Search

Purpose: High-density lipoprotein cholesterol (HDL-c) plays an important role in tumorigenesis in several endocrine-related cancers. Few studies have shown the effect of non-HDL-c in malignant tumors. The present study aimed to identify the association between non-HDL-c and high-grade pancreatic neuroendocrine neoplasms (PNENs)., Methods: A total of 197 PNEN patients who underwent surgery were analyzed retrospectively. Clinical and histopathological features, such as patients' age and sex, tumor location and size, tumor grade, the level of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c) and fasting plasma-glucose levels were obtained. Non-HDL-c was calculated as total cholesterol - HDL-c. The relationships between those features and high-grade PNENs were identified using logistic regression analysis., Results: Among the 197 patients with PNENs, a lower HDL-c level was more common seen in patients with poorly differentiated PNENs than in those with well-differentiated PNENs (P < 0.05). The non-HDL-c/HDL-c ratio was greater in patients with poorly differentiated PNENs than in those with well-differentiated PNENs (P < 0.01). Similarly, a greater proportion of patients with a non-HDL-c/HDL-c ratio larger than 5 was found in patients with poorly differentiated PNENs than in those with well-differentiation PNENs (P < 0.01). Multivariate logistic analysis showed that the non-HDL-c/HDL-c ratio was positively associated with poorly differentiated PNENs (odds ratio (OR) = 1.45, 95% conference interval (CI):1.13-1.87). Similarly, the risk of poorly differentiated PNENs increased significantly in patients with a non-HDL-c/HDL-c greater than 5 (OR = 14.13, 95%CI: 2.98-66.89). The risk of high-grade PNENs increased in patients with a high non-HDL-c/HDL-c ratio (OR = 1.27, 95% CI: 1.04-1.55), and the risk also increased markedly when the ratio was greater than 5 (OR = 5.00, 95%CI: 1.28-19.49)., Conclusions: A high ratio of non-HDL-c/HDL-c was associated with high-grade PNENs or poorly differentiated PNENs., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The aim of this study was to evaluate the cutoff value for identifying malignance in main pancreatic duct (MPD)-involved intraductal papillary mucinous neoplasm (IPMN) with an MPD diameter ranging from 5 to 10 mm. Clinical-radiological characteristics of 142 patients, including MPD-involved IPMNs (n = 53) and branch-duct (BD)-IPMNs (n = 89) were analyzed. Logistic regression analysis was used to determine the risk factors of malignant IPMNs and invasive carcinoma. ROC curves were used to identify different cutoffs in terms of preoperative MPD values to predict the presence of invasive carcinoma as well as malignant IPMNs, and the prediction performance was evaluated. For MPD-involved IPMNs (5 mm < MPD < 10 mm), MPD diameter of 7.5 mm for discriminating malignant IPMNs (area under curve [AUC] = 0.67) and 7.7 mm for discriminating invasive IPMNs (AUC = 0.56) were found to be the optimal cutoff values at receiver operating characteristic curve (ROC) analysis. MPD > 7.5 mm and carbohydrate antigen19-9 (Ca19-9) > 37 U/ml were found to be predictors of malignant IPMNs at univariate, and MPD > 7.5 mm was a predictor in multivariate analysis in MPD-involved IPMNs. The AUC of the ROC curve of MPD (7.5 mm) combined with Ca19-9 in identifying malignant IPMNs was 0.73 in MPD-involved IPMNs. MPD (7.5 mm) combined with Ca19-9 performed well in identifying malignant IPMNs in MPD-involved IPMNs., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis and treatment for patients with pancreatic tumors. However, fully supervised detection algorithms based on deep learning usually require a large number of manual annotations, which is time-consuming and labor-intensive. In this paper, we aim to detect the TLSs in a manner of few-shot learning by proposing a weakly supervised segmentation network. We firstly obtain the lymphocyte density maps by combining a pretrained model for nuclei segmentation and a domain adversarial network for lymphocyte nuclei recognition. Then, we establish a cross-scale attention guidance mechanism by jointly learning the coarse-scale features from the original histopathology images and fine-scale features from our designed lymphocyte density attention. A noise-sensitive constraint is introduced by an embedding signed distance function loss in the training procedure to reduce tiny prediction errors. Experimental results on two collected datasets demonstrate that our proposed method significantly outperforms the state-of-the-art segmentation-based algorithms in terms of TLSs detection accuracy. Additionally, we apply our method to study the congruent relationship between the density of TLSs and peripancreatic vascular invasion and obtain some clinically statistical results.

Immune checkpoint blockade (ICB) treatments have contributed to substantial clinical progress. However, challenges persist, including inefficient drug delivery and penetration into deep tumor areas, inadequate response to ICB treatments, and potential risk of inflammation due to over-activation of immune cells and uncontrolled release of cytokines following immunotherapy. In response, this study, for the first time, presents a multimodal imaging-guided organosilica nanomedicine (DCCGP) for photoimmunotherapy of pancreatic cancer. The novel DCCGP nanoplatform integrates fluorescence, magnetic resonance, and real-time infrared photothermal imaging, thereby enhancing diagnostic precision and treatment efficacy for pancreatic cancer. In addition, the incorporated copper sulfide nanoparticles (CuS NPs) lead to improved tumor penetration and provide external regulation of immunotherapy via photothermal stimulation. The synergistic immunotherapy effect is realized through the photothermal behavior of CuS NPs, inducing immunogenic cell death and relieving the immunosuppressive tumor microenvironment. Coupling photothermal stimulation with αPD-L1-induced ICB, the platform amplifies the clearance efficiency of tumor cells, achieving an optimized synergistic photoimmunotherapy effect. This study offers a promising strategy for the clinical application of ICB-based combined immunotherapy and presents valuable insights for applications of organosilica in precise tumor immunotherapy and theranostics., (© 2023 Wiley-VCH GmbH.)

