Search Results (720)

The advancement of artificial intelligence (AI), deep learning, and radiomics has introduced novel methodologies for the detection, classification, prognosis, and treatment evaluation of pancreatic ductal adenocarcinoma (PDAC). As the integration of AI into medical imaging continues to evolve, its potential to enhance early detection, refine diagnostic precision, and optimize treatment strategies becomes increasingly evident. However, despite significant progress, various challenges remain, particularly in terms of clinical applicability, generalizability, interpretability, and integration into routine practice. Understanding the current state of research is crucial for identifying gaps in the literature and exploring opportunities for future advancements. This literature review aims to provide a comprehensive overview of the existing studies on AI applications in PDAC, with a focus on disease detection, classification, survival prediction, treatment response assessment, and radiogenomics. By analyzing the methodologies, findings, and limitations of these studies, we aim to highlight the strengths of AI-driven approaches while addressing critical gaps that hinder their clinical translation. Furthermore, this review aims to discuss future directions in the field, emphasizing the need for multi-institutional collaborations, explainable AI models, and the integration of multi-modal data to advance the role of AI in personalized medicine for PDAC. Full article

Background: A dilated main pancreatic duct (MPD) ≥ 5 mm can be observed in main-duct IPMNs (MD-IPMN) and chronic pancreatitis (CP); however, distinguishing between the two differently treated diseases can be difficult. Cell-free (cf) DNA in MPD fluid obtained by EUS-guided FNA might help to distinguish MD-IPMN from CP. Methods: All patients with a dilated MPD ≥ 5 mm on EUS during the period of 1 June 2017 to 30 April 2024 were prospectively analysed in this single-centre study, with EUS-guided MPD fluid aspiration performed for suspected MD-IPMN or CP in patients who were suitable for surgery. Twenty-two known gastrointestinal cancer genes, including GNAS and KRAS, were analysed by deep targeted (dt) NGS. The results were correlated with resected tissue, biopsy, and long-term follow-up. Results: A total of 164 patients with a dilated MPD were identified, of which 30 (18.3%) underwent EUS-guided FNA, with 1 patient having a minor complication (3.3%). Twenty-two patients (mean MPD diameter of 12.4 (7–31) mm) with a definitive, mostly surgically confirmed diagnosis were included in the analysis. Only a fish-mouth papilla, which was present in 3 of 12 (25%) MD-IPMNs, could reliably differentiate between the two diseases, with history, symptoms, diffuse or segmental MPD dilation, presence of calcifications on imaging, cytology, and CEA in the ductal fluid failing to achieve differentiation. However, GNAS mutations were found exclusively in 11 of the 12 (91.6%) patients with MD-IPMN (p < 0.01), whereas KRAS mutations were identified in both diseases. Conclusions: GNAS testing by dtNGS in aspirated fluid from dilated MPD obtained by EUS-guided FNA may help differentiate MD-IPMN from CP for surgical resection. Full article

Background: Pancreatic cystic lesions (PCLs), including intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), pose a diagnostic challenge due to their variable malignant potential. Current guidelines, such as Fukuoka and American Gastroenterological Association (AGA), have moderate predictive accuracy and may lead to overtreatment or missed malignancies. Artificial intelligence (AI), incorporating machine learning (ML) and deep learning (DL), offers the potential to improve risk stratification, diagnosis, and management of PCLs by integrating clinical, radiological, and molecular data. This is the first systematic review to evaluate the application, performance, and clinical utility of AI models in the diagnosis, classification, prognosis, and management of pancreatic cysts. Methods: A systematic review was conducted in accordance with PRISMA guidelines and registered on PROSPERO (CRD420251008593). Databases searched included PubMed, EMBASE, Scopus, and Cochrane Library up to March 2025. The inclusion criteria encompassed original studies employing AI, ML, or DL in human subjects with pancreatic cysts, evaluating diagnostic, classification, or prognostic outcomes. Data were extracted on the study design, imaging modality, model type, sample size, performance metrics (accuracy, sensitivity, specificity, and area under the curve (AUC)), and validation methods. Study quality and bias were assessed using the PROBAST and adherence to TRIPOD reporting guidelines. Results: From 847 records, 31 studies met the inclusion criteria. Most were retrospective observational (n = 27, 87%) and focused on preoperative diagnostic applications (n = 30, 97%), with only one addressing prognosis. Imaging modalities included Computed Tomography (CT) (48%), endoscopic ultrasound (EUS) (26%), and Magnetic Resonance Imaging (MRI) (9.7%). Neural networks, particularly convolutional neural networks (CNNs), were the most common AI models (n = 16), followed by logistic regression (n = 4) and support vector machines (n = 3). The median reported AUC across studies was 0.912, with 55% of models achieving AUC ≥ 0.80. The models outperformed clinicians or existing guidelines in 11 studies. IPMN stratification and subtype classification were common focuses, with CNN-based EUS models achieving accuracies of up to 99.6%. Only 10 studies (32%) performed external validation. The risk of bias was high in 93.5% of studies, and TRIPOD adherence averaged 48%. Conclusions: AI demonstrates strong potential in improving the diagnosis and risk stratification of pancreatic cysts, with several models outperforming current clinical guidelines and human readers. However, widespread clinical adoption is hindered by high risk of bias, lack of external validation, and limited interpretability of complex models. Future work should prioritise multicentre prospective studies, standardised model reporting, and development of interpretable, externally validated tools to support clinical integration. Full article

