Factors affecting the diagnostic value of liquid-based cytology by EUS-FNA in the diagnosis of pancreatic cystic neoplasms.

Background and Objectives: This study retrospectively evaluated the value of liquid-based cytology (LBC) alone for diagnosing pancreatic cystic neoplasms (PCNs) in a large sample and initially estimated factors that might affect LBC diagnostic ability. Methods: From April 2015 to October 2022, we prospectively enrolled 331 patients with suspected PCNs in our prospective database. Among them, 112 patients chosen to receive surgical resection were included. Only 96 patients who underwent EUS-guided cystic fluid LBC were finally studied. The diagnostic values of LBC for differentiating benign and malignant PCNs and subtypes of PCNs were evaluated. Results: There were 71 female and 25 male patients with a mean age of 47.6 ± 14.4 years. The median cyst size was 43.4 mm. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of LBC for the differentiation of benign and malignant PCNs were 96.9%, 57.1%, 100%, 100%, and 96.7%, respectively. The overall diagnostic accuracy of LBC for specific cyst types was 33.3% (32/96). Cysts located in the pancreatic body/tail or with irregular shapes were more likely to obtain a definite LBC diagnosis. At the same time, age, sex, tumor size, cystic fluid viscosity, operation time, needle type, and presence of septation were not significantly different. Conclusion: Liquid-based cytology alone is useful for differentiating benign PCNs from malignant PCNs and can successfully characterize the PCN subtypes in one-third of patients. Pancreatic cystic neoplasms located in the body/tail or exhibiting irregular shapes are more likely to obtain a definite LBC diagnosis.

Current considerations on intraductal papillary neoplasms of the bile duct and pancreatic duct.

Pancreatobiliary intraductal papillary neoplasms (IPNs) represent precursors of pancreatic cancer or bile duct cholangiocarcinoma that can be detected and treated. Despite advances in diagnostic methods, identifying these premalignant lesions is still challenging for treatment providers. Modern imaging, biomarkers and molecular tests for genomic alterations can be used for diagnosis and follow-up. Surgical intervention in combination with new chemotherapeutic agents is considered the optimal treatment for malignant cases. The balance between the risk of malignancy and any risk of resection guides management policy; therefore, treatment should be individualized based on a meticulous preoperative assessment of high-risk stigmata. IPN of the bile duct is more aggressive; thus, early diagnosis and surgery are crucial. The conservative management of low-risk pancreatic branch-duct lesions is safe and effective.

Robotic-assisted organ-preserving or parenchymal-sparing pancreatectomy in pancreatic benign or low-grade malignant tumors: a single institute's experience.

AIM: Robotic-assisted pancreatectomy has been widely used. Organ-preserving pancreatectomy (OPP) and parenchymal-sparing pancreatectomy (PSP) has been gradually adopted for pancreatic benign or low-grade malignant tumors. This study aimed to evaluate the safety and efficacy of robotic-assisted OPP/PSP in our institute. METHODS: Patients undergoing robotic-assisted OPS/PSP at First Affiliated Hospital of Sun Yat-sen University between July 2015 and October 2021 were included in this study. The short-term and long-term outcomes of patients were retrospectively analyzed. RESULTS: Seventy-two patients were enrolled, including spleen-preserving distal pancreatectomy, central pancreatectomy, duodenum-preserving pancreatic head resection, and enucleation. Patients included were more likely to be young female (female: 46/72, median age: 47 years old). The median intraoperative blood loss and operation time was 50 ml and 255 min, respectively. Clinically relevant postoperative pancreatic fistula was 20.8% (grade B: 15/72, 20.8%; no grade C). The overall complication rate was 22.2% with the median postoperative length-of-stay of 8 days. At a median follow-up time of 28.5 months, the 5-year overall survival and recurrence-free survival rate were 100.0% and 100.0%, respectively. CONCLUSION: The short-term and long-term outcomes of patients receiving robotic-assisted OPP/PSP were acceptable. Robotic-assisted OPP/PSP was a feasible and safe technique for pancreatic benign or low-grade malignant lesions.