Background: Jaundice occurs in some pancreatic disease. However, its occurrences and role in pancreatic neuroendocrine neoplasms (PNENs) has not been well studied. In this study we showed the association between jaundice and the risk of high grade and poorly differentiated PNENs., Methods: Ninety-three patients with head-neck PNENs were included. Poorly differentiated pancreatic neuroendocrine neoplasms were defined by a ki67 index > 55.0%. Logistic regression was used to show the association between demographic information, clinical signs and symptoms and the risk of poorly differentiated tumors. A nomogram model was developed to predict poorly differentiated tumor., Results: Eight of 93 PNEN patients (8.6%) had jaundice. The age and ki67 index in patients with jaundice were significantly higher than those patients without jaundice. All jaundice occurred in patients with grade 3 PNENs. Mutivariable regression analysis showed that age (odds ratio(OR) = 1.10, 95% confidence interval (CI):1.02-1.19), tumor size (OR = 1.42, 95%CI:1.01-2.00) and jaundice (OR = 14.98, 95%CI: 1.22-184.09) were associated with the risk of poorly differentiated PNENs. The age and size combination showed a good performance in predicting poorly differentiated PNENs (area under the curve (AUC) = 0.81, 95% CI: 0.71-0.90). The addition of jaundice further improved the age- and size-based model (AUC = 0.86, 95% CI: 0.78-0.91). A nomogram was developed based on age, tumor size and jaundice., Conclusion: Our data showed that jaundice was associated with the risk of high grade PNENs and poorly differentiated PNENs., (© 2023. The Author(s).)

Background: Early detection of pancreatic ductal adenocarcinoma (PDAC) may improve the prognosis of patients. This study was to identify metabolic features of PDAC and to discover early detection biomarkers for PDAC by tissue and serum metabolomics analysis., Methods: We conducted nontargeted metabolomics analysis in tissue samples of 51 PDAC tumors, 40 noncancerous pancreatic tissues (NT), and 14 benign pancreatic neoplasms (BP) as well as serum samples from 80 patients with PDAC, 36 with BP, and 48 healthy controls (Ctr). The candidate metabolites identified from the initial analysis were further quantified using targeted analysis in serum samples of an independent cohort of 22 early stage PDAC, 27 BP, and 27 Ctr subjects. Unconditional binary logistic regression analysis was used to construct the optimal model for PDAC diagnosis., Results: Upregulated levels of fatty acids and lipids and downregulated amino acids were observed in tissue and serum samples of PDAC patients. Proline, creatine, and palmitic acid were identified as a panel of potential biomarkers to distinguish PDAC from BP and Ctr (odds ratio = 2.17, [95% confidence interval 1.34-3.53]). The three markers showed area under the receiver-operating characteristic curves (AUCs) of 0.854 and 0.865, respectively, for the comparison of PDAC versus Ctr and PDAC versus BP. The AUCs were 0.830 and 0.852 in the validation set and were improved to 0.949 and 0.909 when serum carbohydrate antigen 19-9 (CA19-9) was added to the model., Conclusion: The novel metabolite biomarker panel identified in this study exhibited promising performance in distinguishing PDAC from BP or Ctr, especially in combination with CA19-9., (© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Abdominal or back pain is a common symptom in pancreatic diseases. However, the role of pain in pancreatic neuroendocrine neoplasm (PNENs) has not been clarified., Objective: In this study, we aimed to show the association between the pain and the grade of PNENs., Methods: A total of 186 patients with pathologically confirmed PNENs were included in this study. Clinical features and histological or radiological findings (size, location, and vascular invasion and local organs invasion and distal metastasis) were collected. Logistic regression analyses were used to show the association between pain and grade of PNENs. Nomogram was developed based on associated factors to predict the higher grade of PNENs. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of size and nomogram model., Results: The prevalence of pain in the cohort was 30.6% (n= 57). The vascular invasion and G3 PNENs were more common in the pain group (P= 0.02, P< 0.01). The tumor size was larger and incident of higher grade of PNENs was higher in the pain group than the non-pain group (p< 0.01). Age, pain and size were independent risk factors for G2/G3 or G3 PNENs. The odds ratio was 3.03 (95% CI: 1.67-7.91) and 3.32 (95% CI: 1.42-7.79) for pain, respectively. The nomogram model was developed to predict the G2/G3 or G3 PNENs. The area under the curve (AUC) of the nomogram model was 0.84 (95% CI, 0.77-0.91) in predicting the G2/G3 PNENs, and was 0.84 (95% CI, 0.78-0.91) in predicting the G3 PNENs., Conclusion: Abdominal or back pain is associated with the grade of PNENs. The nomograms based on clinical features may be a powerful numerical tool for predicting the grade of PNENs.

Objective: Intraductal papillary mucinous neoplasm (IPMN) is a rare pancreatic lesion. The identification of malignancy is critical for the establishment of treatment strategies. Main pancreatic duct (MPD) diameter is one critical feature for malignant IPMNs. However, the threshold of 1.0 cm is challenged. In this study, we explored independent risk factors and further calculated the threshold of MPD in identifying malignant IPMNs. Method: A total of 151 IPMN patients were included in this retrospective study. Demographic information, clinicopathological features, laboratory testing, and preoperative radiological characteristics by magnetic resonance imaging were collected. The receiver operating characteristic (ROC) curves were performed to determine the MPD diameter's cutoff levels and evaluate the predicted factors' diagnostic ability. Results: A cutoff value of 0.77 cm MPD (an area under the curve (AUC) = 0.746) in all IPMNs and 0.82 cm (AUC = 0.742) in the main duct involved IPMNs was obtained. MPD diameter (odds ratio (OR), 12.67; 95% confidence interval (CI), 4.80-33.48) and the mural nodule (OR, 12.98; 95% CI, 3.18-52.97) were the independent associated factors with high-risk IPMNs. The combined model with MPD and mural nodule showed a better predictive performance than mural nodule or MPD diameter alone (AUC = 0.803 vs 0.619, 0.746). A nomogram was developed and showed good performance (C index = 0.803). Conclusion: Our data show that mural nodule and MPD diameter are independent risk factors in identifying malignant intraductal papillary mucinous neoplasms. A cutoff value of 0.77 cm of MPD diameter may be a threshold value in identifying malignant intraductal papillary mucinous neoplasms or undergoing surgical resection.

