ArticleInsights into imaging2024
Assessment of vascular invasion of pancreatic ductal adenocarcinoma based on CE-boost black blood CT technique.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Enhancing vascular wall assessment in computed tomography: image quality optimization via small-field-of-view vascular wall spectral images.Quantitative imaging in medicine and surgery · 2026Article
- Black-blood computed tomography with contrast-enhancement boost for optimized portal vein imaging and segmentation: a feasibility study.Quantitative imaging in medicine and surgery · 2026Article
- Diagnosis and Surgical Management for Advanced Pancreatic Cancer Requiring Vascular Resection.Diagnostics (Basel, Switzerland) · 2025Review
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8 authors.
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Abstract
objectivesTo 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).
methodsA 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).
resultsThe AiCE and AiCE-BBCT groups demonstrated superior image noise and diagnostic acceptability compared with AIDR 3D and AIDR 3D-BBCT groups (all p < 0.001), and the k value was 0.861-0.967 for both reviewers. In terms of diagnostic capability for vascular invasion in PDAC, the AiCE-BBCT group exhibited higher specificity (95.0%) and sensitivity (93.3%) compared to the AIDR 3D and AIDR 3D-BBCT groups, with an AUC of 0.942 (95% CI: 0.849-1.000, p < 0.05). Furthermore, all vascular evaluations conducted using AiCE-BBCT demonstrated better consistency (ICC: 0.847-0.935).
conclusionThe BBCT technique in conjunction with AiCE could lead to notable enhancements in both the image quality of PDAC images and the diagnostic performance for tumor vascular invasion. CRITICAL RELEVANCE STATEMENT: Better diagnostic accuracy of vascular invasion of PDAC based on BBCT in combination with an AiCE is a critical factor in determining treatment strategies and patient outcomes. KEY POINTS: Identifying vascular invasion of PDAC is important for prognostication. Combined images provide improved image quality and higher diagnostic accuracy. Combined images can excellently display the vascular wall and invasion.
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