The association between serum ferritin levels and malignant intraductal papillary mucinous neoplasms.

BACKGROUND: Serum ferritin levels are elevated in many malignancies. In this study, we showed the performance of serum ferritin in identifying malignant intraductal papillary mucinous neoplasms (IPMNs). METHODS: A total of 151 patients with pathologically confirmed IPMNs were enrolled. Serum tumor biomarker (carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA)) levels and serum ferritin levels were recorded. Lesion location, tumor size, diameter of the main pancreatic duct (MPD), mural nodule, and IPMN type, were collected from imaging examinations. IPMNs with high grade dysplasia and associated invasive carcinoma were considered malignant IPMNs. RESULTS: Serum ferritin levels in patients with malignant IPMNs were higher than those in patients with nonmalignant IPMNs (p <  0.05). Serum ferritin was an independent factor for the occurrence of malignant IPMNs (odds ratio (OR) = 1.18, 95% confidence interval (CI):1.01-1.39). A similar trend was found between high serum ferritin (> 149 ng/ml) and malignant IPMNs (OR = 5.64, 95% CI:1.78-17.92). The area under the curve (AUC) of serum ferritin was higher than that of CEA and CA19-9 in identifying malignant IPMNs (AUC = 0.67 vs. AUC = 0.58, 0.65). The combination of serum ferritin with IPMN type showed a similar performance to MPD diameter and the combination of serum CA19-9 with IPMN types in identifying malignant IPMNs (AUC = 0.78 vs. AUC = 0.79, 0.77) and invasive carcinoma (AUC = 0.77 vs. AUC = 0.79, 0.79). CONCLUSIONS: Elevated serum ferritin is a factor associated with malignant IPMNs. Serum ferritin may be a useful marker for identifying malignancy in IPMNs.

Low high-density lipoprotein cholesterol levels are associated with malignant intraductal papillary mucinous neoplasms: A multicenter study.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) can potentially undergo malignant transformation. Studies have shown that high-density lipoprotein cholesterol (HDL-c) was associated with the risk of cancer. In this study, the association between HDL-c and the incidence of malignancy in IPMNs was investigated. MATERIALS AND METHODS: 226 patients with histologically proven IPMNs who underwent surgery were included in the present study. Patients were assigned to a training group (n = 151) and validation group (n = 75). Patients' demographic information, clinical data, and histopathological evaluation findings were obtained from medical records. Malignant IPMNs were defined as lesions that showed high grade dysplasia and invasive carcinoma. Logistic regression analyses were used to show the association between HDL-c and malignant IPMNs. Receiver operating characteristic (ROC) curves were generated to analyze predictive performance. RESULTS: The prevalence of low HDL-c levels was higher in patients with malignant IPMNs than in those with non-malignant IPMNs (P < 0.01) in both the training group and validation group. The prevalence of malignant IPMNs decreased with an increase in HDL-c levels both in patients with all types of IPMNs, as well as in those with branch-duct IPMNs (BD-IPMNs).Logistic analysis showed that low HDL-c levels were associated with malignant IPMNs (odds ratio (OR) = 20.56, 95 % confidence interval (CI): 2.58-163.64, P < 0.01) in all types of IPMNs and BD-IPMNs (OR = 17.6, 95 %CI: 1.16-268.46, P = 0.02 ).The predictive performance of mural nodules plus low HDL-c levels was higher than that of mural nodules alone or mural nodules plus cyst size for the identification of malignant BD-IPMNs. CONCLUSIONS: HDL-c levels may serve a potential biomarker for identifying malignant IPMNs and improve the predictive ability of malignancy in BD-IPMNs.

Diabetes in Patients With Pancreatic Neuroendocrine Neoplasms.