Background: Main pancreatic duct (MPD) dilation is a high-risk stigmata/worrisome feature of malignancy in intraductal papillary mucinous neoplasms (IPMNs). The threshold of MPD diameter in predicting malignancy may be related to the lesion location. This study aimed to separately identify the thresholds of MPD for malignancy of IPMNs separately for the head-neck and body-tail., Materials and Methods: A total of 185 patients with pathologically confirmed IPMNs were included. Patient demographic information, clinical data, and pathological features were obtained from the medical records. Those IPMNs with high-grade dysplasia or with associated invasive carcinoma were considered as malignant tumor. Radiological data including lesion location, tumor size, diameter of the MPD, mural nodule, and IPMN types (main duct, MD; branch duct, BD; and mixed type, MT), were collected on computed tomography or magnetic resonance imaging. Serum carbohydrate antigen 19-9 levels, serum carcinoembryonic antigen levels, and the medical history of diabetes mellitus, chronic cholecystitis, and pancreatitis were also collected., Results: Malignant IPMNs were detected in 31.6% of 117 patients with lesions in the pancreatic head-neck and 20.9% of 67 patients with lesions in the pancreatic body-tail. In MPD-involved IPMNs, malignancy was observed in 54.1% of patients with lesions in the pancreatic head-neck and 30.8% of patients with lesions in the pancreatic body-tail (p < 0.05). The cutoff value of MPD diameter for malignancy was 6.5 mm for lesions in the head-neck and 7.7 mm for lesions in the body-tail in all type of IPMNs. In MPD-involved IPMNs, the threshold was 8.2 mm for lesion in pancreatic head-neck and 7.7 mm for lesions in the body-tail. Multivariate analysis confirmed that MPD diameter ≥ 6.5 mm (pancreatic head-neck) and MPD diameter ≥ 7.7 mm (pancreatic body-tail) were independent predictors of malignancy (p < 0.05). Similar results were observed in MPD-involved IPMNs using 8.2 mm as a threshold., Conclusion: The thresholds of the dilated MPD may be associated with IPMNs locations. Thresholds of 6.5 mm for lesions in the head-neck and 7.7 mm for lesions in the body-tail were observed. For MPD-involved IPMNs alone, threshold for lesions in the head-neck was close to that in the body-tail., (© 2022. The Author(s).)

Background: The role of serum high-density lipoprotein cholesterol (HDL-c) in tumorigenesis are observed in several endocrine-related cancers. However, its role in pancreatic neuroendocrine neoplasms (PNENs) has not been understood. In the current study, the relationship between HDL-c levels and malignant behavior in PNENs was explored., Methods: One hundred ninety-seven patients with histopathology confirmed PNENs were included. PNENs were divided into three grades (G1, G2 and G3) as 2017 WHO classification based on ki67 index and mitosis count. The demographic data, clinical information, tumor morphological and pathological features (organs invasion, lymph node metastasis, vascular invasion and perineural invasion), and serum tumor biomarkers were collected. The relationships between HDL-c levels and malignant behaviors in PNENs were analyzed using logistic regression analysis. Models were also developed for the identification of high grade PNENs., Results: The levels of serum HDL-c in G2/G3 tumor were significantly lower than that in G1 tumor (P = 0.031). However, no such difference was found between G3 and G1/G2. The proportions of low HDL-c (≤ 0.9 mmol/L) were higher in high-grade PNENs (G2/G3 or G3) than those in low-grade (G1 or G1/G2) (29.0 vs 15.2%, P = 0.032; 37.0 vs 20.5%, P = 0.023). The risk of G2/G3 tumors in patients with high serum HDL-c levels was decreased (odds ratio (OR) = 0.35, 95% confidence interval (CI): 0.12-0.99). Similarly, the risk of G3 PNENs increased in patients with low HDL-c levels (OR = 2.51, 95%CI:1.12-5.60). HDL-c level was also associated with a high ki67 index (> 55%) (OR = 0.10, 95%CI: 0.02-0.51) and neuroendocrine carcinoma G3 (OR = 0.21, 95%CI: 0.06-0.80). The area under the curve (AUC) of HDL-c + tumor size + age was 0.85 (95% CI: 0.79-0.91) in identifying G2/G3 PNENs, and HDL-c (> 0.9 mmol/L) + tumor size + age had an AUC of 0.77 (95% CI: 0.70-0.84) in identifying G3 PNENs. HDL-c level was associated with lymph node metastasis (OR = 0.24, 95%CI:0.08-0.99)., Conclusion: Serum HDL-c levels were significantly associated with malignant behaviors in PNENs, in particular to tumor grade and lymph node metastasis., (© 2022. The Author(s).)

