Role of artificial intelligence and novel visualization techniques in the early diagnosis of pancreatic cancer: a review

Abstract

Pancreatic ductal adenocarcinoma is the most common pancreatic cancer. It is characterized by a progressive course or distant metastases in 80%–85% of cases. Despite advances in understanding of pancreatic ductal adenocarcinoma, the disease is consistently linked to poor prognosis due to late diagnosis and limited treatment options in advanced stages. Recently, image processing using artificial intelligence has been introduced for pancreatic ductal adenocarcinoma diagnosis and demonstrated promising results. This review summarizes current scientific data, evaluates the role of artificial intelligence in imaging and early detection of pancreatic ductal adenocarcinoma, and identifies issues that warrant further investigation. The search for publications was conducted using PubMed, Google Scholar, and eLibrary. The following Russian and English search keywords were used: ранняя диагностика рака поджелудочной железы (early diagnosis of pancreatic cancer), искусственный интеллект (artificial intelligence), протоковая аденокарцинома поджелудочной железы (pancreatic ductal adenocarcinoma), медицинская визуализация (medical visualization), наночастицы (nanoparticles), pancreatic cancer, artificial intelligence, early diagnosis pancreatic ductal adenocarcinoma, and pancreatic cancer imaging. Significant progress in early detection of pancreatic ductal adenocarcinoma using artificial intelligence technologies was observed. Current approaches include pre-imaging risk stratification and increased data volume by analyzing electronic medical records. Despite substantial achievements, the clinical implementation of artificial intelligence technologies remains challenging. The use of artificial intelligence along with biomarkers is a promising direction and may enhance theranostics of various malignancies, including pancreatic ductal adenocarcinoma.

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