Application of a pyramid pooling Unet model with integrated attention mechanism and Inception module in pancreatic tumor segmentation.

BACKGROUND: The segmentation and recognition of pancreatic tumors are crucial tasks in the diagnosis and treatment of pancreatic diseases. However, due to the relatively small proportion of the pancreas in the abdomen and significant shape and size variations, pancreatic tumor segmentation poses considerable challenges. PURPOSE: To construct a network model that combines a pyramid pooling module with Inception architecture and SE attention mechanism (PIS-Unet), and observe its effectiveness in pancreatic tumor images segmentation, thereby providing supportive recommendations for clinical practitioners. MATERIALS AND METHODS: A total of 303 patients with histologically confirmed pancreatic cystic neoplasm (PCN), including serous cystic neoplasm (SCN) and mucinous cystic neoplasm (MCN), from Shanghai Changhai Hospital between March 2011 and November 2021 were included. A total of 1792 T2-weighted imaging (T2WI) slices were used to build a CNN model. The model employed a pyramid pooling Inception module with a fused attention mechanism. The attention mechanism enhanced the network's focus on local features, while the Inception module and pyramid pooling allowed the network to extract features at different scales and improve the utilization efficiency of global information, thereby effectively enhancing network performance. RESULTS: Using three-fold cross-validation, the model constructed by us achieved a dice score of 85.49 ± 2.02 for SCN images segmentation, and a dice score of 87.90 ± 4.19 for MCN images segmentation. CONCLUSION: This study demonstrates that using deep learning networks for the segmentation of PCNs yields favorable results. Applying this network as an aid to physicians in PCN diagnosis shows potential for clinical applications.

Glucose and lactate levels are lower in EUS-aspirated cyst fluid of mucinous vs non-mucinous pancreatic cystic lesions.

BACKGROUND: Distinguishing mucinous (M) pancreatic cystic neoplasms (PCNs) from non-mucinous (NM) is challenging but crucial. Low intracystic glucose level has shown diagnostic tool promise, however further investigation is needed to understand metabolic processes. AIMS: To compare the diagnostic accuracy of intracystic glucose and CEA levels in a large cohort and explore lactate levels as potential marker. METHODS: PCNs≥15 mm which underwent EUS-fine needle aspiration were prospectively enrolled. Glucose, CEA and lactate levels were measured. Diagnostic accuracy for M-PCN diagnosis was evaluated using surgical/cytology reports or multidisciplinary evaluations. RESULTS: 169 PCNs were included (64 % M-PCNs). Median intracystic glucose was significantly lower in M-PCNs (1 mg/dL) compared to NM-PCNs (101 mg/dL); mean intracystic CEA was significantly higher in M-PCNs (152.5 ng/mL) compared to NM-PCNs (0.3 ng/mL). ROC curve analysis revealed best glucose cut-off ≤58 mg/dL (accuracy 93.5 %) and CEA cut-off >2.5 ng/mL (accuracy 90.5 %) for M-PCNs. Intracystic lactates were significantly lower in M-PCNs correlating directly with glucose. Single glucose dosage evidenced best diagnostic accuracy respect markers combination. CONCLUSION: Intracystic glucose demonstrated high diagnostic utility for M-PCNs differentiation, surpassing CEA. Lactate levels correlated with glucose, suggesting their uptake by M-PCNs cells. These findings contribute to a better metabolic landscape understanding glucose use as diagnostic marker.

Surgical outcomes of resected cystic neoplasms of pancreas: Experience from a tertiary care centre in India.

