.82, I 2 = 15%, P < 0.01). The results remained robust in sensitivity analysis adjusting for study quality, sample source, and cognitive scale score in analysis of studies, as well as in analysis adjusted for publication bias. Conclusions: Blood Aß1-42 level was significantly negatively related to the risk for PSCI, and more prospective studies with large sample size are needed to define a precise threshold value of blood Aß1-42 level to predict PSCI in the future. This study is registered with PROSPERO, registration number: CRD42021246165.