Background: Pancreatic cancer (PC) remains a difficult tumor to diagnose and treat. It is often diagnosed as advanced by reason of the anatomical structure of the deep retroperitoneal layer of the pancreas, lack of typical symptoms and effective screening methods to detect this malignancy, resulting in a low survival rate. Emodin (EMO) is an economical natural product with effective treatment and few side effects of cancer treatment. Magnetic nanoparticles (MNPs) can achieve multiplexed imaging and targeted therapy by loading a wide range of functional materials such as fluorescent dyes and therapeutic agents., Purpose: The purpose of this study was to design and evaluate a multifunctional theranostic nanoplatform for PC diagnosis and treatment., Methods: In this study, we successfully developed EMO-loaded, Cy7-functionalized, PEG-coated Fe 3 O 4 (Fe 3 O 4 -PEG-Cy7-EMO). Characteristics including morphology, hydrodynamic size, zeta potentials, stability, and magnetic properties of Fe 3 O 4 -PEG-Cy7-EMO were evaluated. Fluorescence imaging (FI)/magnetic resonance imaging (MRI) and therapeutic treatment were examined in vitro and in vivo., Results: Fe 3 O 4 -PEG-Cy7-EMO nanoparticles had a core size of 9.9 ± 1.2 nm, which showed long-time stability and FI/MRI properties. Bio-transmission electron microscopy (bio-TEM) results showed that Fe 3 O 4 -PEG-Cy7-EMO nanoparticles were endocytosed into BxPC-3 cells, while few were observed in hTERT-HPNE cells. Prussian blue staining also confirmed that BxPC-3 cells have a stronger phagocytic ability as compared to hTERT-HPNE cells. Additionally, Fe 3 O 4 -PEG-Cy7-EMO had a stronger inhibition effect on BxPC-3 cells than Fe 3 O 4 -PEG and EMO. The hemolysis experiment proved that Fe 3 O 4 -PEG-Cy7-EMO can be used in vivo experiments. In vivo analysis demonstrated that Fe 3 O 4 -PEG-Cy7-EMO enabled FI/MRI dual-modal imaging and targeted therapy in pancreatic tumor xenografted mice., Conclusion: Fe 3 O 4 -PEG-Cy7-EMO may serve as a potential theranostic nanoplatform for PC., Competing Interests: The authors report no conflicts of interest concerning this article., (© 2021 Ren et al.)

Purpose: To develop and validate a CT-based radiomics nomogram in preoperative differential diagnosis of SCNs from mucin-producing PCNs., Material and Methods: A total of 89 patients consisting of 31 SCNs, 30 IPMNs, and 28 MCNs who underwent preoperative CT were analyzed. A total of 710 radiomics features were extracted from each case. Patients were divided into training (n = 63) and validation cohorts (n = 26) with a ratio of 7:3. Least absolute shrinkage and selection operator (LASSO) method and logistic regression analysis were used for feature selection and model construction. A nomogram was created from a comprehensive model consisting of clinical features and the fusion radiomics signature. A decision curve analysis was used for clinical decisions., Results: The radiomics features extracted from CT could assist with the differentiation of SCNs from mucin-producing PCNs in both the training and validation cohorts. The signature of the combination of the plain, late arterial, and venous phases had the largest areas under the curve (AUCs) of 0.960 (95% CI 0.910-1) in the training cohort and 0.817 (95% CI 0.651-0.983) in the validation cohort with good calibration. The value and efficacy of the nomogram was verified using decision curve analysis., Conclusion: A comprehensive nomogram incorporating clinical features and fusion radiomics signature can differentiate SCNs from mucin-producing PCNs.

Background: Non-hypervascular pancreatic neuroendocrine tumors (PNETs) showed slight or iso-enhancement in contrast-enhanced computed tomography (CE-CT), which shared similar imaging findings with mass-forming pancreatitis (MFPs)., Purpose: To explore the value of CT imaging features in differentiating the two diseases., Material and Methods: Fifty-one patients with histologically proved MFPs (n = 27) or non-hypervascular PNETs (n = 24) were included. Two radiologists reviewed CT imaging findings and clinical features. Logistic regression analysis was performed to identify relevant features in differentiating non-hypervascular PNETs and MFPs. Receiver operating characteristic (ROC) curve analysis was used to show the performance of the optimal parameters in differentiating non-hypervascular PNETs and MFPs., Results: A well-defined margin was more common in non-hypervascular PNETs ( P  < 0.05) than that in MFPs. MFPs often occurred in older people ( P  < 0.01) and the head-neck of the pancreas compared with non-hypervascular PNETs ( P  < 0.05). Metastases only presented in non-hypervascular PNETs ( P  < 0.05). CT values at venous phase and delay phase of MFPs were higher ( P  = 0.010 and P  = 0.029) than those in non-hypervascular PNETs. Logistic analysis showed gender, tumor margin, CT values at venous phase, and tumor components were independent predictors in differentiating the two lesions. The area under the curve (AUC) was 0.938 with a sensitivity of 87.5% and specificity of 92.6% for combined predicators., Conclusion: Gender, tumor margin, CT values at venous phase, and tumor components were useful predicators in differentiating non-hypervascular PNETs and MFPs.