Objectives: Cystic neoplasms of the pancreas form a rare heterogeneous group of pancreatic tumors with variable clinical and diagnostic characteristics. Its incidence has increased in recent years due to improvements in cross-sectional imaging methods and awareness amongst surgeons. Material and Methods: This study aimed to study the demographic, clinical, imaging, and histopathologic characteristics, incidence of malignancy and outcome of surgical resection of pancreatic cystic neoplasms. Retrospective analysis of 91 patients who underwent surgical resection for cystic neoplasm of the pancreas between 2006 to 2017 at a tertiary care institute was done. Results: There was a female preponderance in the study with a mean age of 47.2 years. Abdominal pain (46.1%) and jaundice (23.1%) were the most common symptoms. Computed tomography and endoultrasound (EUS) were the most commonly used imaging methods in the study and demonstrated good surgical correlation. Pancreaticoduodenectomy (37.1%) was the most commonly performed procedure followed by distal pancreaticosplenectomy (31.8%). Of the lesions, 9.8% were found malignant. Solid pseudopapillary epithelial neoplasm (SPEN) (37.3%) was the most common neoplasm followed by serous (21.9%), intraductal papillary mucinous neoplasm (IPMN) (15.3%) and mucinous neoplasm (14.3%). Preoperative radiological diagnostic correlation was found to be 75-100% implying the importance of imaging in cystic neoplasms of the pancreas. Morbidity and mortality in the study group were 28.5% and 2.1%, respectively. Conclusion: Pancreatic cystic neoplasms were mostly benign with female preponderance and presented in the younger age group with prevalence of SPEN higher than IPMN in our subcontinent. These can be reliably diagnosed on preoperative cross-sectional imaging, and surgical resection is associated with favourable outcome and acceptable morbidity.

The level of glucose in pancreatic cyst fluid is more accurate than carcinoembryonic antigen to identify mucinous tumors: A French multicenter study.

Background and Objectives: Pancreatic cyst fluid level of glucose is a promising marker to identify mucinous from nonmucinous tumors, but the glucose assay has not yet been recommended. The objective of this study is to compare the diagnostic performances of pancreatic cyst fluid level of glucose and carcinoembryonic antigen (CEA). Methods: In this French multicenter study, data of consecutive patients who underwent fine-needle aspiration of pancreatic cyst with intracyst glucose assay between 2018 and 2022 were retrospectively reviewed. The area under the receiver operating characteristic curve (AUROC) of glucose and corresponding sensitivity (Se), specificity (Sp), accuracy (Acc), positive predictive value (PPV), and negative predictive value (NPV) were calculated and compared with those of CEA. The best threshold of glucose was identified using the Youden index. Results: Of the 121 patients identified, 81 had a definitive diagnosis (46 mucinous, 35 nonmucinous tumors) and were included for analysis. An intracystic glucose level <41.8 mg/dL allowed identification of mucinous tumors with better diagnostic performances (AUROC, 93.6%; 95% confidence interval, 87.2%-100%; Se, 95.3%; Sp, 91.2%; Acc, 93.5%; PPV, 93.2%; NPV, 93.9%) compared with CEA level >192 ng/mL (AUROC, 81.2%; 95% confidence interval, 71.3%-91.1%; Se, 41.7%; Sp, 96.9%; Acc, 67.6%; PPV, 93.8%; NPV, 59.6%) (P = 0.035). Combining values of glucose and CEA did not offer additional benefit in terms of diagnosis. Conclusion: Our results confirm previously published data and support the use of pancreatic cyst fluid glucose for the identification of mucinous tumors when the definitive diagnosis remains uncertain.

Radiomics Based on Contrast-Enhanced Ultrasound Images for Diagnosis of Pancreatic Serous Cystadenoma.

