Houghtonmorton6379

The alternative is the acquisition of a third system, which must be connected by an interface with the main system and has significantly higher acquisition and maintenance costs.In this work, the free lipase Eversa® Transform 2.0 was used as a catalyst for enzymatic glycerolysis reaction in a solvent-free system. The product was evaluated by nuclear magnetic resonance (1H NMR) and showed high conversion related to hydroxyl groups. In sequence, the product of the glycerolysis was used as stabilizer and biopolyol for the synthesis of poly(urea-urethane) nanoparticles (PUU NPs) aqueous dispersion by the miniemulsion polymerization technique, without the use of a further surfactant in the system. Reactions resulted in stable dispersions of PUU NPs with an average diameter of 190 nm. After, the formation of the PUU NPs in the presence of concentrated lipase Eversa® Transform 2.0 was studied, aiming the lipase immobilization on the NP surface, and a stable enzymatic derivative with diameters around 231 nm was obtained. The hydrolytic enzymatic activity was determined using ρ-nitrophenyl palmitate (ρ-NPP) and the immobilization was confirmed by morphological analysis using transmission electron microscopy and fluorescence microscopy.OBJECTIVES Magnetic resonance elastography (MRE) is a non-invasive tool for measuring liver stiffness (LS) with high diagnostic accuracy. This study investigated whether quantified LS by MRE could predict early recurrence of patients with hepatocellular carcinoma (HCC) within the Milan criteria. METHODS A prospectively collected cohort, which included the HCC patients who underwent MRE before treatment (an HCC-MRE cohort), was analyzed. In the HCC-MRE cohort, only patients under the Milan criteria, who underwent hepatic resection, radiofrequency ablation (RFA), or transarterial chemoembolization (TACE), were reviewed. We investigated whether LS assessed by MRE was an independent predictor of early recurrence using Cox regressions and Kaplan-Meier analyses. RESULTS A total of 192 HCC patients under the Milan criteria who underwent hepatic resection (n = 96), RFA (n = 23), or TACE (n = 73) were included. Higher LS ratings (kPa; hazard ratio [HR] = 1.12; 95% confidence interval [CI] = 1.01-1.25; p = 0.040) emerged as an independent risk factor for early tumor recurrence. In the subgroup analysis, higher LS ratings were associated with higher risks of early HCC recurrence in both the resection/RFA group (> 4.5 kPa; HR = 2.95; 95% CI = 1.26-6.94; p = 0.013) and the TACE group (> 6 kPa; HR = 2.94; 95% CI = 1.27-6.83; p = 0.012). CONCLUSION LS assessed by MRE was an independent predictor of early recurrence among HCC patients under the Milan criteria after achieving a complete response. KEY POINTS • Liver parenchymal stiffness measured by MRE predicts early recurrence of treated HCC under Milan criteria. • A liver stiffness > 5.5 kPa was associated with worse recurrence-free survival. • Patients with high pre-treatment LS may benefit from stringent follow-up.OBJECTIVES To establish a diagnostic tree analysis (DTA) model based on ultrasonography (US) findings and clinical characteristics for differential diagnosis of common causes of cervical lymphadenopathy in children. METHODS A total of 242 patients (131 boys, 111 girls; mean age, 11.2 ± 0.3 years; range, 1 month-18 years) with pathologically confirmed Kikuchi disease (n = 127), reactive hyperplasia (n = 64), lymphoma (n = 24), or suppurative lymphadenitis (n = 27) who underwent neck US were included. US images were retrospectively reviewed to assess lymph node (LN) characteristics, and clinical information was collected from patient records. DTA models were created using a classification and regression tree algorithm on the basis of US imaging and clinical findings. The patients were randomly divided into training (70%, 170/242) and validation (30%, 72/242) datasets to assess the diagnostic performance of the DTA models. RESULTS In the DTA model based on all predictors, perinodal fat hyperechogenicity, LN echogenicity, and short diameter of the largest LN were significant predictors for differential diagnosis of cervical lymphadenopathy (overall accuracy, 85.3% and 83.3% in the training and validation datasets). In the model based on categorical parameters alone, perinodal fat hyperechogenicity, LN echogenicity, and loss of fatty hilum were significant predictors (overall accuracy, 84.7% and 86.1% in the training and validation datasets). CONCLUSIONS Perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum were significant US findings in the DTA for differential diagnosis of cervical lymphadenopathy in children. KEY POINTS • Diagnostic tree analysis model based on ultrasonography and clinical findings would be helpful in differential diagnosis of pediatric cervical lymphadenopathy. • Significant predictors were perinodal fat hyperechogenicity, heterogeneous echotexture, short diameter of the largest LN, and loss of fatty hilum.OBJECTIVE To evaluate the feasibility of one-stop pancreatic perfusion CT with mean temporal (MT) imaging replacing the combination of a bi-phasic scan plus a perfusion scan to detect insulinoma. TG003 MATERIAL AND METHODS Forty-five patients with suspected insulinoma, who underwent both biphasic and perfusion CT, were enrolled in this retrospective study. MT datasets including images for different delineation purposes were generated by averaging 3 dynamic datasets from perfusion CT, which are MTA for arterial, MTPV for portal vein and MTO for lesions. Two readers assessed the image quality and diagnostic performance separately for biphasic and MT datasets. Radiation doses were also assessed. Paired t tests, Wilcoxon signed-rank tests and McNemar's tests were applied for comparison. RESULTS Compared with bi-phasic CT images, image noise, SNR and CNR of the MTA and MTPV datasets were all non-inferior (noise and CNR of the portal vein, p = 0.565 and p = 0.227, respectively) or superior (p ≤ 0.001). The subjective image quality was better in the MTA and MTPV images (p  less then  0.