Clinical Research Directory

Preventing Postoperative Complications in Patients Undergoing High-risk Pancreatoduodenectomy With a Bundle Approach Including Hydrocortisone, Octreotide, and the Teres Ligament Patch (PANENCA)

The PANENCA trial aims to reduce postoperative complications in patients undergoing pancreatoduodenectomy (also known as a Whipple procedure), a complex surgical operation performed to remove tumors located in or near the head of the pancreas. One of the most frequent and serious complications after this surgery is postoperative pancreatic fistula (POPF), a leakage of pancreatic fluid from the surgical connection. POPF can lead to intra-abdominal infection, bleeding, and inflammation, often resulting in delayed recovery and postponement of subsequent oncological treatment. In severe cases, these complications may be life-threatening. Patients with a small main pancreatic duct (3 millimeters or less) are known to have a substantially higher risk of developing POPF. Previous studies have shown that several existing interventions may reduce the risk or severity of these complications. These include hydrocortisone, a medication that suppresses postoperative inflammation; octreotide, a medication that reduces the production of pancreatic secretions; and a surgical technique known as the ligamentum teres hepatis patch, which uses the patient's own tissue to protect nearby blood vessels in the event of a pancreatic leak. Because the development of pancreatic fistulas is multifactorial, the investigators hypothesize that a combined approach targeting different underlying mechanisms may provide a complementary and more effective protective effect than any single intervention alone. The PANENCA trial therefore evaluates whether the combined use of hydrocortisone, octreotide, and the ligamentum teres patch can reduce the rate of major postoperative complications after pancreatoduodenectomy. Patients participating in the study are randomly assigned to receive either the combination treatment in addition to standard perioperative care or standard perioperative care alone. The study medications are administered only during the first postoperative days, and the surgical patch is applied during the operation itself. No additional tests, monitoring procedures, or hospital visits are required beyond routine clinical care. This international, multicenter randomized trial includes patients at high risk for POPF who are undergoing pancreatoduodenectomy. The primary objective is to determine whether the combination treatment reduces the incidence of major postoperative complications. If proven effective, this bundle approach may be implemented more consistently across participating countries and incorporated into international clinical guidelines for pancreatic surgery.

Artificial Intelligence-powered Low-Dose Computed Tomography for Screening of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with early diagnosis crucial for improving survival. Due to the absence of effective screening methods, most patients are diagnosed at advanced stages. The population undergoing low-dose computed tomography (LDCT) screening significantly overlaps with those at high risk for PDAC; however, traditional imaging methods have limited sensitivity for detecting pancreatic lesions. This study utilizes the Pancreatic Cancer Detection with Artificial Intelligence (PANDA) system to enhance LDCT for pancreatic cancer screening in a prospective, multicenter, observational cohort. PANDA will analyze LDCT images, followed by a multidisciplinary team (MDT) reassessment of abnormal interpretations. Based on MDT evaluation, individuals will be recalled for further examination, placed under a personalized follow-up plan, or monitored for at least one year. The primary outcomes include pancreatic cancer detection rate, positive predictive value, consensus rate, and recall rate, while secondary outcomes focus on early-stage cancers, resectable tumors, and safety indicators such as false positive rates and unnecessary procedures. This study aims to assess the effectiveness and safety of AI-assisted LDCT for PDAC detection, providing a practical solution for improving public health and enhancing early diagnostic capabilities.

AI-powered Early Detection for Pancreatic Cancer Via Non-contrast CT in Opportunistic Screening Cohort

Pancreatic ductal adenocarcinoma (PDAC) remains a therapeutic challenge with 5-year survival rates of 13%, primarily attributable to advanced-stage diagnosis (AJCC Stage III/IV in \>80% of cases). This prospective, observational, multi-center study will evaluate the performance of an AI-powered opportunistic screening system utilizing non-contrast computed tomography (NCCT) acquired during routine clinical encounters or health check-ups. The proposed AI model will perform automated detection of pancreatic parenchymal abnormalities, including PDAC and precursor lesions (intraductal papillary mucinous neoplasms \[IPMN\], mucinous cystic neoplasms \[MCN\]). Algorithm-positive cases will be independently reviewed by two radiologists. Highly suspected individuals will undergo further diagnostic verification, including serological tests and multimodal imaging confirmation. Patients with confirmed positive diagnosis will receive multidisciplinary consultation and specialized treatment, whereas those with negative results will undergo at least one-year clinical follow-up. This study will quantitatively evaluate the AI system's performance, and aims to advance PDAC early detection, improve patient outcomes, and make it accessible in underserved populations.