Assessment of vascular invasion of pancreatic ductal adenocarcinoma based on CE-boost black blood CT technique

Objectives To explore the diagnostic efficacy of advanced intelligent clear-IQ engine (AiCE) and adaptive iterative dose reduction 3D (AIDR 3D), combination with and without the black blood CT technique (BBCT), for detecting vascular invasion in patients diagnosed with nonmetastatic pancreatic ductal adenocarcinoma (PDAC). Methods A total of 35 consecutive patients diagnosed with PDAC, proceeding with contrast-enhanced abdominal CT scans, were enrolled in this study. The arterial and portal venous phase images were reconstructed using AiCE and AIDR 3D. The corresponding BBCT images were established as AiCE–BBCT and AIDR 3D–BBCT, respectively. Two observers scored the image quality independently. Cohen’s kappa (k) value or intraclass correlation coefficient (ICC) was used to analyze consistency. The diagnostic performance of four algorithms in detecting vascular invasion in PDAC patients was assessed using the area under the curve (AUC). Results The AiCE and AiCE–BBCT groups demonstrated superior image noise and diagnostic acceptability compared with AIDR 3D and AIDR 3D–BBCT groups (all p