OBJECTIVE: The purpose of the study was to develop and validate a radiomics model by using contrast-enhanced ultrasound (CEUS) data for pre-operative differential diagnosis of pancreatic cystic neoplasms (PCNs), especially pancreatic serous cystadenoma (SCA). METHODS: Patients with pathologically confirmed PCNs who underwent CEUS examination at Chinese PLA hospital from May 2015 to August 2022 were retrospectively collected. Radiomic features were extracted from the regions of interest, which were obtained based on CEUS images. A support vector machine algorithm was used to construct a radiomics model. Moreover, based on the CEUS image features, the CEUS and the combined models were constructed using logistic regression. The performance and clinical utility of the optimal model were evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity and decision curve analysis. RESULTS: A total of 113 patients were randomly split into the training (n = 79) and test cohorts (n = 34). These patients were pathologically diagnosed with SCA, mucinous cystadenoma, intraductal papillary mucinous neoplasm and solid-pseudopapillary tumor. The radiomics model achieved an AUC of 0.875 and 0.862 in the training and test cohorts, respectively. The sensitivity and specificity of the radiomics model were 81.5% and 86.5% in the training cohort and 81.8% and 91.3% in the test cohort, respectively, which were higher than or comparable with that of the CEUS model and the combined model. CONCLUSION: The radiomics model based on CEUS images had a favorable differential diagnostic performance in distinguishing SCA from other PCNs, which may be beneficial for the exploration of personalized management strategies.

Clinical characteristics and survival prediction of surgical patients with invasive pancreatic cystic neoplasm: a large retrospective study over two decades.

PURPOSES: Invasive pancreatic cystic neoplasms (iPCNs) are an uncommon and biologically heterogeneous group of malignant neoplasms. We aimed to investigate the clinicopathological characteristics of iPCN patients and to develop nomograms for individual survival prediction after radical surgery. METHODS: Data of patients diagnosed with iPCN and pancreatic ductal adenocarcinoma (PDAC) between 2000 and 2018 from the SEER database were retrieved. The differences in clinical outcomes were evaluated using the Kaplan-Meier analysis. Nomograms were proposed based on the Cox regression model and internally validated by C-index, area under the curve (AUC) value, and calibration plot. RESULTS: A total of 7777 iPCN patients and 154,336 PDAC patients were enrolled. Most neoplasms were advanced, with 63.1% at stage IV. The 3-year overall survival (OS) and cancer-specific survival (CSS) rates in surgical patients were as follows: 45.7% and 50.1% for invasive intraductal papillary mucinous neoplasm (IPMN), 54.8% and 59.3% for invasive mucinous cystic neoplasm (MCN), 97.8% and 98.2% for invasive solid pseudopapillary neoplasm (SPN), 88.9% and 88.9% for invasive serous cystic neoplasm (SCN), and 27.3% and 30.5% for PDAC. Subgroup analyses showed no clinical benefit from chemotherapy or radiotherapy in lymph node-negative iPCN patients who underwent surgery. The following variables associated with OS and CSS were identified: age, race, chemotherapy, radiotherapy, histologic type, pathological grade, regional nodes examined, and T, N, and M stage. The nomograms had good discrimination and calibration by internal validation, with an AUC value of 0.800 for 3-year OS and 0.814 for 3-year CSS. CONCLUSION: Our study showed that the prognosis of iPCN patients was significantly better than PDAC patients. The proposed nomograms demonstrated substantially better discrimination and calibration.

Endoscopic Ultrasound-Guided Local Ablative Therapies for the Treatment of Pancreatic Neuroendocrine Tumors and Cystic Lesions: A Review of the Current Literature.

Since its emergence as a diagnostic modality in the 1980s, endoscopic ultrasound (EUS) has provided the clinician profound access to gastrointestinal organs to aid in the direct visualization, sampling, and subsequent identification of pancreatic pathology. In recent years, advancements in EUS as an interventional technique have promoted the use of local ablative therapies as a minimally invasive alternative to the surgical management of pancreatic neuroendocrine tumors (pNETs) and pancreatic cystic neoplasms (PCNs), especially for those deemed to be poor operative candidates. EUS-guided local therapies have demonstrated promising efficacy in addressing a spectrum of pancreatic neoplasms, while also balancing local adverse effects on healthy parenchyma. This article serves as a review of the current literature detailing the mechanisms, outcomes, complications, and limitations of EUS-guided local ablative therapies such as chemical ablation and radiofrequency ablation (RFA) for the treatment of pNETs and PCNs, as well as a discussion of future applications of EUS-guided techniques to address a broader scope of pancreatic pathology.