Objective: Diabetes mellitus (DM) is probably a risk factor for pancreatic neuroendocrine neoplasms (PNENs). However, the prevalence of DM in PNEN patients remains inconclusive. In the present study we observed the prevalence of DM and possible risk factors in PNEN patients. Methods: After excluding those with insulinoma, a total of 197 patients with PNENs were included. The demographic data, pathological characteristics, and data of blood biochemical tests were recorded. DM was considered if there was evidence of a fasting plasma glucose level of ≥7.0 mmol/L or a 2-h plasma glucose level of ≥11.1 mmol/L, or a history of DM at the time of PNEN diagnosis. Impaired fasting glucose was considered if fasting plasma glucose level was between 6.1 and 7.0 mmol/L. Results: The prevalence of DM, new-onset DM, and impaired fasting glucose were 17.26, 9.14, and 7.1%, respectively. The prevalence of DM was 26.0% in patients ≥60 years old (19/73) and 12.1% in patients <60 years old. Multivariable logistic regression analysis demonstrated that age, tumor size, and nerve invasion were independent risk factors for DM and impaired fasting glucose + DM (p < 0.05). Age, organs and nerve invasion were independent risk factors for impaired fasting glucose. Low high-density lipoprotein (HDL) was also a risk factor for incident of DM (OR = 0.15, 95%CI: 0.03-0.66). G2/G3 was an independent risk factor for DM in women. Conclusion: Our data shows that the prevalence of DM is 17.26% in patients with PNENs and is 26.0% in patients ≥60 years of age after excluding insulinoma. Age, nerve invasion, tumor size, and HDL are risk factors for DM in PNEN patients.

Textural analysis on contrast-enhanced CT in pancreatic neuroendocrine neoplasms: association with WHO grade.

PURPOSE: Grades of pancreatic neuroendocrine neoplasms (PNENs) are associated with the choice of treatment strategies. Texture analysis has been used in tumor diagnosis and staging evaluation. In this study, we aim to evaluate the potential ability of texture parameters in differentiation of PNENs grades. MATERIALS AND METHODS: 37 patients with histologically proven PNENs and underwent pretreatment dynamic contrast-enhanced computed tomography examinations were retrospectively analyzed. Imaging features and texture features at contrast-enhanced images were evaluated. Receiver operating characteristic curves were used to determine the cut-off values and the sensitivity and specificity of prediction. RESULTS: There were significant differences in tumor margin, pancreatic duct dilatation, lymph nodes invasion, size, portal enhancement ratio (PER), arterial enhancement ratio (AER), mean grey-level intensity, kurtosis, entropy, and uniformity among G1, G2, and pancreatic neuroendocrine carcinoma (PNEC) G3 (p < 0.01). Similar results were found between pancreatic neuroendocrine tumors (PNETs) G1/G2 and PNEC G3. AER and PER showed the best sensitivity (0.86-0.94) and specificity (0.92-1.0) for differentiating PNEC G3 from PNETs G1/G2. Mean grey-level intensity, entropy, and uniformity also showed acceptable sensitivity (0.73-0.91) and specificity (0.85-1.0). Mean grey-level intensity was also showed acceptable sensitivity (91% to 100%) and specificity (82% to 91%) in differentiating PNET G1 from PNET G2. CONCLUSIONS: Our data indicated that texture parameters have potential in grading PNENs, in particular in differentiating PNEC G3 from PNETs G1/G2.

The differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma: the values of CT imaging features and texture analysis.

BACKGROUND: Imaging findings for pancreatic neuroendocrine carcinoma (PNEC) and pancreatic ductal adenocarcinoma (PDAC) often overlap. The aim of this study was to demonstrate the value of computed tomography (CT) imaging features and texture analysis to differentiate PNEC from PDAC. METHODS: Twenty-eight patients with pathologically-proved PDAC and 14 patients with PNEC were included in this study. CT imaging findings, including tumor boundary, size, enhancement degree, duct dilatation and parenchymal atrophy were used to compare PDAC and PNEC. CT texture features were extracted from CT images at the arterial and portal phases. RESULTS: More PNEC than PDAC had well-defined margins (57.1% vs 25.0%, p = 0.04). Parenchymal atrophy was more common in PDAC than in PNEC (67.9% vs 28.1%, p = 0.02). CT attenuation values (HU) and contrast ratios of PNEC inthe arterial and portal phases were higher than those of PDAC (p < 0.05 or 0.01). Entropy was lower and uniformity was higher in PNEC compare to PDAC at the arterial phase (p < 0.05). Contrast ratio showed the highest area under curve (AUC) for differentiating PNEC from PDAC (AUC = 0.98-0.99). Entropy and uniformity also showed an acceptable AUC (0.71-0.72). CONCLUSIONS: Our data indicate that CT imaging features, including tumor margin, enhanced degree and parenchymal atrophy, as well as texture parameters can aid in the differentiation of PNEC from PDAC.

