• D P O'Leary, D O'Neill, P McLaughlin, S O'Neill, E Myers, M M Maher, and H P Redmond.
• Department of Academic Surgery, Cork University Hospital, Wilton, Cork, Ireland. olearypeter83@hotmail.com
• World J Surg. 2012 Jul 1; 36 (7): 1679-85.

BackgroundObesity is a well-established risk factor for acute pancreatitis. Increased visceral fat has been shown to exacerbate the pro-inflammatory milieu experienced by patients. This study aimed to investigate the relationship between the severity of acute pancreatitis and abdominal fat distribution parameters measured on computed tomography (CT) scan.MethodsConsecutive patients admitted to Cork University Hospital with acute pancreatitis between January 2005 and December 2010 were evaluated for inclusion in the study. An open source image analysis software (Osirix, v 3.9) was used to calculate individual abdominal fat distribution parameters from CT scans by segmentation of abdominal tissues.ResultsA total of 214 patients were admitted with pancreatitis between January 2005 and December 2010. Sixty-two of these patients underwent a CT scan and were thus eligible for inclusion. Visceral fat volume was the volumetric fat parameter that had the most significant association with severe acute pancreatitis (P = 0.003). There was a significant association between visceral fat volume and subsequent development of systemic complications of severe acute pancreatitis (P = 0.003). There was a strong association between mortality and visceral fat volume (P = 0.019). Multivariate regression analysis, adjusted for gender, did not identify any individual abdominal fat distribution index as an independent risk factor for severe acute pancreatitis.ConclusionsOverall, estimation of abdominal fat distribution parameters from CT scans performed on patients with acute pancreatitis indicates a strong association between visceral fat, severe acute pancreatitis, and the subsequent development of systemic complications. These data suggest that visceral fat volume should be incorporated into future predictive scoring systems.

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