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.

Ability of three-dimensional 3-Tesla ultrashort echo time magnetic resonance imaging to display the morphological characteristics of pulmonary nodules: a sensitivity analysis.

Background: Radiation-free lung cancer screening will reduce/eliminate radiation exposure in the diagnosis and follow-up of patients with lung cancer. Methods: This was a prospective study. The participants were recruited using convenience sampling. A total of 36 patients with pulmonary nodules [patients with single or multiple pulmonary nodules >4 and <30 mm on their pulmonary computed tomography (CT) scans] who were admitted to Fudan University Zhongshan Hospital's Xiamen branch were enrolled; they underwent a CT scan and a free-breathing ultrashort time-of-echo (UTE) sequence scan using a 3-Tesla (T) magnetic resonance imaging (MRI) scanner. The CT examinations were regarded as the reference standard. Patients had an interval time of <3 days between their CT and MRI examinations. Two reviewers with more than 10 years' experience in the diagnosis of pulmonary nodules identified the numbers and morphological features of the pulmonary nodules. Results: Among the 36 patients, 46 nodules were detected on CT images, 45 of which were also detected on UTE images (a detection rate of 97.6%). The detection rate for lobulation using UTE-MRI was 96.9%; however, the difference compared with the rate for the CT images was not statistically significant (P>0.05). In terms of confounding lesions (confounding lesions indicate that the patient has malignant tumours, benign nodules or inoperable nodules), the UTE-MRI method had a higher detection rate than the CT method, and the difference was significant (P<0.05). The probability of malignant lesions was found to be higher in confounding lesions than in homogeneous lesions. In terms of pleural traction, the UTE-MRI method demonstrated a higher detection rate (120%) than the CT method, but the difference was not statistically significant (P>0.05). In terms of spiculation, the UTE-MRI method demonstrated a lower detection rate (81.8%) than the CT method, although the difference was not statistically significant (P>0.05). Conclusions: Overall, 3-T UTE-MRI imaging has a high detection rate for pulmonary nodules >4 mm and is similar to that of conventional CT imaging. The method can be used for radiation-free lung cancer screening and follow-up examinations to reduce/eliminate both repeat CT examinations and radiation damage.

Study of T2 mapping in quantifying and discriminating uterine lesions under different magnetic field strengths: 1.5 T vs. 3.0 T.

BACKGROUND: MRI is the best imaging tool for the evaluation of uterine tumors, but conventional MRI diagnosis results rely on radiologists and contrast agents (if needed). As a new objective, reproducible and contrast-agent free quantification technique, T2 mapping has been applied to a number of diseases, but studies on the evaluation of uterine lesions and the influence of magnetic field strength are few. Therefore, the aim of this study was to systematically investigate and compare the performance of T2 mapping as a nonenhanced imaging tool in discriminating common uterine lesions between 1.5 T and 3.0 T MRI systems. METHODS: A total of 50 healthy subjects and 126 patients with suspected uterine lesions were enrolled in our study, and routine uterine MRI sequences with additional T2 mapping sequences were performed. T2 maps were calculated by monoexponential fitting using a custom code in MATLAB. T2 values of normal uterine structures in the healthy group and lesions (benign: adenomyosis, myoma, endometrial polyps; malignant: cervical cancer, endometrial carcinoma) in the patient group were collected. The differences in T2 values between 1.5 T MRI and 3.0 T MRI in any normal structure or lesion were compared. The comparison of T2 values between benign and malignant lesions was also performed under each magnetic field strength, and the diagnostic efficacies of the T2 value obtained through receiver operating characteristic (ROC) analysis were compared between 1.5 T and 3.0 T. RESULTS: The mean T2 value of any normal uterine structure or uterine lesion under 3.0 T MRI was significantly lower than that under 1.5 T MRI (p < 0.05). There were significant differences in T2 values between each lesion subgroup under both 1.5 T and 3.0 T MRI. Moreover, the T2 values of benign lesions (71.1 ± 22.0 ms at 1.5 T and 63.4 ± 19.1 ms at 3.0 T) were also significantly lower than those of malignant lesions (101.1 ± 4.5 ms at 1.5 T and 93.5 ± 5.1 ms at 3.0 T) under both field strengths. In the aspect of differentiating benign from malignant lesions, the area under the curve of the T2 value under 3.0 T (0.94) was significantly higher than that under 1.5 T MRI (0.90) (p = 0.02). CONCLUSION: T2 mapping can be a potential tool for quantifying common uterine lesions, and it has better performance in distinguishing benign from malignant lesions under 3.0 T MRI.

Differentiation Between Solitary Pulmonary Inflammatory Lesions and Solitary Cancer Using Gemstone Spectral Imaging.