Purpose: To assess the role of contrast-enhanced computed tomography (CECT) for differentiation of hypovascular pancreatic neuroendocrine tumors (hypo-PNETs) from chronic mass-forming pancreatitis (CMFP)., Methods: A retrospective study of 59 patients (27 hypo-PNETs patients vs 32 CMFP patients) who underwent preoperative CECT between July 2012 and July 2019 was performed. Qualitative and quantitative analysis was performed, including mass location, size, margin, cystic changes, calcification, pancreatic or bile duct dilatation, pancreatic atrophy, local vessels involvement, mass contrast enhancement and mass-to-pancreas enhancement ratio. Multivariate logistic regression analyses were used to identify relevant CT imaging findings in differentiation between hypo-PNETs and CMFP., Results: When compared to CMFP, hypo-PNETs more frequently had a well-defined margin and cystic changes and less frequently had a history of pancreatitis and calcification. CMFP had higher mass contrast enhancement and mass-to-pancreas enhancement ratio in the portal and delayed phases than hypo-PNETs. After multivariate logistic regression analyses, areas under the curve (AUCs) were 0.795 (95 % CI: 0.652-0.899), 0.752 (95 % CI: 0.604-0.866), 0.859 (95 % CI: 0.726-0.943), and 0.929 (95 % CI: 0.814-0.983) for Model 1(clinical factors), Model 2 (qualitative parameters), Model 3 (quantitative parameters), and their combinations, respectively., Conclusion: Combined assessment of clinical factors, qualitative, and quantitative imaging characteristics can improve the differentiation between hypo-PNETs and CMFP at CECT., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: To investigate the value of texture analysis on unenhanced computed tomography (CT) to potentially differentiate mass-forming pancreatitis (MFP) from pancreatic ductal adenocarcinoma (PDAC)., Methods: A retrospective study consisting of 109 patients (30 MFP patients vs 79 PDAC patients) who underwent preoperative unenhanced CT between January 2012 and December 2017 was performed. Synthetic minority oversampling technique (SMOTE) algorithm was adopted to reconstruct and balance MFP and PDAC samples. A total of 396 radiomic features were extracted from unenhanced CT images. Mann-Whitney U test and minimum redundancy maximum relevance (MRMR) methods were used for the purpose of dimension reduction. Predictive models were constructed using random forest (RF) method, and were validated using leave group out cross-validation (LGOCV) method. Diagnostic performance of the predictive model, including sensitivity, specificity, accuracy, positive predicting value (PPV), and negative predicting value (NPV), was recorded., Results: We applied 200% of SMOTE to MFP and PDAC patients, resulting in 90 MFP patients compared with 120 PDAC patients. Dimension reduction steps yielded 30 radiomic features using Mann-Whitney U test and MRMR methods. Ten radiomic features were retained using RF method. Four most predictive parameters, including GreyLevelNonuniformity&#95;angle90&#95;offset1, VoxelValueSum, HaraVariance, and ClusterProminence&#95;AllDirection&#95;offset1&#95;SD, were used to generate the predictive model with preferable 92.2% sensitivity, 94.2% specificity, 93.3% accuracy, 92.2% PPV, and 94.2% NPV. Finally, in LGOCV analysis, a high pooled mean sensitivity, specificity, and accuracy (82.6%, 80.8%, and 82.1%, respectively) indicate a relatively reliable and stable predictive model., Conclusions: Unenhanced CT texture analysis can be a promising noninvasive method in discriminating MFP from PDAC.

Aim: Biomarker-targeted nanocarrier holds promise for early diagnosis and effective therapy of cancer. Materials & methods: This work successfully designs and evaluates GPC1-targeted, gemcitabine (GEM)-loaded multifunctional gold nanocarrier for near-infrared fluorescence (NIRF)/MRI and targeted chemotherapy against pancreatic cancer in vitro and in vivo . Results: Blood biochemical and histological analyses show that the in vivo toxicity of GPC1-GEM-nanoparticles (NPs) was negligible. Both in vitro and in vivo studies demonstrate that GPC1-GEM-NPs can be used as NIRF/MR contrast agent for pancreatic cancer detection. Treatment of xenografted mice with GPC1-GEM-NPs shows a higher tumor inhibitory effect compared with controls. Conclusion: This novel theranostic nanoplatform provides early diagnostic and effective therapeutic potential for pancreatic cancer.

Purpose: To retrospectively investigate the computed tomography (CT) and magnetic resonance (MR) imaging features of pancreatic adenosquamous carcinoma (PASC) and the association between imaging findings and prognosis., Materials and Methods: CT, MR images of 26 patients with PASC were analyzed. Clinical symptoms, tumor markers, and patients' survival were recorded. Tumor attenuation, enhancement pattern and degree, vessel involvement, adjacent tissue invasion and metastasis were evaluated. The association between imaging features and overall survival (OS) were also assessed using Cox proportional hazards ratio model., Results: Fourteen masses were found in the head of the pancreas and 12 in the body/tail. The mean tumor size was 4.47 ± 1.76 cm. PASC usually showed ill-defined (96.2%), lobulated (76.9%) and predominantly solid mass (92.3%). Ring enhancement in the peripheral area of the tumor was commonly seen (76.9%). Vessel invasion was seen in 17 cases (65.4%), encasement of adjacent arteries in 7 cases (26.9%), upstream main pancreatic duct (MPD) dilatation in 16 cases (61.5%) and double duct sign in 9 cases (34.6%). Multivariate Cox proportional hazards model demonstrated that patients with vessel invasion may predict a poor prognosis (p = 0.037)., Conclusion: PASC tends to be an ill-defined solid mass with peripheral ring enhancement, and relatively poor enhancement in the central area. PASC may also show vessel invasion, vessel encasement and upstream MPD dilatation. Vessel invasion may indicate a poor prognosis.