Pancreatic Cystic Lesions: Imaging Techniques and Diagnostic Features.

The detection of incidental pancreatic cystic lesions has increased over time. It is crucial to separate benign from potentially malignant or malignant lesions to guide management and reduce morbidity and mortality. The key imaging features used to fully characterize cystic lesions are optimally assessed by contrast-enhanced magnetic resonance imaging/magnetic resonance cholangiopancreatography, with pancreas protocol computed tomography offering a complementary role. While some imaging features have high specificity for a particular diagnosis, overlapping imaging features between diagnoses may require further investigation with follow-up diagnostic imaging or tissue sampling.

Pancreatic Cystic Lesions: Next Generation of Radiologic Assessment.

Pancreatic cystic lesions are frequently identified on cross-sectional imaging. As many of these are presumed branch-duct intraductal papillary mucinous neoplasms, these lesions generate much anxiety for the patients and clinicians, often necessitating long-term follow-up imaging and even unnecessary surgical resections. However, the incidence of pancreatic cancer is overall low for patients with incidental pancreatic cystic lesions. Radiomics and deep learning are advanced tools of imaging analysis that have attracted much attention in addressing this unmet need, however, current publications on this topic show limited success and large-scale research is needed.

Endoscopic Imaging of Pancreatic Cysts.

Pancreatic cystic lesions (PCLs) have been diagnosed with increasing frequency likely due to the widespread use of cross-sectional imaging. A precise diagnosis of the PCL is important because it helps identify patients in need of surgical resection and those who can undergo surveillance imaging. A combination of clinical and imaging findings as well as cyst fluid markers can help classify PCLs and guide management. This review focuses on endoscopic imaging of PCLs including endoscopic and endosonographic features and fine needle aspiration. We then review the role of adjunct techniques, such as microforceps, contrast-enhanced endoscopic ultrasound, pancreatoscopy, and confocal laser endomicroscopy.

Role of Endoscopic Ultrasound in the Evaluation of Pancreatic Cystic Neoplasms: A Concise Review.

Pancreatic cystic lesions are being discovered as incidental lesions during cross-sectional imaging studies of the abdomen with increasing frequency. Endoscopic ultrasound is an important diagnostic modality for managing pancreatic cystic lesions. There are various types of pancreatic cystic lesions, from benign to malignant. Endoscopic ultrasound has a multifactorial role in delineating the morphology of pancreatic cystic lesions, ranging from fluid and tissue acquisition for analysis-fine needle aspiration and through-the-needle biopsy, respectively-to advanced imaging techniques, such as contrast-harmonic mode endoscopic ultrasound and EUS-guided needle-based confocal laser endomicroscopy. In this review, we will summarize and provide an update on the specific role of EUS in the management of pancreatic cystic lesions.

Validation of combined carcinoembryonic antigen and glucose testing in pancreatic cyst fluid to differentiate mucinous from non-mucinous cysts.

