Cystic pancreatic lesions, the endless dilemma

Using a customized GPT to provide guideline-based recommendations for management of pancreatic cystic lesions

Background and study aims Rising prevalence of pancreatic cysts and inconsistent management guidelines necessitate innovative approaches. New features of large language models (LLMs), namely custom GPT creation, provided by ChatGPT can be utilized to integrate multiple guidelines and settle inconsistencies. Methods A custom GPT was developed to provide guideline-based management advice for pancreatic cysts. Sixty clinical scenarios were evaluated by both the custom GPT and gastroenterology experts. A consensus was reached between experts and review of guidelines and the accuracy of recommendations provided by the custom GPT was evaluated and compared with experts. Results The custom GPT aligned with expert recommendations in 87% of scenarios. Initial expert recommendations were correct in 97% and 87% of cases, respectively. No significant difference was observed between the accuracy of custom GPT and the experts. Agreement analysis using Cohen's and Fleiss' Kappa coefficients indicated consistency among experts and the custom GPT. Conclusions This proof-of-concept study shows the custom GPT's potential to provide accurate, guideline-based recommendations for pancreatic cyst management, comparable to expert opinions. The study highlights the role of advanced features of LLMs in enhancing clinical decision-making in fields with significant practice variability.

Preoperative differentiation of pancreatic cystic neoplasm subtypes on computed tomography radiomics

Background

Serous cystic neoplasm (SCN), mucinous cystic neoplasm (MCN), and intraductal papillary mucinous neoplasm (IPMN) comprise a large proportion of pancreatic cystic neoplasms (PCNs). Patients with MCN and IPMN require surgery due to the potential of malignant transformation, whereas those with SCN require periodic surveillance. However, the differential diagnosis of patients with PCNs before treatment remains a great challenge for all surgeons. Therefore, the establishment of a reliable diagnostic tool is urgently required for the improvement of precision diagnostics.

Methods

Between February 2015 and December 2020, 143 consecutive patients with PCNs who were confirmed by postoperative pathology were retrospectively included in the study cohort, then randomized into development and test cohorts at a ratio of 7:3. The predictors of preoperative clinical-radiologic parameters were evaluated by univariate and multivariable logistic regression analyses. A total of 1,218 radiomics features were computationally extracted from the enhanced computed tomography (CT) scans of the tumor region, and a radiomics signature was established by the random forest algorithm. In the development cohort, multi- and binary-class radiomics models integrating preoperative variables and radiomics features were constructed to distinguish between the 3 types of PCNs. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive efficiency of the model. An independent internal test cohort was applied to validate the classification models.

Results

All preoperative prediction models were built by integrating the radiomics signature with 13 diagnosis-related radiomics features and 3 important clinical-radiologic parameters: age, sex, and tumor diameter. The multiclass prediction model presented an overall accuracy of 0.804 in the development cohort and 0.707 in the test cohort. The binary-class prediction models displayed higher overall accuracies of 0.853, 0.866, and 0.928 in the development dataset and 0.750, 0.839, and 0.889 in the test dataset. In the test cohort, the binary-class radiomics models showed better predictive performances {AUC =0.914 [95% confidence interval (CI): 0.786 to 1.000], 0.863 (95% CI: 0.714 to 0.941), and 0.926 (95% CI: 0.824 to 1.000)} than the multiclass radiomics model [AUC =0.850 (95% CI: 0.696 to 1.000)], with a large net benefit in the decision curve analysis (DCA). The radiomics-based nomogram provided the correct predicted probability for the diagnosis of PCNs.

Conclusions

The proposed radiomics models with clinical-radiologic parameters and radiomics features help to predict the accurate diagnosis among PCNs to advance personalized medicine.

Lymphoepithelial cyst mimicking malignant pancreatic signs: a case report

BACKGROUND

A lymphoepithelial cyst of the pancreas is a rare benign lesion that is difficult to diagnose preoperatively and challenging in distinguishing from potentially malignant cystic pancreatic neoplasms. A diagnostic step-up approach is recommended to clarify the lesion's dignity and specify a treatment plan.