BACKGROUND: The distinction between solitary inflammatory lesion and solitary lung cancer remains a challenge because of their considerable overlapping computed tomography (CT) imaging features. PURPOSE: This study aimed to verify whether spectral CT parameters can differentiate solitary lung cancer from solitary inflammatory lesions and to find their correlations with lesion size. METHODS: A total of 78 patients with solitary lung lesions were included in our study. All of them underwent enhanced CT scans with Gemstone Spectral Imaging (GSI) mode, which was one of the dual-energy imaging technologies. According to maximum diameter (Dmax) of the lesion, regions of interest were collected and divided into inflammatory (group I: <3 cm [IA], n = 17; ≥3 cm [IB], n = 14) and cancer groups (group II: <3 cm [IIA], n = 20; ≥3 cm [IIB], n = 27). Computed tomography values (HU40keV, HU70keV), effective atomic number (Zeff), iodine concentration (IC), normalized IC (NIC), and spectral curve slopes (λ30, λ40) of each region of interest were calculated. The NIC was defined as the IC ratio of the lesion to the descending aorta. Mann-Whitney U test was used for intergroup (I vs II, IA vs IIA, IB vs IIB) and intragroup (IA vs IB, IIA vs IIB) comparisons, and receiver operating characteristic curve analysis was performed. Correlation analysis was applied to find the relationship between Dmax and GSI parameters. RESULTS: No significant correlation was found between GSI parameters and Dmax in the inflammatory group, whereas inverse correlations were found in the cancer group. Gemstone spectral imaging parameters (except HU70keV) of group IIA were significantly higher than those of group IIB. There were significant differences in HU40keV, IC, NIC, λ30, and λ40 between groups IB and IIB under both arterial and venous phase (P values < 0.05), whereas the area under the curve for λ30 under venous phase was largest, and sensitivity and specificity were 96.32% and 85.71%, respectively. However, only HU40keV and HU70keV values under the arterial phase of IIA were significantly higher than those of IA. CONCLUSIONS: Quantitative parameters of GSI demonstrated an inverse correlation with the lesion size of solitary lung cancer, and GSI parameters can be new ways to differentiate solitary lung cancer from solitary inflammatory lesions.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations.

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient (ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China (approval No. 2014002).Diffusion kurtosis imaging (DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke (61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter (n = 52), corpus callosum (n = 14), cerebellum (n = 29), basal ganglia and thalamus (n = 21), brainstem (n = 21) and gray-white matter junctions (n = 62). Percentage changes of apparent diffusion coefficient (ΔADC) and DKI-derived indices (fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔDa], radial diffusivity ΔDr, mean kurtosis [ΔMK], axial kurtosis [ΔKa], and radial kurtosis [ΔKr]) of each lesion were computed relative to the normal contralateral region. The results showed that (1) there was no significant difference in ΔADC, ΔMD, ΔDa or ΔDr among almost all locations. (2) There was significant difference in ΔMK among almost all locations (except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions. (3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.

Antimicrobial Activity and Resistance: Influencing Factors.

Rational use of antibiotic is the key approach to improve the antibiotic performance and tackling of the antimicrobial resistance. The efficacy of antimicrobials are influenced by many factors: (1) bacterial status (susceptibility and resistance, tolerance, persistence, biofilm) and inoculum size; (2) antimicrobial concentrations [mutant selection window (MSW) and sub-inhibitory concentration]; (3) host factors (serum effect and impact on gut micro-biota). Additional understandings regarding the linkage between antimicrobial usages, bacterial status and host response offers us new insights and encourage the struggle for the designing of antimicrobial treatment regimens that reaching better clinical outcome and minimizing the emergence of resistance at the same time.

[Ligans from branch of Hypericum petiolulatum].

OBJECTIVE: To investigate the chemical constituents of Hypericum petiolulatum. METHOD: The chemical constituents were isolated and purified by column chromatography on silica gel, macroporous adsorbent resin, Sephadex LH-20, and preparative HPLC. Structures of the compounds were identified by NMR and MS spectroscopic methods. RESULT: Nine lignans were obtained and their structures were elucidated as (-)-(2R, 3R)-1-O-feruloyl-8,8'-bisdihydrosiringenin (1), (-) -secoisolariciresinol 4-O-beta-D-glucopyrano-side (2), isolariciresinol-beta-4'-O-beta-D-glucopyranoside (3), 5-methoxy-9beta-xylopyra-nosyl-(+) -isolariciresinol (4), (+) -lyoniresinol 2alpha-O-beta-D-xylopyranoside (5), 5-methoxy-9-beta-xylopyranosyl-(-) -isolariciresinol (6), isolariciresinol 6a-O-beta-D-gluco-side (7), (+)-lyoniresinol 3alpha-O-beta-D-xylopyranoside (8) and 7-methoxy-5-benzofuranpropanol 4'-O-beta-D-glucopyranoside (9). CONCLUSION: Coupound 1 was new and compounds 2-9 were obtained from the genus Hypericum for the first time.