Background/Objectives: To evaluate the importance of image processing in a previously validated model for detecting pancreatic neuroendocrine tumors (PanNETs) and to introduce Image2Radiomics, a new framework that ensures reproducibility of the image processing pipeline and facilitates the deployment of radiomics models. Methods: A previously validated model for identifying PanNETs from CT images served as the reference. Radiomics features were re-extracted using Image2Radiomics and compared to those from the original model using performance metrics. The impact of nine alterations to the image processing pipeline was evaluated. Prediction discrepancies were quantified using the mean ± SD of absolute differences in PanNET probability and the percentage of classification disagreement. Results: The reference model was successfully replicated with Image2Radiomics, achieving a Cohen’s kappa coefficient of 1. Alterations to the image processing pipeline led to reductions in model performance, with AUC dropping from 0.87 to 0.71 when image windowing was removed. Prediction disagreements were observed in up to 45% of patients. Even minor changes, such as switching the library used for spatial resampling, resulted in up to 21% disagreement. Conclusions: Reproducing image processing pipelines remains challenging and limits the clinical deployment of radiomics models. While this study is limited to one model and imaging modality, the findings underscore a common risk in radiomics reproducibility. The Image2Radiomics framework addresses this issue by allowing researchers to define and share complete processing pipelines in a standardized way, improving reproducibility and facilitating model deployment in clinical and multicenter settings. Full article

Pancreatic neuroendocrine neoplasms (PNENs) are a diverse group of rare tumor subtypes, representing less than 2% of all pancreatic tumors. Often detected late in the clinical course, they are associated with high rates of morbidity and mortality. Hereditary syndromes such as multiple endocrine neoplasia type-1 and von Hippel–Lindau are associated with the development of PNENs, although only a small portion of total tumors have a genetic basis. This review aims to explore the recent advances in laboratory diagnostics, imaging modalities, medical management, and surgical approaches to hormone-producing PNENs (including some common, less common, and some rare subtypes), with the goal of assisting physicians in the integration of evidence-based information into their practice. Full article

Despite advances in surgery, chemotherapy, and radiation treatments for pancreatic ductal adenocarcinoma (PDAC), 5-year survival rates remain at nearly 11%. Cholangiocarcinoma, while not as severe, also possesses similar survival rates. Fewer than 20% of patients are surgical candidates at time of diagnosis; therefore, it is imperative that alternative therapies are effective for non-surgical patients. There are several thermal ablative techniques, including radiofrequency ablation (RFA), high-intensity focused ultrasound (HIFU), microwave ablation (MWA), alcohol ablation, stereotactic body radiotherapy (SBRT), cryoablation, irreversible electroporation (IRE), biliary intraluminal brachytherapy, and biliary photodynamic therapy (PDT). Emerging literature in animal models and human patients has demonstrated that endoscopic ultrasound (EUS)-guided RFA (EUS-RFA) prevents tumor progression through coagulative necrosis, protein denaturation, and activation of anticancer immunity in local and distant tumor tissue (abscopal effect). RFA treatment has been shown to not only reduce tumor-associated immunosuppressive cells but also increase functional T cells in distant tumor cells not treated with RFA. The remarkable ability to reduce tumor progression and promote tumor microenvironment (TME) remodeling makes RFA a very promising non-surgical therapy technique that has the potential to reduce mortality in this patient population. EUS-RFA offers superior precision and safety compared to other ablation techniques for pancreatic and biliary cancers, due to real-time imaging capabilities and minimally invasive nature. Future research should focus on optimizing RFA protocols, exploring combination therapies with chemotherapy or immunotherapy, and expanding its use in patients with metastatic disease. This review article will explore the current data and underlying pathophysiology of EUS-RFA while also highlighting the role of ablative therapies as a whole in immune activation response. Full article