CASE PRESENTATION

Here, we describe a case of a 51-year-old male European with a lymphoepithelial cyst of the pancreas mimicking malignant features in a mid-age male patient with abdominal pain and unintended weight loss.

CONCLUSION

Patients with indeterminate cystic pancreatic lesions should be examined by a multidisciplinary diagnostic team in a step-up approach to clarify the lesion's entity. In the case of incidentally found lymphoepithelial cysts of the pancreas, a watchful waiting strategy might be clinically reasonable if the diagnosis is proven.

The Latest Advancements in Diagnostic Role of Endosonography of Pancreatic Lesions

Endosonography, a minimally invasive imaging technique, has revolutionized the diagnosis and management of pancreatic diseases. This comprehensive review highlights the latest advancements in endosonography of the pancreas, focusing on key technological developments, procedural techniques, clinical applications and additional techniques, which include real-time elastography endoscopic ultrasound, contrast-enhanced-EUS, EUS-guided fine-needle aspiration or EUS-guided fine-needle biopsy. EUS is well established for T-staging and N-staging of pancreaticobiliary malignancies, for pancreatic cyst discovery, for identifying subepithelial lesions (SEL), for differentiation of benign pancreaticobiliary disorders or for acquisition of tissue by EUS-guided fine-needle aspiration or EUS-guided fine-needle biopsy. This review briefly describes principles and application of EUS and its related techniques.

Using Endoscopy in the Diagnosis of Pancreato-Biliary Cancers

Pancreatic cancer and cholangiocarcinoma are life threatening oncological conditions with poor prognosis and outcome. Pancreatic cystic lesions are considered precursors of pancreatic cancer as some of them have the potential to progress to malignancy. Therefore, accurate identification and classification of these lesions is important to prevent the development of invasive cancer. In the biliary tract, the accurate characterization of biliary strictures is essential for providing appropriate management and avoiding unnecessary surgery. Techniques have been developed to improve the diagnosis, risk stratification, and management of pancreato-biliary lesions. Endoscopic ultrasound (EUS) and associated techniques, such as elastography, contrasted-enhanced EUS, and EUS-guided needle confocal laser endomicroscopy, may improve diagnostic accuracy. In addition, intraductal techniques applied during endoscopic retrograde cholangiopancreatography (ERCP), such as new generation cholangioscopy and in vivo cellular evaluation through probe-based confocal laser endomicroscopy, can increase the diagnostic yield in characterizing indeterminate biliary strictures. Both EUS-guided and intraductal approaches can provide the possibility for tissue sampling with new tools, such as needles, biopsies forceps, and brushes. At the molecular level, novel biomarkers have been explored that provide new insights into diagnosis, risk stratification, and management of these lesions.

EUS-guided FNAC in intra-abdominal lesions: Technique of tissue acquisition, ancillary testing, pearls and perils, and prospects

Endoscopic ultrasound enables visualization of lesions within and in the vicinity of the gastrointestinal tract. Endoscopic ultrasound guided fine needle aspiration cytology (EUS-FNAC) helps in targeting various luminal and extraluminal lesions both diagnostically and therapeutically. Various intra-abdominal organs amenable to EUS-FNA include the gastrointestinal tract (GIT), pancreas, kidney, adrenal gland, liver, bile duct, gallbladder, spleen, and lymph nodes. EUS-FNAC is mostly done for pancreatic and intra-abdominal lymph nodal lesions. In the present review, we have discussed various aspects of EUS-FNAC.

Pancreatic serous cystic neoplasm mimicking intraductal papillary mucinous neoplasm: Two case reports and literature review

RATIONALE

Serous cystic neoplasms (SCNs) are treated as benign lesions. It is widely known that SCN rarely have a connection with the main pancreatic duct (MPD), which helps differentiate them from other cystic lesions, such as intraductal papillary mucinous neoplasm (IPMN). However, very rare cases where the SCN appears connected to the MPD cause diagnostic confusion.