Purposes: Microscopic aggressive behaviors may be related with the prognosis of solid pseudopapillary neoplasms (SPNs). In this study, we investigate computed tomography (CT) features and differential diagnosis of aggressive and non-aggressive SPNs in pancreas., Materials and Methods: 122 patients with pathologically proven SPNs in pancreas were included. Patients' age, tumor site, texture, shape, margins, exophytic growth, capsule, calcification, hemorrhage, pancreatic duct dilatation or pancreatic parenchyma atrophy, peripancreatic infiltration or metastases, vascular encasement, and enhancement pattern were assessed. The diagnostic accuracy was analyzed by using the receiver operating characteristic curve (ROC)., Results: There were 30 aggressive SPNs and 92 non-aggressive SPNs. Aggressive SPNs showed significantly higher frequencies of an ill-defined margin, patient age > 40.5 years, and tumor size < 42.1 mm, but lower frequencies of complete capsule, hemorrhage compared with non-aggressive SPNs (p < 0.05). Lack of complete capsule and age > 40.5 years were independent risk factors of aggressive SPNs (odd ratio 7.08 and 3.1, respectively). When we applied the two predictors in the logistic regression model, the area under the curve (AUC) was 0.77 with sensitivity of 86.7% and specificity of 55.4%., Conclusion: Size less than 42.1 mm, lack of complete capsule, ill-defined, and absent bleeding are useful CT imaging features for predicating aggressive SPNs. Patient age > 40.5 years and lack of complete capsule showed acceptable diagnostic performance for discriminating aggressive from non-aggressive SPNs.

Background: Intrapancreatic accessory spleens (IPASs) are usually misdiagnosed as pancreatic neuroendocrine tumors (PNETs). Texture analysis is valuable in tumor detection, diagnosis, and staging., Purpose: To identify the potential of texture features in differentiating IPASs from small hypervascular PNETs., Material and Methods: Twenty-one patients with PNETs and 13 individuals with IPASs who underwent pretreatment dynamic contrast-enhanced computed tomography (CT) were retrospectively analyzed. The routine imaging features-such as location, size, margin, cystic or solid appearance, enhancement degree and pattern, and lymph node enlargement-were recorded. Texture features, such as entropy, skewness, kurtosis, and uniformity, on contrast-enhanced images were analyzed. Receiver operating characteristic (ROC) analysis was performed to differentiate IPASs from PNETs., Results: No significant differences were observed in margin, enhancement degree (arterial and portal phase), lymph node enlargement, or size between PNETs and IPASs (all P > 0.05). However, IPASs usually showed heterogeneous enhancement at the arterial phase and the same degree of enhancement as the spleen at the portal phase, both of which were greater than those of PNETs (69% vs. 35%, P = 0.06; 100% vs. 29%, P = 0.04). Entropy and uniformity were significantly different between IPASs and PNETs at moderate (1.5) and high sigma values (2.5) (both P < 0.01). ROC analysis showed that uniformity at moderate and high sigma had the highest area under the curve (0.82 and 0.89) with better sensitivity (85.0-95.0%) and acceptable specificity (75.0-83.3%) for differentiating IPASs from PNETs., Conclusions: Texture parameters have potential in differentiating IPASs from PNETs.

Purpose: To determine useful contrast-enhanced computed tomography (CE-CT) features in differentiating duodenal gastrointestinal stromal tumors (duodenal GISTs) from hypervascular pancreatic neuroendocrine tumors in the pancreatic head (pancreatic head NETs)., Methods: Seventeen patients with pathologically confirmed duodenal GISTs and 25 with pancreatic NETs underwent preoperative CE-CT. CT image analysis included tumor size, morphology, and contrast enhancement. Receiver operating characteristic curves were performed, and cutoff values were calculated to determine CT findings with high sensitivity and specificity., Results: CT imaging showed duodenal GISTs with higher frequencies of tumor central location close to the duodenum and a predominantly solid tumor type when compared with pancreatic head NETs (p < 0.05 for both). Duodenal GISTs were larger than pancreatic head NETs (3.3 ± 0.9 cm vs. 2.5 ± 1.1 cm, p = 0.03). Duodenal GISTs had significantly lower CT attenuation values (112.9 ± 17.9HU vs. 137.4 ± 32.1HU, p < 0.01) at the arterial phase and higher CT attenuation values at the delayed phase (94.3 ± 7.9HU vs. 84.9 ± 10.4HU, p < 0.01) when compared with pancreatic head NETs. A CT attenuation value of ≤ 135 HU at the arterial phase (30 s) was 76% sensitive, 94.1% specific, and 83.3% accurate for the diagnosis of duodenal GISTs, while a CT attenuation value of ≥ 89.5 HU at the delayed phase (120 s) was 93.3% sensitive, 81.8% specific, and 76.2% accurate for the diagnosis of duodenal GISTs., Conclusion: Tumor central location, size, texture, and contrast enhancement are valuable characteristics for the differentiation between duodenal GISTs and hypervascular pancreatic head NETs during preoperative examination.

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.

Hypovascular pancreatic neuroendocrine tumors (hypo-PNETs) are often misdiagnosed as pancreatic ductal adenocarcinoma (PDAC). However, the treatment options and prognosis of PNETs and PDAC are substantially different. This retrospective study differentiated hypo-PNETs from PDAC using contrast-enhanced CT (CE-CT). Clinical data and CE-CT findings, including tumor location, size, boundary, pancreatic duct dilatation, local invasion or metastases, tumor contrast enhancement, and tumor-to-pancreas enhancement ratio, were compared between 39 PDACs and 18 hypo-PNETs. At CT imaging, hypo-PNETs showed a higher frequency of a well-defined margin and lower frequencies of pancreatic duct dilatation and local invasion or metastasis when compared with PDAC (p < 0.05 for all). The mean attenuation of hypo-PNETs at the arterial and portal venous phase was significantly higher than that of PDAC (p < 0.001, p = 0.003, respectively). Similar results were observed in tumor-to-pancreas enhancement ratio. Tumor attenuation and tumor-to-pancreas enhancement ratio at the arterial phase showed the largest area under the curve (AUC) of 0.888 and 0.812 with 83.3-88.9% of sensitivity and 61.6-77.0% of specificity. Pancreatic duct dilatation, local invasion or metastasis, and tumor attenuation at the portal venous phase also showed acceptable AUC (0.703-0.748). Thus CE-CT features, especially the enhancement degree at the arterial phases, may be useful for differentiating hypo-PNETs from PDAC using CE-CT., Competing Interests: The authors have declared that no competing interests exist.

