Advances for Managing Pancreatic Cystic Lesions: Integrating Imaging and AI Innovations

Seyithanoglu D., Durak G., Keles E., Medetalibeyoglu A., Hong Z., Taktak Y. B., ...More

Cancers, vol.16, no.24, 2024 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Review
  • Volume: 16 Issue: 24
  • Publication Date: 2024
  • Doi Number: 10.3390/cancers16244268
  • Journal Name: Cancers
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, CINAHL, EMBASE, Veterinary Science Database, Directory of Open Access Journals
  • Keywords: AI for pancreatic diseases, IPMN, pancreas imaging, pancreatic cancer, pancreatic cystic lesions, precancerous cysts
  • Istanbul University Affiliated: Yes

Abstract

Pancreatic cystic lesions (PCLs) can range from harmless growths to precursors of pancreatic cancer, making accurate diagnosis crucial for patient care. Traditional methods for managing PCLs, such as imaging and biopsies, often depend on the skill of the doctor interpreting the images, leading to variability in diagnosis and treatment. This review highlights the challenges in diagnosing and managing PCLs and discusses the potential for artificial intelligence (AI) to improve accuracy. AI techniques, such as automated image analysis and deep learning algorithms, can provide more consistent and reliable assessments of pancreatic cysts. These tools could help doctors better identify high-risk lesions that need treatment, while avoiding unnecessary procedures for benign cysts. AI-driven methods show promise in improving patient outcomes, offering earlier detection and more precise management, and ultimately helping to prevent pancreatic cancer.