BACKGROUND: More accurate diagnosis of mucinous cysts will reduce the risk of unnecessary pancreatic surgery. Carcinoembryonic antigen (CEA) and glucose in pancreatic cyst fluid (PCF) can differentiate mucinous from non-mucinous pancreatic cystic neoplasms (PCN). The current study assessed the value of combined CEA and glucose testing in PCF. METHODS: Cross-sectional validation study including prospectively collected PCF from patients undergoing endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) and pancreatic surgery. We performed laboratory measurements for CEA and glucose and measured glucose levels by a hand glucometer. Primary outcome was diagnostic accuracy evaluated by receiver operator curves (ROC), sensitivity, specificity, positive, and negative predictive value (PPV, NPV). RESULTS: Overall, PCF was collected from 63 patients, including 33 (52%) with mucinous and 30 (48%) with non-mucinous PCN. Histopathology (n = 36; 57%), cytopathology (n = 2; 3%), or clinical and/or radiological diagnosis (n = 25; 40%) was used as reference standard. Combined CEA (cut-off ≥ 192 ng/ml) and laboratory glucose testing (cut-off ≤ 50 mg/dL) reached 92% specificity and 48% sensitivity, whereas either positive CEA (cut-off ≥ 20 ng/ml) or glucose testing (cut-off ≤ 50 mg/dL) showed 97% sensitivity and 50% specificity. Sensitivity and specificity were 80% and 68% for CEA ≥ 20 ng/mL versus 50% and 93% for CEA ≥ 192 ng/mL (the conventional cut-off level). Laboratory and glucometer glucose both reached 100% sensitivity and 60% and 45% specificity, respectively. None of the biomarkers and cut-offs reached a PPV exceeding 90%, whereas both glucose measurements had a NPV of 100% (i.e., high glucose excludes a mucinous cyst). CONCLUSION: Combined CEA and glucose testing in PCF reached high specificity and sensitivity for differentiating mucinous from non-mucinous PCN. Glucose testing, whether alone or combined with the new CEA cut-off (≥ 20 ng/mL), reached > 95% sensitivity for mucinous cysts, whereas only glucose reached a NPV > 95%.

Preoperative ultrasound combined with routine blood tests in predicting the malignant risk of pancreatic cystic neoplasms.

OBJECTIVE: Accurate preoperative identification of benign or malignant pancreatic cystic neoplasms (PCN) may help clinicians make better intervention choices and will be essential for individualized treatment. METHODS: Preoperative ultrasound and laboratory examination findings, and demographic characteristics were collected from patients. Multiple logistic regression was used to identify independent risk factors associated with malignant PCN, which were then included in the nomogram and validated with an external cohort. The Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) were calculated to evaluate the improvement in the predictive power of the new model with respect to that of a combined imaging and tumor marker prediction model. RESULTS: Malignant PCN were found in 83 (40.7%) and 33 (38.7%) of the model and validation cohorts, respectively. Multivariate analysis identified age, tumor location, imaging of tumor boundary, blood type, mean hemoglobin concentration, neutrophil-to-lymphocyte ratio, carbohydrate antigen 19-9, and carcinoembryonic antigen as independent risk factors for malignant PCN. The calibration curve indicated that the predictions based on the nomogram were in excellent agreement with the actual observations. A nomogram score cutoff of 192.5 classified patients as having low vs. high risk of malignant PCN. The model achieved good C-statistics of 0.929 (95% CI 0.890-0.968, P < 0.05) and 0.951 (95% CI 0.903-0.998, P < 0.05) in predicting malignancy in the development and validation cohorts, respectively. NRI = 0.268; IDI = 0.271 (P < 0.001 for improvement). The DCA curve indicated that our model yielded greater clinical benefits than the comparator model. CONCLUSIONS: The nomogram showed excellent performance in predicting malignant PCN and may help surgeons select patients for detailed examination and surgery. The nomogram is freely available at https://wangjunjinnomogram.shinyapps.io/DynNomapp/.

Diabetes mellitus and the risk of progression or malignancy of pancreatic cystic neoplasms in patients undergoing surveillance: A systematic review and meta-analysis.

BACKGROUND/OBJECTIVES: Patients with pancreatic cystic neoplasms (PCN) generally undergo surveillance by cross-sectional imaging or endoscopic-ultrasound due to their pre-malignant potential. Appearance of certain cyst characteristics during surveillance is associated with aggressive behavior or presence of malignancy. Patient characteristics associated with progression or induction of malignancy in PCN is unclear from current studies. We performed this meta-analysis to determine the patient characteristics associated with progression or malignancy in patients with PCN who undergo surveillance. METHODS: We performed a systematic research of several electronic databases for all the studies on surveillance of PCN which reported demographic data of patients who had progression or malignancy and controls. We calculated Risk ratio (RR) or Hazard ratio (HR) with 95% confidence interval (CI) for each variable. Mantel- Haenszel method or Inverse-variance model was used to pool data of progression or malignant transformation into fixed or random effect model meta-analysis. RESULTS: 11observational studies, 4 assessing risk factors for malignancy (3955 patients) and 7 evaluating risk factors for progression of PCN (3144 patients) were included in the meta-analysis. Diabetes mellitus was associated with higher risk for malignant transformation as well as progression of PCN (RR = 1.54, CI 1.23, 1.92). Advanced age was associated with higher risk of progression. Male gender had higher risk for malignant transformation but not progression of PCN. CONCLUSION: Diabetes is associated with an increased risk of both malignancy and progression of PCN in patients who undergo surveillance. Advanced age is also associated with higher risk of progression of PCN.