Background and Objectives: Visceral arterial pseudoaneurysms (VAPAs) are rare vascular lesions characterized by the disruption of partial disruption of the arterial wall, most commonly involving the intima and media. They have an estimated incidence of 0.1–0.2%, with the splenic artery most commonly affected. Their management poses unique challenges due to the high risk of rupture. Timely recognition is crucial, as unmanaged pseudoaneurysms have a mortality rate of 90%. This narrative review aims to synthesize current knowledge regarding the epidemiology, etiology, clinical presentation, diagnostic methods, and management strategies for VAPAs. Materials and Methods: A literature search was performed across Pubmed for articles reporting on VAPAs, including case reports, review articles, and cohort studies, with inclusion of manuscripts that were up to (date). VAPAs are grouped by embryological origin—foregut, midgut, and hindgut. Results: Chronic pancreatitis is a primary cause of VAPAs, with the splenic artery being involved in 60–65% of cases. Other causes include acute pancreatitis, as well as iatrogenic trauma from surgeries, trauma, infections, drug use, and vascular diseases. VAPAs often present as abdominal pain upon rupture, with symptoms like nausea, vomiting, and gastrointestinal hemorrhage. Unruptured pseudoaneurysms may manifest as pulsatile masses or bruits but are frequently asymptomatic and discovered incidentally. Diagnosis relies on both non-invasive imaging techniques, such as CT angiography and Doppler ultrasound, and invasive methods like digital subtraction angiography, which remains the gold standard for detailed evaluation and treatment. A range of management options exists that are tailored to individual cases based on the aneurysm’s characteristics and patient-specific factors. This encompasses both surgical and endovascular approaches, with a growing preference for minimally invasive techniques due to lower associated morbidity. Conclusions: VAPAs are a critical condition requiring prompt early recognition and intervention. This review highlights the need for ongoing research to improve diagnostic accuracy and refine treatment protocols, enhancing patient outcomes in this challenging domain of vascular surgery. Full article

Pancreatic cancer is a highly lethal malignant tumor characterized by challenges in early diagnosis and limited therapeutic options, leading to an exceptionally low clinical cure rate. With the advent of novel cancer treatment paradigms, ferroptosis—a form of iron-dependent regulated cell death driven by lipid peroxidation—has emerged as a promising therapeutic strategy, particularly for tumors harboring RAS mutations. However, the poor bioavailability and insufficient tumor-targeting capabilities of conventional drugs constrain the efficacy of ferroptosis-based therapies. Recent advancements in nanotechnology and imaging-guided treatments offer transformative solutions through targeted drug delivery, real-time monitoring of treatment efficacy, and multimodal synergistic strategies. This article aims to elucidate the mechanisms underlying ferroptosis in pancreatic cancer and to summarize the latest identified therapeutic targets for ferroptosis in this context. Furthermore, it reviews the recent progress in nanotechnology-based ferroptosis therapy for pancreatic cancer, encompassing ferroptosis monotherapy, synergistic ferroptosis therapy, and endogenous ferroptosis therapy. Subsequently, the integration of imaging-guided nanotechnology in ferroptosis therapy is summarized. Finally, this paper discusses innovative strategies, such as stroma-targeted ferroptosis therapy, immune-ferroptosis synergy, and AI-driven nanomedicine development, offering new insights and directions for future research in pancreatic cancer treatment. Full article

