Huang Chenchan, Shen Yiqiu, Galgano Samuel J, Goenka Ajit H, Hecht Elizabeth M, Kambadakone Avinash, Wang Zhen Jane, Chu Linda C
New York University Langone Health, New York, USA.
University of Alabama at Birmingham, Birmingham, USA.
Abdom Radiol (NY). 2025 Apr;50(4):1731-1743. doi: 10.1007/s00261-024-04644-7. Epub 2024 Oct 28.
Early detection is crucial for improving survival rates of pancreatic ductal adenocarcinoma (PDA), yet current diagnostic methods can often fail at this stage. Recently, there has been significant interest in improving risk stratification and developing imaging biomarkers, through novel imaging techniques, and most notably, artificial intelligence (AI) technology. This review provides an overview of these advancements, with a focus on deep learning methods for early detection of PDA.
早期检测对于提高胰腺导管腺癌(PDA)的生存率至关重要,但目前的诊断方法在这一阶段往往会失败。最近,人们对通过新型成像技术,尤其是人工智能(AI)技术来改善风险分层和开发成像生物标志物产生了浓厚兴趣。本文综述了这些进展,重点介绍了用于PDA早期检测的深度学习方法。