Pancreatic ductal adenocarcinoma (PDAC) stands out as the predominant malignant neoplasm affecting the pancreas, characterized by a poor prognosis, in most cases patients being diagnosed in a nonresectable stage. Image-based artificial intelligence (AI) models implemented in tumor detection, segmentation, and classification could improve diagnosis with better treatment options and increased survival. This review included papers published in the last five years and describes the current trends in AI algorithms used in PDAC. We analyzed the applications of AI in the detection of PDAC, segmentation of the lesion, and classification algorithms used in differential diagnosis, prognosis, and histopathological and genomic prediction. The results show a lack of multi-institutional collaboration and stresses the need for bigger datasets in order for AI models to be implemented in a clinically relevant manner.

The liver is a frequent focus in radiology due to its diverse pathology, and artificial intelligence (AI) could improve diagnosis and management. This systematic review aimed to assess and categorize research studies on AI applications in liver radiology from 2018 to 2024, classifying them according to areas of interest (AOIs), AI task and imaging modality used. We excluded reviews and non-liver and non-radiology studies. Using the PRISMA guidelines, we identified 6680 articles from the PubMed/Medline, Scopus and Web of Science databases; 1232 were found to be eligible. A further analysis of a subgroup of 329 studies focused on detection and/or segmentation tasks was performed. Liver lesions were the main AOI and CT was the most popular modality, while classification was the predominant AI task. Most detection and/or segmentation studies (48.02%) used only public datasets, and 27.65% used only one public dataset. Code sharing was practiced by 10.94% of these articles. This review highlights the predominance of classification tasks, especially applied to liver lesion imaging, most often using CT imaging. Detection and/or segmentation tasks relied mostly on public datasets, while external testing and code sharing were lacking. Future research should explore multi-task models and improve dataset availability to enhance AI’s clinical impact in liver imaging.

Somatostatinomas are rare neuroendocrine tumors (NET) that arise in the gastrointestinal (GI) tract. Because of their insidious growth, they are usually asymptomatic until late stages, presenting as malignant disease. We report the case of a 50-year-old woman who presented with epigastric abdominal pain, diarrhea and significant weight loss in the last two years. On clinical examination the patient met the criteria for neurofibromatosis type 1 (NF1). Abdominal CT and MRI revealed an infiltrative duodenal mass, with pancreatic invasion, locoregional enlarged lymph nodes and disseminated hepatic nodules. Microscopy and immunohistochemistry uncovered a neuroendocrine tumor, staining positive for chromogranin A (CgA), synaptophysin and somatostatin, with a Ki67 = 1%. Somatostatin receptors (SSTRs) type 2 were negative and SSTRs type 5 were positive in less than 50% of tumoral cells. Our patient was classified as a T3N1M1 stage IV metastatic duodenal grade 1 somatostatinoma and treatment with somatostatin analogues and chemotherapy with capecitabine and temozolomide was started, with so far abdominal imaging follow-up showing stable disease. When a patient is diagnosed with a rare NET, such as a somatostatinoma, it is of utmost importance to determine if it is a sporadic tumor or just a feature of a genetic disorder.

Background and Aims: The evidence regarding the use of anticoagulant (AC) agents in portal vein thrombosis (PVT) is increasing and, most patients undergo chronic treatment with low molecular weight heparin (LMWH) or vitamin K antagonists (VKA). Nevertheless, there are no clear data about who should receive antithrombotic therapy, when to initiate it, how long and what dose should be used for this set of patients. The aim of the study was to assess the outcome of patients with cirrhosis and portal vein thrombosis who received AC therapy, in terms of thrombus regression, bleeding events and survival rates. Methods: This observational and retrospective study included 107 cirrhotic patients diagnosed with PVT in a single tertiary center between 2010-2019. 54 received low molecular weight heparin or vitamin K antagonist (AC treatment group) and 53 were untreated. All patients were periodically follow-up to assess the evolution of PVT (regression, progression, stable thrombus) and potential occurrence of bleeding events. Results: The regression of portal vein thrombosis was significantly higher in the AC treatment group (OR=2.430; 95% CI=1.11-6.167; p=0.026), more than 50% of on-treatment patients experiencing regression of the thrombus. However, bleeding events were significantly more frequent in the AC treatment group (18.5% vs. 7.5%) and the risk of bleeding was associated with thrombocytes less than 50x103/mm3 (OR=8.266; 95%CI: 2.310-39.211; p=0.002). Survival was better in the AC treatment group (68.4% vs 48.7% at 5 years and 92.7% vs 77.8% at 1 year, p=0.038) and was lower in patients that experienced bleeding events (37.22% survival at 5 years, mean time survival 44 months, p=0.008). Conclusions: In our cohort of cirrhotic patients with PVT more than 50% of patients receiving AC therapy presented regression of the thrombus; most of them obtained partial recanalization. The bleeding complication rate was higher than expected, reaching 18%. The overall mortality was lower in the treated group.

Background and Objectives: Although many of the neuroendocrine neoplasms (NEN) have a typically prolonged natural history compared with other gastrointestinal tract cancers, at least 40% of patients develop liver metastases. This study aims to identify whether liver resection improves the overall survival of patients with liver metastases from NEN. Materials and Methods: We conducted a retrospective study at “Fundeni” Clinical Institute over a time period of 15 years; we thereby identified a series of 93 patients treated for NEN with liver metastases, which we further divided into 2 groups as follows: A (45 patients) had been subjected to liver resection complemented by systemic therapies, and B (48 patients) underwent systemic therapy alone. To reduce the patient selection bias we performed at first a propensity score matching. This was followed by a bootstrapping selection with Jackknife error correction, with the purpose of getting a statistically illustrative sample. Results: The overall survival of the matched virtual cohort under study was 41 months (95% CI 37–45). Group A virtual matched patients showed a higher survival rate (52 mo., 95% CI: 45–59) than B (31 mo., 95% CI: 27–35), (p < 0.001, Log-Rank test). Upon multivariate analysis, seven independent factors were identified to have an influence on survival: location (midgut) and primary tumor grading (G3), absence of concomitant LM, number (2–4), location (unilobar), grading (G3) of LM, and 25–50% hepatic involvement at the time of the metastatic disease diagnosis. Conclusions: Hepatic resection is nowadays the main treatment providing potential cure and prolonged survival, for patients with NEN when integrated in a multimodal strategy based on systemic therapy.