Rationale: Intraductal tubulopapillary neoplasm (ITPN) is a rare type of pancreatic epithelial neoplasm. We report 2 cases of ITPN and detail the imaging findings., Patient Concerns: The 1st case was a 36-year-old woman who complained of jaundice, yellow urine and diarrhea. She accepted ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) examination before surgery, which all revealed a mass in the pancreatic head. The 2nd case was a 62-year-old woman who was admitted to our hospital for the treatment of a pancreatic tumor. The MRI showed a mass filled the mian pancreatic duct in the head and neck., Diagnosis: The ITPN is an intraductal, grossly visible, tubule-forming epithelial neoplasm with high-grade dysplasia and ductal differentiation without overt mucin production., Interventions: The 1st patient received percutaneous transhepatic cholangial drainage procedure, endoscopic ultrasound guided fine needle aspiration, pancreatoduodenectomy, cholecystectomy, and lymphadenectomy successively. The 2nd patient received pancreaticoduodenectomy, cholecystectomy, and partial gastrectomy., Outcomes: Two months after surgery, the follow-up MRI revealed hepatic metastasis of the 1st patient. She is still alive now. The 2nd patient was lost to follow-up., Lessons: The ITPN is a rare pancreatic neoplasm and its clinical symptoms are atypical. It is difficult to make accurate diagnosis of ITPN before surgery even though various imaging modalities are used in combination. When a solid mass growing in the lumen of the pancreatic duct, ITPN should be taken into consideration.

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.

Purpose: Early diagnosis and therapy are critical to improve the prognosis of patients with pancreatic cancer. However, conventional imaging does not significantly increase the capability to detect early stage disease. In this study, we developed a multifunctional theranostic nanoplatform for accurate diagnosis and effective treatment of pancreatic cancer., Methods: We developed a theranostic nanoparticle (NP) based on gold nanocages (AuNCs) modified with hyaluronic acid (HA) and conjugated with anti-Glypican-1 (anti-GPC1) antibody, oridonin (ORI), gadolinium (Gd), and Cy7 dye. We assessed the characteristics of GPC1-Gd-ORI@HAuNCs-Cy7 NPs (ORI-GPC1-NPs) including morphology, hydrodynamic size, stability, and surface chemicals. We measured the drug loading and release efficiency in vitro. Near-infrared fluorescence (NIRF)/magnetic resonance imaging (MRI) and therapeutic capabilities were tested in vitro and in vivo., Results: ORI-GPC1-NPs demonstrated long-time stability and fluorescent/MRI properties. Bio-transmission electron microscopy (bio-TEM) imaging showed that ORI-GPC1-NPs were endocytosed into PANC-1 and BXPC-3 (overexpression GPC1) but not in 293 T cells (GPC1- negative). Compared with ORI and ORI-NPs, ORI-GPC1-NPs significantly inhibited the viability and enhanced the apoptosis of pancreatic cancer cells in vitro. Moreover, blood tests suggested that ORI-GPC1-NPs showed negligible toxicity. In vivo studies showed that ORI-GPC1-NPs enabled multimodal imaging and targeted therapy in pancreatic tumor xenografted mice., Conclusion: ORI-GPC1-NP is a promising theranostic platform for the simultaneous diagnosis and effective treatment of pancreatic cancer., Competing Interests: Disclosure The authors report no conflicts of interest in this work.

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.

Background: Biomarker-targeted molecular imaging holds promise for early detection of pancreatic cancer. The aim of this study was to design and evaluate a plectin-1 targeted multi-functional nanoparticle probe for pancreatic cancer imaging., Methods: 1,2-Distearoyl-sn-glycero-3-phosphoethanolamine-N-amino(polyethylene glycol) (DSPE-PEG-NH2)-modified superparamagnetic iron oxide (Fe 3 O 4 ) nanoparticles (SPION) were conjugated with plectin-1 antibody and/or Cy7 to create the multi-functional targeted nanoparticle targeted probe (Plectin-SPION-Cy7) or non-targeted probe (SPION-Cy7). Pancreatic carcinoma cell lines expressing plectin-1 were cultured with the targeted or control probes and then were imaged using confocal laser scanning microscopy and magnetic resonance imaging (MRI). Accumulations of the nanoparticles in pancreatic tumor xenografted mice were determined by MRI and fluorescence imaging., Results: In vitro optical imaging and MRI showed that the targeted nanoparticles were highly accumulated in MIAPaCa2 and XPA-1 carcinoma cells but not in non-carcinoma MIN6 cells, which was further confirmed by Prussian blue staining. In vivo MRI showed a significant T2 signal reduction. Prussian blue staining further confirmed that the plectin-1 targeted nanoparticles were highly accumulated in the tumor mass but not in normal pancreatic tissues, or in the liver and kidney, and few nanoparticles were observed in the tumors of mice injected with SPION-Cy7., Conclusions: Our data demonstrate that plectin-1 targeted fluorescence and MR dual-functional nanoparticle can visualize pancreatic cancer, and it has great potential to be used with various imaging devices for pancreatic cancer detection., (Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.)

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.