Background: Assessing pancreatic ductal adenocarcinoma (PDAC) resectability after neoadjuvant therapy (NAT) remains a diagnostic challenge. Traditional computed tomography (CT) criteria often fail to distinguish viable tumor from fibrosis, necessitating a reassessment of imaging-based standards. Methods: A comprehensive literature review was conducted using PubMed, focusing on prospective and retrospective studies over the past 25 years that evaluated the role of CT and complementary imaging modalities (MRI, PET-CT) in predicting resectability post-NAT in non-metastatic PDAC. Studies with small sample sizes or case reports were excluded. Results: Across studies, conventional CT parameters—particularly >180° vascular encasement—showed a limited correlation with histologic invasion or surgical outcomes after NAT. Persistent vessel contact on CT often reflected fibrosis, rather than active tumor. Dynamic changes, such as regression in the tumor–vessel interface and vessel lumen restoration, correlated more accurately with R0 resection. Adjunct markers like CA 19-9 response and patient performance status further improved resectability prediction. Conclusions: CT-based resectability assessment after NAT should transition from static morphologic criteria to response-based interpretation. Multidisciplinary evaluation integrating radiologic, biochemical, and clinical findings is essential to guide surgical decision-making and improve patient outcomes. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains among the most lethal malignancies, with a five-year survival rate below 12%, largely attributable to its asymptomatic onset, late-stage diagnosis, and limited curative treatment options. Although PDAC accounts for approximately 3% of all cancers, it is projected to become the second leading cause of cancer-related mortality in the United States by 2030. A major contributor to its dismal prognosis is the lack of validated early detection strategies for asymptomatic individuals. In this review, we present a comprehensive synthesis of current advances in the early detection of PDAC, with a focus on the identification of high-risk populations, novel biomarker platforms, advanced imaging modalities, and artificial intelligence (AI)-driven tools. We highlight high-risk groups—such as those with new-onset diabetes after age 50, pancreatic steatosis, chronic pancreatitis, cystic precursor lesions, and hereditary cancer syndromes—as priority populations for targeted surveillance. Novel biomarker panels, including circulating tumor DNA (ctDNA), miRNAs, and exosomes, have demonstrated improved diagnostic accuracy in early-stage disease. Recent developments in imaging, such as multiparametric MRI, contrast-enhanced endoscopic ultrasound, and molecular imaging, offer improved sensitivity in detecting small or precursor lesions. AI-enhanced radiomics and machine learning models applied to prediagnostic CT scans and electronic health records are emerging as valuable tools for risk prediction prior to clinical presentation. We further refine the Define–Enrich–Find (DEF) framework to propose a clinically actionable strategy that integrates these innovations. Collectively, these advances pave the way for personalized, multimodal surveillance strategies with the potential to improve outcomes in this historically challenging malignancy. Full article

Pancreatic adenocarcinoma remains one of the deadliest cancers, with limited treatment options and high chemoresistance. Traditional 2D cell cultures fail to accurately replicate the tumor architecture. Our study introduces three-dimensional (3D) pancreatic adenocarcinoma spheroid models using magnetic aggregation of pancreatic cancer cells and immortalized fibroblasts in either liquid culture medium or embedded in hydrogels. The spheroids’ growth was characterized using optical imaging, while viability was assessed using ATP quantification and flow cytometry. Results demonstrated successful spheroid formation and growth. Further analysis suggested that on one hand, culture in liquid medium and ATP-based viability assessment are practical for initial experiments. On the other hand, hydrogel culture and flow cytometry, although being more resource- and labor-intensive, provided both a more reproducible and detailed viability analysis. Full article

Pancreatic cancer cells exhibit a remarkable ability to tolerate nutrient deprivation, a phenomenon termed “austerity,” which enables their survival within the hypovascular tumor microenvironment. Conventional anticancer therapies frequently fail to effectively target these resilient neoplastic cells, posing a significant challenge to the therapeutic management of pancreatic cancer. Consequently, targeting austerity, the ability of cancer cells to tolerate nutrient starvation, represents a promising anti-austerity strategy for developing novel pancreatic cancer therapeutics. In this study, we investigated calliviminone A (CVM-A), a phloroglucinol–meroterpenoid isolated from Callistemon citrinus leaves, for its anti-austerity activity against PANC-1 human pancreatic cancer cells. Calliviminone A exhibited potent preferential cytotoxicity in nutrient-deprived medium (NDM) with a PC₅₀ of 0.57 µM, while showing minimal toxicity in nutrient-rich Dulbecco’s Modified Eagle’s medium (IC₅₀ = 45.2 µM), indicating a favorable therapeutic index. Real-time live-cell imaging revealed that CVM-A induced significant morphological changes, including cell shrinkage and membrane blebbing, leading to cell death within 24 h of NDM. Furthermore, under normal nutrient conditions in Dulbecco’s Modified Eagle’s Medium (DMEM), CVM-A significantly inhibited PANC-1 cell migration (up to 47% reduction at 20 µM) and colony formation (over 80% suppression at 25 µM), suggesting its antimetastatic potential. Western blot studies demonstrated that CVM-A downregulated key survival components of the PI3K/Akt/mTOR signaling pathway, completely inhibiting Akt and p-Akt at 2.5 µM in NDM, and suppressing insulin-induced Akt activation. These findings highlight CVM-A as a promising lead compound for developing novel anticancer therapies that target the adaptive survival mechanisms and metastatic potential of pancreatic cancer in nutrient-deprived microenvironments. Full article

