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.
Original language | English (US) |
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Article number | 4268 |
Journal | Cancers |
Volume | 16 |
Issue number | 24 |
DOIs | |
State | Published - Dec 2024 |
Funding
This research was funded by NIH NCI R01 CA246704. Dr. Tiwari acknowledges the following grants for her efforts: R01CA264017, R01CA277728, VA Merit 1 I01 BX005842-01A2, ICTR Advancing Translational Research & Science (ATRS) Pilot (UL1TR002373), P30CA014520, Wisconsin Alumni Research Foundation Accelerator Oncology Diagnostics Grant (MSN281757), and UW-Madison Radiology R&D Award.
Keywords
- AI for pancreatic diseases
- IPMN
- pancreas imaging
- pancreatic cancer
- pancreatic cystic lesions
- precancerous cysts
ASJC Scopus subject areas
- Oncology
- Cancer Research