The Levels of Tumor Markers in Pancreatic Neuroendocrine Carcinoma and Their Values in Differentiation Between Pancreatic Neuroendocrine Carcinoma and Pancreatic Ductal Adenocarcinoma.

OBJECTIVES: The levels of tumor markers in pancreatic neuroendocrine carcinoma (PNEC) are unknown, and imaging findings of PNEC and pancreatic ductal adenocarcinoma (PDAC) have overlaps. In this study, we show the tumor markers in PNEC and evaluate their values for distinguishing PNEC from PDAC. METHODS: Thirty-three cases of PDAC and 21 cases of PNEC were retrospectively evaluated. The demographic information and clinical data were reviewed. RESULTS: Pancreatic neuroendocrine carcinoma was usually misdiagnosed (57.1%) as PDAC based on imaging findings. Abnormal carbohydrate antigen (CA) 19-9, carcinoembryonic antigen (CEA), and α-fetoprotein (AFP) were observed in 19.0% to 28.6% of PNECs. Abnormal CA 19-9 and CA 125 levels were more common in PDAC than in PNEC (P < 0.05). Higher level of AFP was more common in PNEC than in PDAC (33.3% vs 3.0%, P < 0.05). The cutoff value of CA 19-9 for detecting PNEC was calculated as 38.5 U/mL or less with 0.788 sensitivity and 0.800 specificity. Carbohydrate antigen 19-9 (odds ratio [OR], 22.9; 95% confidence interval [CI], 2.94-179.3), AFP (OR, 0.08; 95% CI, 0.012-0.564), and CA 125 (OR, 17.4; 95% CI, 1.13-267.3) were predictors in differentiating PDAC from PNEC. CONCLUSIONS: Carbohydrate antigen 19-9, AFP, and CA 125 have potential for distinguishing hypovascularized PNEC from PDAC.

Value of diffusion-weighted magnetic resonance imaging in predicting World Health Organization grade in G1/G2 pancreatic neuroendocrine tumors.

The present study aimed to investigate the value of diffusion-weighted magnetic resonance imaging (DWI) in the grading of well-differentiated pancreatic neuroendocrine tumors (PanNETs). A total of 44 patients with histologically proven well-differentiated PanNET [grade 1 (G1) and grade 2 (G2) according to the World Health Organization (WHO) criteria] underwent pretreatment magnetic resonance imaging (MRI), which was retrospectively analyzed. The location, size, cystic or solid appearance, boundary, presence or absence of tumor contrast enhancement, and MRI signal of the tumor were assessed. Apparent diffusion coefficients (ADCs) within the primary tumor were measured on ADC maps. Receiver operating characteristic curves were used to determine ADC cut-off values and the sensitivity and specificity of the grade prediction. Spearman's rank correlation was utilized to probe the association between ADC value and PanNET grade or pathological parameters. G1 tumors exhibited a well-circumscribed border more often than G2 tumors. No marked differences were observed between PanNET G1 and PanNET G2 for cystic or solid appearance, enhancement, and T1- and T2-weighted imaging signals. Marked hyperintensities were more common in PanNET G2 tumors than in PanNET G1 tumors (P<0.01). The mean ADC values were statistically different between the normal pancreas and G1 and G2 tumors (P<0.01), and between PanNET G1 and PanNET G2 (P<0.05). Correlation analysis showed that ADC value was negatively correlated with PanNET grade, mitotic count and Ki-67 proliferation index (P<0.05). The cut-off ADC value was 0.930×10-3 mm2/sec, which identified G2 tumors with 82.4% sensitivity and 79.5% selectivity. ADC value therefore represents a non-invasive and valuable imaging parameter in predicting the WHO grade of tumors in well-differentiated PanNET.

Differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma using magnetic resonance imaging: The value of contrast-enhanced and diffusion weighted imaging.

Pancreatic neuroendocrine carcinoma (PNEC) is often misdiagnosed as pancreatic ductal adenocarcinoma (PDAC). This retrospective study differentiated PNEC from PDAC using magnetic resonance imaging (MRI), including contrast-enhanced (CE) and diffusion-weighted imaging (DWI). Clinical data and MRI findings, including the T1/T2 signal, tumor boundary, size, enhancement degree, and apparent diffusion coefficient (ADC), were compared between 37 PDACs and 13 PNECs. Boundaries were more poorly defined in PDAC than PNEC (97.3% vs. 61.5%, p<0.01). Hyper-/isointensity was more common in PNEC than PDAC at the arterial (38.5% vs. 0.0), portal (46.2% vs. 2.7%) and delayed phases (46.2% vs. 5.4%) (all p<0.01). Lymph node metastasis (97.3% vs. 61.5%, p<0.01) and local invasion/distant metastasis (86.5% vs. 46.2%, p<0.01) were more common in PDAC than PNEC. Enhancement degree via CE-MRI was higher in PNEC than PDAC at the arterial and portal phases (p<0.01). PNEC ADC values were lower than those of normal pancreatic parenchyma (p<0.01) and PDAC (p<0.01). Arterial and portal phase signal intensity ratios and ADC values showed the largest areas under the receiver operating characteristic curve and good sensitivities (92.1%-97.2%) and specificities (76.9%-92.3%) for differentiating PNEC from PDAC. Thus the enhancement degree at the arterial and portal phases and the ADC values may be useful for differentiating PNEC from PDAC using MRI.

Simultaneous detection of influenza A, influenza B, and respiratory syncytial viruses and subtyping of influenza A H3N2 virus and H1N1 (2009) virus by multiplex real-time PCR.

A multiplex real-time PCR assay was developed to simultaneously detect and discriminate influenza A virus subtypes, including novel H1N1 (2009) and seasonal H3N2 virus, influenza B virus, and respiratory syncytial virus (RSV) in a single test tube, with detection sensitivity and specificity of 99% and 100%, respectively, for the four pathogens.

[Detection and typing of caliciviruses from patients with acute diarrhea in Hangzhou area, 2009 - 2010].

OBJECTIVE: To investigate the molecular-epidemiologic characteristics and genotypes of human calicivirus (HuCVs) in acute diarrhea patients in Hangzhou from 2009 to 2010. METHODS: Epidemiologic data and fecal specimens were collected from patients with acute diarrhea. HuCVs of 920 specimens were detected by PCR. PCR products of several positive samples were randomly selected and sequenced. All the sequences were analyzed, phylogenetically. RESULTS: 201 HuCVs positive cases were identified from 920 facal specimens (21.8%). 25 isolates would include norovirus GI-type, GII-type for 170 strains and sapovirus for 11 strains. Norovirus GI-type and GII-type were detected in four specimens at the same time. Other specimens were mixed infection with norovirus GII-type and sapovirus. Genotypes of HuCVs showed that norovirus GI subtypes were GI-1 (3 strains) and GI-2 (1 strain). Norovirus GII subtypes were GII-4/2006b variant strains (7 strains), GII-2 (1 strain), GII-7 (1 strain) and GII-4/2008 variant strains (2 strains); Sapovirus subtypes were GI-2 (5 strains), GI-1 (4 strains) and GII-1 (1 strain). The prevalence rates of HuCVs were different in seasons and age groups. CONCLUSION: HuCVs were one of the major pathogens causing acute diarrhea. Both multiple viruses and genotypes of HuCVs were found in the specimens. GII-4/2006b variant and similar strains were identified, probably as the prevalent strains from 2009 to 2010 in Hangzhou, Zhejiang province.