Background: Solid pseudopapillary neoplasm (SPN) is a rare pancreatic tumor with malignant potential. Its diagnosis has grown alongside increased use of abdominal imaging. SPN is suspected after classical findings in abdominal imaging studies; however, endoscopic ultrasound-guided (EUS) fine needle aspiration can support preoperative diagnosis. The treatment of choice is still surgical intervention, with an intent to reach curative resection. The prognosis is excellent. Recently, emerging data on EUS-guided radiofrequency ablation (RFA) suggest changing the choice of treatment for small SPN. Methods: We provide a comprehensive overview on pancreatic SPN with a focus on treatment, adverse events, recurrence rate, and outcomes. In addition, we provide a literature summary and pool data analysis. Results: Overall, 70 papers including 6651 patients were identified. The mean SPN size was 5.8 cm, metastasis rate was 1.9%, and recurrence rate was 3%. Moreover, the mortality rate was low at 0.2%, although high postoperative adverse events were reported (32.4%). Small SPN (<2 cm) was present in 4.1% of the studies. Two studies reported EUS-RFA for small SPN <2 cm, without recurrence at a median follow-up of 18.5 months. Conclusions: SPN still necessitates surgical intervention given its malignant potential. However, EUS-RFA can represent a promising and safe therapeutic option for SPN < 2 cm. Full article

Contrast-enhanced ultrasound and elastography are two ultrasound technologies that are becoming increasingly popular in the evaluation of different abdominal pathologies in children. The use of these technologies has expanded the diagnostic scope of ultrasound into areas that were traditionally covered by advanced imaging modalities such as computed tomography, magnetic resonance imaging, and fluoroscopy. In this review, we summarize the use of contrast-enhanced ultrasound and elastography in the evaluation of hepatic, renal, pancreatic, splenic, urinary tract, and scrotal pathologies in children. We describe the technical aspects, applications, and limitations, intending to make readers more acquainted with the technologies. Full article

Endometriosis is a clinical entity affecting up to 10% of women of reproductive age, characterized by ectopic endometrial tissue outside the uterine cavity. While extrapelvic endometriosis has been documented, pancreatic endometriosis remains extremely rare and poses significant diagnostic challenges due to its similarity to other pancreatic diseases. At the same time, splenic mesothelial cysts are also rare and typically benign. This report presents a unique case of pancreatic endometriosis coexisting with a splenic mesothelial cyst in a 31-year-old woman. The patient presented to the emergency department with complaints of persistent epigastric and low back pain. She noted having similar symptoms approximately a year prior. Her past medical history was otherwise unremarkable, and there was no known family history of pancreatic disease or neoplasms. Initial imaging revealed a 3.8 cm cystic lesion in the pancreatic tail, with features suggestive of mucinous cystadenoma. Following clinical evaluation and confirmation of the cyst’s nature through endoscopic ultrasound-guided biopsy, the patient subsequently underwent laparoscopic distal pancreatectomy and splenectomy due to worsening symptoms. Gross examination revealed a multilocular pancreatic cyst with a smooth, hemorrhagic wall. Microscopic analysis showed the cyst to be lined by cuboidal to columnar epithelium, consistent with pancreatic endometriosis, confirmed by immunohistochemical staining. The spleen showed cystic formations, diagnosed as a multifaceted mesothelial cyst. In conclusion, this report is the first to document the coexistence of pancreatic endometriosis and splenic mesothelial cysts, highlighting the importance of accurate imaging and pathologic evaluation in the diagnosis of these rare conditions. Early diagnosis and surgical intervention lead to favorable outcomes, reinforcing the importance of comprehensive diagnostic strategies. Full article