Background: Dual-energy computed tomography (DECT) has been widely applied to detect lymph node (LN) and lymph node metastasis (LNM) in various cancers, including papillary thyroid carcinoma (PTC). This study aimed to quantitatively evaluate metastatic cervical lymph nodes (LNs) <0.5 cm in patients with PTC using DECT, which has not been done in previous studies. Methods: Preoperative DECT data of patients with pathologically confirmed PTC were retrospectively collected and analyzed between May 2016 and June 2018. A total of 359 LNs from 52 patients were included. Diameter, iodine concentration (IC), normalized iodine concentration (NIC), and the slope of the energy spectrum curve (λ HU ) of LNs in the arterial and the venous phases were compared between metastatic and nonmetastatic LNs. The optimal parameters were obtained from the receiver operating characteristic (ROC) curves. The generalized estimation equation (GEE) model was used to evaluate independent diagnostic factors for LNM. Results: A total of 139 metastatic and 220 non-metastatic LNs were analyzed. There were statistical differences of quantitative parameters between the two groups (P value 0.000-0.007). The optimal parameter for diagnosing LNM was IC in the arterial phase, and its area under the curve (AUC), sensitivity, and specificity were 0.775, 71.9%, and 73.6%, respectively. When the three parameters of diameter, IC in the arterial phase, and NIC in the venous phase were combined, the prediction efficiency was better, and the AUC was 0.819. The GEE results showed that LNs located in level VIa [odds ratio (OR) 2.030, 95% confidence interval (CI): 1.134-3.634, P=0.017], VIb (OR 2.836, 95% CI: 1.597-5.038, P=0.000), diameter (OR 2.023, 95% CI: 1.158-3.532, P=0.013), IC in the arterial phase (OR 4.444, 95% CI: 2.808-7.035, P=0.000), and IC in the venous phase (OR 5.387, 95% CI: 3.449-8.413, P=0.000) were independent risk factors for LNM in patients with PTC. Conclusions: DECT had good diagnostic performance in the differentiation of cervical metastatic LNs <0.5 cm in patients with PTC.

DCE-MRI is useful to differentiate the metastatic LNs from benign LNs. Sizes of LNs has no effect on parameters.

Background: To study the incidence of metabolic syndrome (MetS) and kidney stones in a healthy screening population and to explore the correlation between them. Methods: The physical examination data of 11,827 people screened at the First Affiliated Hospital of Soochow University from August 2019 to July 2020 were analyzed. MetS diagnostic criteria were based on the 2004 guidelines of Chinese Diabetes Society (CDS). Multivariate logistic regression was used to analyze the correlation between MetS and various characteristics and kidney stones. Trend analysis was represented by P value, and P<0.05 indicated statistical significance. Results: The present study comprised 6,570 males (55.6%, aged 46.15±13.653 years) and 5,257 females (44.4%, aged 41.41±11.712 years). Of these, 1,036 (8.8%) had kidney stones and 1,552 (13.1%) had MetS. Among the MetS patients, 35.1% had a body mass index (BMI) ≥25, 27.7% had hypertension, 10.8% had hyperglycemia, and 31.2% had dyslipidemia. Kidney stone morbidity was 14.5% in the MetS group and 7.9% in the non-MetS group (P<0.05). As the number of MetS characteristics increased, kidney stone morbidity showed a linear increasing trend (P<0.05 for trend). With an increase in BMI and blood triglycerides (TG), and a decrease in lipoprotein cholesterol (HDL-C), the incidence of kidney stones had an increasing trend (P<0.05 for trend). Sex, age and MetS were independent risk factors for the occurrence of kidney stones, with and odds ratio (OR) of 1.493 [95% confidence interval (CI): 1.264-1.763] for MetS. Of the MetS characteristics, BMI ≥25 and blood pressure (BP) ≥140/90 mmHg were independent risk factors for kidney

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