Pancreatic cysts are mostly incidental findings on computed tomography or magnetic resonance imaging scans, with few patients presenting with abdominal pain or other symptoms. The accurate diagnosis of cysts is important as management depends on the type (neoplastic or non-neoplastic). Cross-sectional imaging is fast being replaced with endoscopic ultrasound (EUS) and various techniques based on that such as EUS-guided fine needle aspiration, EUS-guided needle confocal laser endomicroscopy, EUS-through-the-needle biopsy, and contrast-enhanced EUS. Clinical studies have reported varying diagnostic and adverse event rates with these modalities. In addition, American, European, and Kyoto guidelines for the diagnosis and management of pancreatic cysts have provided different recommendations. In this editorial, we elaborate on the clinical guidelines, recent studies, and comparison of different endoscopic methods for the diagnosis of pancreatic cysts.

Endoscopic ultrasound (EUS)-guided tissue sampling includes the techniques of fine needle aspiration (FNA) and fine needle biopsy (FNB), and both procedures have revolutionized specimen collection from the gastrointestinal tract, especially from remote/inaccessible organs. EUS-FNB has replaced FNA as the procedure of choice for tissue acquisition in solid pancreatic lesions (SPLs) across various society guidelines. FNB specimens provide a larger histological tissue core (preserving tissue architecture) with fewer needle passes, and this is extremely relevant in today's era of precision and personalized molecular medicine. Innovations in needle tip design are constantly under development to maximize diagnostic accuracy by enhancing histological sampling capabilities. But, apart from the basic framework of the needle, various other factors play a role that influence diagnostic outcomes, namely, sampling techniques (fanning, aspiration or suction, and number of passes), collection methods, on-site evaluation (rapid, macroscopic, or visual), and specimen processing. The choice taken depends strongly on the endoscopist's preference, available resources at the disposal, and procedure objectives. Hence, in this review, we explicate in detail the concepts and available literature at our disposal on the topic of EUS-guided pancreatic tissue sampling to best guide any practicing gastroenterologist/endoscopist in a not-to-ideal set-up, which EUS-guided tissue acquisition technique is the "best" for their case to augment their diagnostic outcomes.

Detective flow imaging EUS (DFI-EUS) is a new technology that detects fine vessels and low-flow velocity without contrast agents, used in real time during EUS, with a better resolution compared to usual technologies such as color Doppler and eFLOW. The aim of this study was to compare DFI-EUS with contrast-enhanced EUS (CE-EUS) for the evaluation of vascularization in solid pancreatic lesions.

We included patients who had a pancreatic mass visualized by EUS, with recorded images of their assessment in DFI-EUS and CE-EUS techniques and a histological diagnosis confirmed malignant tumors or a minimum of 1-year follow-up for benign lesions.

Of the 107 patients included in this retrospective single-center study, the histological diagnosis revealed 69 cases (64.5%) of pancreatic adenocarcinoma, 18 cases (16.8%) of neuroendocrine tumors (NETs), and 10 cases (9.3%) of metastases from nonpancreatic cancers. A smaller proportion (9.4%) exhibited other lesions. As a result, the incidence of intralesional microvascularization was 43.9% with DFI-EUS and 48.6% with CE-EUS, indicating a positive correlation between the 2 techniques (P = 0.0001). Compared to CE-EUS, DFI-EUS exhibited sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 88.5%, 98.2%, 97.9%, and 90%, respectively, for the detection of intralesional vessels.

The novel technique DFI-EUS demonstrates a remarkable correlation with CE-EUS, exhibiting high sensitivity and specificity for the assessment of microvascularization in solid pancreatic lesions. This method eliminates the need for a contrast agent, thus carrying no risk of adverse effects.

The differential diagnosis of solid pancreatic lesions (SPLs) using B-mode endoscopic ultrasonography (EUS) is challenging. Detective flow imaging (DFI) offers the potential for detecting low-flow vessels in the pancreas, thus enhancing diagnostic accuracy. This retrospective study aimed to investigate DFI-EUS findings of SPLs and analyze their differential diagnostic accuracy for pancreatic cancer. We included 104 patients with pathologically confirmed SPLs who underwent EUS between April 2021 and June 2023. Expert endosonographers, blinded to the patients' clinical data, evaluated images obtained through B-mode, eFLOW, and DFI-EUS. The frame rate and vessel detection sensitivity were compared between eFLOW and DFI, and the diagnostic criteria for pancreatic cancer were established. The visualization rate for vessels in SPLs was significantly higher with DFI-EUS (96%) compared to eFLOW (27%). Additionally, DFI showed a superior frame rate, sensitivity (99%), and accuracy (88%) for detecting pancreatic cancer, although with a modest specificity (43%). On DFI-EUS, characteristics such as hypovascularity, peritumoral vessel distribution, or spotty vessel form were suggestive of pancreatic cancer. DFI-EUS significantly improved the visualization of vascular structures within the SPLs, highlighting its efficacy as a diagnostic modality for pancreatic cancer.

Differentiating pancreatic cystic lesions (PCLs) remains a diagnostic challenge. The use of high-definition imaging modalities which detect tumor microvasculature have been described in solid lesions. We aim to evaluate the usefulness of cystic microvasculature when used in combination with cyst fluid biochemistry to differentiate PCLs.

We retrospectively analyzed 110 consecutive patients with PCLs from 2 Italian Hospitals who underwent EUS with H-Flow and EUS fine needle aspiration to obtain cystic fluid. The accuracy of fluid biomarkers was evaluated against morphological features on radiology and EUS. Gold standard for diagnosis was surgical resection. A clinical and radiological follow up was applied in those patients who were not resected because not surgical indication and no signs of malignancy were shown.

Of 110 patients, 65 were diagnosed with a mucinous cyst, 41 with a non-mucinous cyst, and 4 with an undetermined cyst. Fluid analysis alone yielded 76.7% sensitivity, 56.7% specificity, 77.8 positive predictive value (PPV), 55.3 negative predictive value (NPV) and 56% accuracy in diagnosing pancreatic cysts alone. Our composite method yielded 97.3% sensitivity, 77.1% specificity, 90.1% PPV, 93.1% NPV, 73.2% accuracy.

This new composite could be applied to the holistic approach of combining cyst morphology, vascularity, and fluid analysis alongside endoscopist expertise.

Early detection of pancreatic cancer has long eluded clinicians because of its insidious nature and onset. Often metastatic or locally invasive when symptomatic, most patients are deemed inoperable. In those who are symptomatic, multi-modal imaging modalities evaluate and confirm pancreatic ductal adenocarcinoma. In asymptomatic patients, detected pancreatic lesions can be either solid or cystic. The clinical implications of identifying small asymptomatic solid pancreatic lesions (SPLs) of < 2 cm are tantamount to a better outcome. The accurate detection of SPLs undoubtedly promotes higher life expectancy when resected early, driving the development of existing imaging tools while promoting more comprehensive screening programs. An imaging tool that has matured in its reiterations and received many image-enhancing adjuncts is endoscopic ultrasound (EUS). It carries significant importance when risk stratifying cystic lesions and has substantial diagnostic value when combined with fine needle aspiration/biopsy (FNA/FNB). Adjuncts to EUS imaging include contrast-enhanced harmonic EUS and EUS-elastography, both having improved the specificity of FNA and FNB. This review intends to compile all existing enhancement modalities and explore ongoing research around the most promising of all adjuncts in the field of EUS imaging, artificial intelligence.