Imaging of Pancreatic Ductal Adenocarcinoma: An Update on Recent Advances

Abstract

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.

Interobserver Variability and Accuracy of Preoperative CT and MRI in Pancreatic Ductal Adenocarcinoma Size Estimation: A Retrospective Cohort Study

“…Finally, our study was restricted to the analysis of PDAC size and CT and MRI were not compared for other information such as the assessment of extrapancreatic disease. 20,21 In conclusion, and in line with previous studies, we found that MRI provides significant underestimation of PDAC size. Our study reveals that PDAC dimension should be preferably estimated using CT images obtained during the PP of enhancement due to high degrees of interobserver agreement and also because size estimates are close to actual tumour size as obtained from fresh gross pathologic specimens.…”

“…Finally, our study was restricted to the analysis of PDAC size and CT and MRI were not compared for other information such as the assessment of extrapancreatic disease. 20,21…”

Exploring the Potentials of Large Language Models in Vascular and Interventional Radiology: Opportunities and Challenges

“…Other authors have reported similar results after investigating ChatGPT's performance on VIR knowledge. 34 35 McCarthy et al 35 evaluated the LLM's efficacy in delivering educational content on VIR, comparing it to standard material from the Society of Interventional Radiology Patient Care Web site. Despite occasional inaccuracies and a tendency to produce lengthy and somewhat complex responses, ChatGPT was generally deemed a reliable source for most VIR procedures.…”

Imaging of Gastrointestinal Stromal Tumours: The Next Wave of Radiology

“…At first glance, the article by Barat et al might appear to be a classic review on the use of CT and MRI imaging for the evaluation of gastrointestinal stromal tumours (GISTs). 1 We might expect the article to review the CT and MRI appearances of these unique tumours focusing on tumour size, location, and imaging characteristics. These findings would typically include enhancement patterns, the presence of calcification, as well as luminal location, and would be discussed as a way of distinguishing these tumours from other tumours including lymphoma, adenocarcinoma, and metastases.…”

“…Barat et al also focus on data acquisition and how dualenergy CT may play a role in monitoring response to therapy and determining when response to therapy is not successful before traditional modes of monitoring. 1 Dual-energy CT has improved the capability of material decomposition compared to conventional CT, which can potentially enhance our ability to detect subtle histologic changes during treatment. The authors also highlight the potential of cinematic rendering with texture mapping as a post-processing tool for analysis of GIST tumours.…”