Online calculator for predicting the risk of malignancy in patients with pancreatic cystic neoplasms: A multicenter, retrospective study.

BACKGROUND: Efficient and practical methods for predicting the risk of malignancy in patients with pancreatic cystic neoplasms (PCNs) are lacking. AIM: To establish a nomogram-based online calculator for predicting the risk of malignancy in patients with PCNs. METHODS: In this study, the clinicopathological data of target patients in three medical centers were analyzed. The independent sample t-test, Mann-Whitney U test or chi-squared test were used as appropriate for statistical analysis. After univariable and multivariable logistic regression analysis, five independent factors were screened and incorporated to develop a calculator for predicting the risk of malignancy. Finally, the concordance index (C-index), calibration, area under the curve, decision curve analysis and clinical impact curves were used to evaluate the performance of the calculator. RESULTS: Enhanced mural nodules [odds ratio (OR): 4.314; 95% confidence interval (CI): 1.618-11.503, P = 0.003], tumor diameter ≥ 40 mm (OR: 3.514; 95%CI: 1.138-10.849, P = 0.029), main pancreatic duct dilatation (OR: 3.267; 95%CI: 1.230-8.678, P = 0.018), preoperative neutrophil-to-lymphocyte ratio ≥ 2.288 (OR: 2.702; 95%CI: 1.008-7.244, P = 0.048], and preoperative serum CA19-9 concentration ≥ 34 U/mL (OR: 3.267; 95%CI: 1.274-13.007, P = 0.018) were independent risk factors for a high risk of malignancy in patients with PCNs. In the training cohort, the nomogram achieved a C-index of 0.824 for predicting the risk of malignancy. The predictive ability of the model was then validated in an external cohort (C-index: 0.893). Compared with the risk factors identified in the relevant guidelines, the current model showed better predictive performance and clinical utility. CONCLUSION: The calculator demonstrates optimal predictive performance for identifying the risk of malignancy, potentially yielding a personalized method for patient selection and decision-making in clinical practice.

Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions.

Endoscopic ultrasonography (EUS) is the most accurate imaging modality for the evaluation of different types of pancreatic cystic lesions. Our aim was to analyze EUS images of pancreatic cystic lesions using an image processing software. We specified the echogenicity of the lesions by measuring the gray value of pixels inside the selected areas. The images were divided into groups (serous cystic neoplasm /SCN/, intraductal papillary mucinous neoplasms and mucinous cystic neoplasms /Non-SCN/ and Pseudocyst) according to the pathology results of the lesions. Overall, 170 images were processed by the software: 81 in Non-SCN, 30 in SCN and 59 in Pseudocyst group. The mean gray value of the entire lesion in the Non-SCN group was significantly higher than in the SCN group (27.8 vs. 18.8; p < 0.0005). The area ratio in the SCN, Non-SCN and Pseudocyst groups was 57%, 39% and 61%, respectively; significantly lower in the Non-SCN group than in the SCN or Pseudocyst groups (p < 0.0005 and p < 0.0005, respectively). The lesion density was also significantly higher in the Non-SCN group compared to the SCN or Pseudocyst groups (4186.6/mm2 vs. 2833.8/mm2 vs. 2981.6/mm2; p < 0.0005 and p < 0.0005, respectively). The EUS image analysis process may have the potential to be a diagnostic tool for the evaluation and differentiation of pancreatic cystic lesions.