Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris543341, Paris, France.
Université Paris Cité, Faculté de Médecine, 555089Paris, France.
Can Assoc Radiol J. 2023 May;74(2):351-361. doi: 10.1177/08465371221124927. Epub 2022 Sep 5.
Pancreatic ductal carcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Computed tomography (CT) remains the primary imaging modality for diagnosis of PDAC. However, CT has limitations for early pancreatic tumor detection and tumor characterization so that it is currently challenged by magnetic resonance imaging. More recently, a particular attention has been given to radiomics for the characterization of pancreatic lesions using extraction and analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence (AI) with the aim of better characterizing pancreatic lesions and providing a more precise assessment of tumor burden. This review article sums up recent advances in imaging of PDAC in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning. In addition, current applications of radiomics and AI in the field of PDAC are discussed.
胰腺导管腺癌 (PDAC) 是全球癌症相关死亡的主要原因之一。计算机断层扫描 (CT) 仍然是 PDAC 诊断的主要成像方式。然而,CT 在早期胰腺肿瘤检测和肿瘤特征描述方面存在局限性,因此目前受到磁共振成像的挑战。最近,人们特别关注利用提取和分析定量成像特征对胰腺病变进行特征描述的放射组学。此外,放射组学目前有许多与人工智能 (AI) 联合开发的应用,旨在更好地描述胰腺病变并更准确地评估肿瘤负担。本文综述了 PDAC 成像领域在图像/数据采集、肿瘤检测、肿瘤特征描述、治疗反应评估和术前规划方面的最新进展。此外,还讨论了放射组学和 AI 在 PDAC 领域的当前应用。