PATIENT CONCERNS

We present 2 patients with SCN (1 male, 54, and 1 female, 42). Both patients were asymptomatic, without abnormal laboratory results.

DIAGNOSIS

In both cases, abdominopelvic computed tomography and pancreatic magnetic resonance imaging scans revealed a multilobulated cystic lesion in communication with the MPD. Since the size of each patient's lesion was >3 cm and there was connectivity with the MPD, it was strongly suspected to be a branch duct-type IPMN with worrisome features rather than SCN and surgical intervention was considered.

INTERVENTIONS

Both neoplasms were misdiagnosed as IPMN due to appearing connected with the MPD on radiologic imaging. Surgery was performed.

OUTCOMES

A final diagnosis of microcystic serous cystadenoma of the pancreas without connectivity of MPD was confirmed in both patients.

LESSONS

An unnecessary surgery was performed due to atypical radiologic features in which the pancreatic duct seems to be connected to the pancreatic cystic lesion on magnetic resonance imaging, leading to misdiagnosis of SCN as IPMN. Particular attention should be paid to interpretation of clinicoradiologic findings of pancreatic cystic lesions, especially to the decision of surgical intervention. Also, awareness of presence of the atypical radiologic features of SCN may broaden the knowledge base of radiologists.

LESSONS

An unnecessary surgery was performed due to atypical radiologic features in which the pancreatic duct seems to be connected to the pancreatic cystic lesion on magnetic resonance imaging, leading to misdiagnosis of SCN as IPMN. Particular attention should be paid to interpretation of clinicoradiologic findings of pancreatic cystic lesions, especially to the decision of surgical intervention. Also, awareness of presence of the atypical radiologic features of SCN may broaden the knowledge base of radiologists.

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.

Lower cyst fluid carcinoembryonic antigen cutoff is helpful in the differential diagnosis of mucinous versus non-mucinous pancreatic cysts

BACKGROUND AND AIM

Pancreatic cystic lesions (PCLs) are being diagnosed with increased frequency and have varying neoplastic potential. We conducted this multimodal, prospective study to evaluate  the role of tumor cytology and molecular markers to differentiate PCL subtypes.

METHODS

Consecutive undiagnosed patients with PCLs (n = 100, mean age: 50.37 years; 41% males) were prospectively studied. Cyst fluid carcinoembryonic antigen (CEA), CA19.9, CA125, CA72.4, and vascular endothelial growth factor-alpha (VEGF-α) levels were measured by quantitative enzyme-linked immunosorbent assay (ELISA) method. Mutational analysis of the KRAS gene (exon 2, Codon 12 and 13) and GNAS gene (Exon 8, Codon 201) were performed by Sanger's sequencing.

RESULTS

The mean cyst size was 4.32 ± 2.4 cm. Fluid cytology revealed definitive diagnosis in 21 (22.3%) patients. All malignant PCLs could be identified on cytology whereas 10/14 (71%) non-malignant mucinous PCLs could also be identified on cytology based on mucin staining. Among the tested tumor markers, cyst fluid CEA had the best diagnostic performance for differentiation between mucinous and non-mucinous PCLs (AUC 0.933 [95% CI 0.86-0.91]). At a cyst fluid CEA cutoff level of 45.0 ng/mL, the sensitivity, specificity, positive predictive value, and negative predictive value for differentiation between mucinous and non-mucinous cysts were 88.5%, 96.8%, 92.0%, and 95.3%, respectively (p &lt; 0.05). KRAS and GNAS mutation had no significant diagnostic benefit in comparison to fluid cytology and CEA levels.

CONCLUSIONS

Fluid CEA at a lower cutoff of 45 ng/mL is the most accurate marker to differentiate between mucinous and non-mucinous PCL. The KRAS and GNAS mutational analysis does not improve upon the diagnostic performance of fluid cytology and tumor markers.

Pancreatic cyst dilemma: Between physical and biochemical markers

Physical analysis of the pancreatic cystic lesions (PCLs) fluid as expressed by the rheological behavior (“string sign”) can improve the diagnostic yield and should be integrated in every multimodal PCLs workup.