Abstract
Background/Purpose: When a pancreatoduodenectomy is to be conducted, preoperative understanding of the vascular anatomy of the pancreatic head is important in order to reduce intraoperative bleeding. Using multislice computed tomography (MS-CT), we investigated the depiction rate and branching of the inferior pancreaticoduodenal artery (IPDA) and dorsal pancreatic artery (DPA), afferent arteries to the pancreatic head. Methods: In 109 patients (68 with pancreatic cancer, 21 with biliary tract cancer, 15 with intraductal papillary mucinous tumor of the pancreas, and 5 others), images were taken, using 64-row MS-CT, in the early and late arterial phases. Results: The depiction rates were 98.2% for the IPDA and 96.3% for the DPA. Branching of the IPDA was categorized into three types: a type in which the IPDA formed a common vessel with the first jejunal branch (72.0%), a type in which the IPDA branched directly from the superior mesenteric artery (18.7%), and a type in which the anterior inferior pancreaticoduodenal artery (AIPDA) and posterior inferior pancreaticoduodenal artery (PIPDA) branched separately (9.3%). DPA branching was categorized into five types, in which the DPA branched from the splenic artery (40.0%), from the common hepatic artery (25.7%), from the superior mesenteric artery (20.0%), and from the celiac artery (8.6%), and a type in which the DPA branching did not follow any of the above patterns (5.7%). Conclusions: MS-CT images of vascular architecture enable evaluation from any angle, which is not possible with conventional angiography, making MS-CT a useful diagnostic imaging technique for understanding the vascular anatomy of the pancreatic head prior to conducting pancreatoduodenectomy for diseases of the pancreatic head region.
| Original language | English |
|---|---|
| Pages (from-to) | 322-326 |
| Number of pages | 5 |
| Journal | Journal of Hepato-Biliary-Pancreatic Surgery |
| Volume | 15 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 05-2008 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Surgery
- Hepatology
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