We investigated the potential of targeting survivin, an inhibitor of apoptosis, in visualize pancreatic tumor in mouse model using targeted magnetic nanoparticles (MNPs) and magnetic resonance imaging (MRI). Chitosan-coated MNPS and survivin antisense oligonucleotide(ASON) were conjugated to give Sur-MNPs. Accumulations of targeted, non-targeted nanoparticles or nonsense oligonucleotide-MNPs (NSON-MNPs) in the liver, spleen, kidney and tumors were determined. Targeted nanoparticles were highly accumulated in BxPC-3 cells but not in non-cancer cells. In vivo MRI showed a significant T2 signal reduction in tumors of mice injected with targeted nanoparticles but slight signal change in tumors of mice injected with non-targeted nanoparticles or NSON-MNPs. Prussian blue staining demonstrated highly accumulated Sur-MNPs in tumor mass compared with normal pancreatic, kidney and liver tissues. Our data show that the MNPs functionalized with ASON lead to the targeted localization in pancreatic tumors. Survivin targeted nanoparticles could be used for detection of pancreatic tumors., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The survivin gene is highly expressed in pancreatic cancer. The purpose of this study was to design and synthesize functionalized magnetic iron oxide nanoparticles (MNPs) targeting survivin gene for the detection of pancreatic cancer. The pancreatic cancer cell line BxPC-3 with survivin gene expression was selected in this study. The healthy lung fibroblast cell was used as a control. Chitosan-coated MNPs (CS@MNPs) and antisense oligodeoxynucleotide of survivin gene were conjugated to MNPs to give Sur-MNPs. Fourier transform infrared spectroscopy was performed to confirm the conjunction of chitosan. The interactions of MNPs, CS@MNPs, and Sur-MNPs in BxPC-3 cells were observed, recorded and analyzed. The size, morphology, cell uptake, cytotoxicity and stability of those particles were assessed by transmission electron microscope, Prussian blue staining, MTT assay and agarose gel electrophoresis. The magnetic resonance signal intensities of pancreatic cells labeled with CS@MNPs and MNPs, and Sur-MNPs, were compared on T₂-weighted images. The results demonstrated that the level of cellular uptake of CS@MNPs was higher than that of naked MNPs. The Sur-MNPs had a suitable size (12 nm sized core), high stability, no cytotoxicity and good water dispersion. Sur-MNPs did not accumulate in healthy lung fibroblast cells, while being taken up by BxPC-3 cells. The Sur-MNPs in BxPC-3 cells could be visualized on T₂-weighted images, which suggested that Sur-MNPs could be used to detect the expression of survivin gene. Thus, Sur-MNPs may be a potential molecular imaging probe targeting survivin gene for early detection of pancreatic cancer cells., (Copyright © 2012 John Wiley & Sons, Ltd.)

The aim of this study was to assess the inhibitory efficacy of short hairpin RNA (ShRNA) targeting vascular endothelial growth factor C (VEGF-C) in an orthotopic pancreatic cancer mouse model. BxPC-3 human pancreatic cancer cells expressing green fluorescent protein (GFP) were orthotopically implanted onto the pancreas of nude mice. All mice were randomly divided into four groups when the average tumor size had reached 100 mm(3) and were treated with either vehicle or gemcitabine at 150 mg/kg; or intravenous VEGF-C ShRNA at 150 mg/kg; or intratumoral VEGF-C ShRNA at 150 μg/kg. In vivo fluorescence imaging was performed to monitor tumor growth and metastasis during the study. Real-time quantitative polymerase chain reaction (RT-qPCR) and an enzyme-linked immunosorbent assay (ELISA) were performed to determine the mRNA and protein level of VEGF-C in tumor tissues. Lymphatic vessel marker D2-40, blood vessel marker CD31 and proliferation marker Ki67 expression of the tumor tissues were analyzed by immunohistochemistry staining. Intravenous and intratumoral VEGF-C ShRNA treatment significantly inhibited tumor growth, downregulated the expression of VEGF-C mRNA, reduced tumor microlymphatic vessel density (MLVD), and inhibited cancer cell proliferation. Gemcitabine, as the standard treatment for pancreatic cancer, demonstrated a stronger inhibitory effect on tumor growth, with less inhibition of MLVD and more inhibition of microvessel density (MVD) and proliferation than VEGF-C ShRNA. These results indicate that different mechanisms are associated with the efficacy of gemcitabine and VEGF-C ShRNA.

Lymphatic vessels in primary tumor tissue play an important role in lymphatic metastasis. Lymphatic metastasis of malignant neoplasms is significantly related to prognosis, influencing both recurrence and survival. The aim of this study was to investigate the correlation of intra-tumoral lymphatic vessel density (iLVD) and peri-tumoral lymphatic vessel density (pLVD) with biological behavior and prognostic parameters in pancreatic carcinoma (PC) and other pancreatic tumors. Lymphangiogenesis was examined using the D2-40 monoclonal antibody in 33 cases of PC, 7 neuroendocrine tumors of the pancreas (NETP), 7 solid pseudopapillary tumors of the pancreas (SPTP) and 3 cystadenomas of the pancreas (CP). Positively-stained microvessels were counted at magnification x400 in dense lymphatic vascular foci (hotspots). The LVD of PC was compared to 3 other pancreatic tumors. The relationships among the LVD, the extent of differentiation, lymphatic invasion, lymph node metastasis and other clinicopathological parameters of PC were analyzed. There was no difference in the iLVD among PC, NETP, SPTP and CP. The pLVD of NETP was markedly higher than that of PC, SPTP and CP. The pLVD of PC was significantly higher than that of SPTP and CP, but there was no difference between SPTP and CP. The pLVD of PC was significantly associated with the extent of differentiation, lymphatic invasion and lymph node metastasis, whereas it was not associated with age, gender, tumor size, tumor location and peri-pancreatic invasion. The iLVD of PC was not correlated with these clinicopathological parameters. There was no difference in iLVD and no marked difference in pLVD among the pancreatic tumors. Detection of pLVD is of greater importance than detecting iLVD in these pancreatic tumors, as pLVD can be utilized for the prediction of lymph node metastasis, thus aiding in the evaluation of patient prognosis.