Unraveling Pancreatic Segmentation.

World J Surg

Department of General, Digestive and Endocrine Surgery, Robert-Debré University Hospital, University of Reims Champagne-Ardenne, Reims, France.

Published: April 2018

Background: Limited pancreatic resections are increasingly performed, but the rate of postoperative fistula is higher than after classical resections. Pancreatic segmentation, anatomically and radiologically identifiable, may theoretically help the surgeon removing selected anatomical portions with their own segmental pancreatic duct and thus might decrease the postoperative fistula rate. We aimed at systematically and comprehensively reviewing the previously proposed pancreatic segmentations and discuss their relevance and limitations.

Methods: PubMed database was searched for articles investigating pancreatic segmentation, including human or animal anatomy, and cadaveric or surgical studies.

Results: Overall, 47/99 articles were selected and grouped into 4 main hypotheses of pancreatic segmentation methodology: anatomic, vascular, embryologic and lymphatic. The head, body and tail segments are gross description without distinct borders. The arterial territories defined vascular segments and isolate an isthmic paucivascular area. The embryological theory relied on the fusion plans of the embryological buds. The lymphatic drainage pathways defined the lymphatic segmentation. These theories had differences, but converged toward separating the head and body/tail parts, and the anterior from posterior and inferior parts of the pancreatic head. The rate of postoperative fistula was not decreased when surgical resection was performed following any of these segmentation theories; hence, none of them appeared relevant enough to guide pancreatic transections.

Conclusion: Current pancreatic segmentation theories do not enable defining anatomical-surgical pancreatic segments. Other approaches should be explored, in particular focusing on pancreatic ducts, through pancreatic ducts reconstructions and embryologic 3D modelization.

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Source
http://dx.doi.org/10.1007/s00268-017-4263-5DOI Listing

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