Development and Validation of a Fusion Model Based on Carotid Plaques and White Matter Lesion Burden Imaging Characteristics to Evaluate Ischemic Stroke Severity in Symptomatic Patients.

BACKGROUND: The diagnostic value of carotid plaque characteristics based on higher-resolution vessel wall MRI (HRVW-MRI) combined with white matter lesion (WML) burden for the risk of ischemic stroke is unclear. PURPOSE: To combine carotid plaque features and WML burden to construct a hybrid model for evaluating ischemic stroke severity and prognosis in patients with symptomatic carotid artery stenosis. STUDY TYPE: Retrospective. SUBJECTS: One hundred and ninty-three patients with least one confirmed carotid atherosclerotic stenosis ≥30% and cerebrovascular symptoms within the last 2 weeks (136 in the training cohort and 57 in the test cohort). FIELD STRENGTH/SEQUENCE: 3.0T, T2-weighted fluid attenuated inversion recovery (T2-FLAIR) and diffusion-weighted imaging (DWI); HRVW-MRI: 3D T1-weighted variable flip angle fast spin-echo sequences (VISTA), T2-weighted VISTA, simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP), and contrast-enhanced T1-VISTA. ASSESSMENT: The following features of the plaques or vessel wall were assessed by three MRI readers independently: calcification (CA), intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), ulceration, plaque enhancement (PE), maximum vessel diameter (Max VD), maximum wall thickness (Max WT), total vessel area (TVA), lumen area (LA), plaque volume, and lumen stenosis. WMLs were graded visually and categorized as absent-to-mild WMLs (Fazekas score 0-2) or moderate-severe WMLs (Fazekas score 3-6). WML volumes were quantified using a semiautomated volumetric analysis program. Modified Rankin scores (mRS) were assessed at 90 days, following an outpatient interview, or by telephone. STATISTICAL TESTS: LASSO-logistic regression analysis was performed to construct a model. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analyses, calibration curves, decision curve analyses, and clinical imaging curves. Conditional logistic regression analysis was used to explore the associations between the hybrid model-derived score and the modified Rankin Scale (mRS) score at 90 days. RESULTS: The model was constructed using five selected features, including IPH, plaque enhancement, ulceration, NWI, and total Fazekas score in deep WMLs (DWMLs). The hybrid model yielded an area under the curve of 0.92 (95% confidence interval [CI] 0.87-0.97) in the training cohort and 0.88 (0.80-0.96) in the test cohort. Furthermore, the hybrid model-derived score (odds ratio = 1.28; 95% CI 1.06-1.53) was independently associated with the mRS score 90 days after stroke. DATA CONCLUSIONS: The hybrid model constructed using MRI plaque characteristics and WML burden has potential to be an effective noninvasive method of assessing ischemic stroke severity. The model-derived score has promising utility in judging neurological function recovery. TECHNICAL EFFICACY: Stage 2.

MRI-based texture analysis for differentiate between pediatric posterior fossa ependymoma type A and B.

PURPOSE: The aim of the study was to evaluate the feasibility of texture analysis in differentiating between posterior fossa ependymoma type A (PF-EPN-A) and type B (PF-EPN-B) among children. MATERIALS AND METHODS: Our retrospective study included 43 patients (37 PF-EPN-A and 6 PF-EPN-B) who were pathologically diagnosed with ependymomas in the posterior fossa. The texture features were extracted automatically from the volume of interests (VOIs), which were manually delineated on fluid-attenuated inversion recovery (FLAIR), contrast-enhanced T1-weighted (T1C), and diffusion-weighted imaging (DWI) MRI sequences. A receiver operating characteristic curve (ROC) was built to assess the diagnostic value of the texture parameters, and the prognostic value was evaluated by survival analysis. RESULTS: Texture parameter [Wavelet-LHH (H: High pass filter, L: Low pass. filter)_glcm (gray-level co-occurrence matrix)_Idn (Inverse difference normalized)] provides valuable information in distinguishing subgroups of ependymomas with higher specificity and positive predictive value (PPV). A total of 27 patients were divided into a high-risk group (IDN value＞0.916) and a low-risk group (IDN value＜0.916) with the most optimistic cut-off value (0.916). The Kaplan-Meier analysis of the survival curves showed significantly longer disease-free survival for low-risk groups compared to high-risk groups [hazard ratio (HR): 0.28, 95% confidence interval (CI): 0.11-0.69; p = 0.017]. CONCLUSION: Our results suggested that the texture parameters based on DWI images can be used to differentiate PF-EPN-A from PF-EPN-B. Texture analysis could be used as a noninvasive tool in distinguishing subgroup pediatric posterior fossa ependymomas and provide reliable prognostic information upon the verification of its reproducibility and feasibility by further studies.

Novel magnetic fluorescence probe based on carbon quantum dots-doped molecularly imprinted polymer for AHLs signaling molecules sensing in fish juice and milk.

A magnetic fluorescence probe was fabricated by coating carbon quantum dots-doped molecularly imprinted polymers (MIPs) layers on the surface of Fe3O4 particles (MFMP) for detection of N-acyl homoserine lactones (AHLs) signaling molecules. N-Z-L-homoserine lactone molecular was used as the template to prepare AHLs MIP layers, employing MAA and HEMA as functional monomers. The developed MFMP owned superparamagnetism, fluorescence, fast response and class-selectivity. If AHLs (C4-HSL, C6-HSL, C8-HSL, C10-HSL, C12-HSL and C14-HSL) were captured by the MFMP, they quenched the fluorescence of the probe. Fluorescence dropped linearly in the concentration ranges of 3.65 × 10-3 µmol/L-0.96 × 10-1 µmol/L for AHLs. The MFMP was applied to the analysis of fish juice and milk samples, and recoveries ranged from 83.10% to 90.74% with relative standard deviation less than 5.1%. This study offered a novel strategy to fabricated AHLs fluorescence probe with great potential for wide-ranging application in agri-food products.

Fluorometric determination of ciprofloxacin using molecularly imprinted polymer and polystyrene microparticles doped with europium(III)(DBM)3phen.

The authors describe a microparticle-based system for the detection of the fluoroquinolone antibiotic ciprofloxacin. The method is using the tris(dibenzoylmethane)(1,10-phenanthroline)europium(III) luminophore in polystyrene microparticles along with a molecularly imprinted polymer (MIP) for ciprofloxacin. If ciprofloxacin is captured by the MIP, it quenches the fluorescence of the luminophores. Fluorescence drops linearly in the 0.5-100 µg L-1 ciprofloxacin concentration range, and the detection limit is 92 ng L-1. The method was applied to the analysis of fish samples to assess the analytical performance of the probe. Recoveries ranged from 85.4 to 86.6%, and relative standard deviations between 2.1 and 3.9% (for n = 5). Graphical abstract Schematic presentation of a microparticle-based probe using the tris(dibenzoylmethane)(1,10-phenanthroline)europium(III) luminophore in polystyrene particles along with a molecularly imprinted polymer for ciprofloxacin. After removal of template, carboxylic groups left in the probe can bind to ciprofloxacin through hydrogen bonds.