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A semi-automated assessment of sarcopenia using psoas area and density predicts outcomes after pancreaticoduodenectomy for pancreatic malignancy

  
@article{JGO15423,
	author = {Jukes Namm and Kiran Thakrar and Chi Wang and Susan Stocker and Malini Sur and onathan Berlin and William Dale and Mark Talamonti and Kevin Roggin},
	title = {A semi-automated assessment of sarcopenia using psoas area  and density predicts outcomes after pancreaticoduodenectomy  for pancreatic malignancy},
	journal = {Journal of Gastrointestinal Oncology},
	volume = {8},
	number = {6},
	year = {2017},
	keywords = {},
	abstract = {Background: Sarcopenia has been associated with increased adverse outcomes after major abdominal surgery. Sarcopenia defined as decreased muscle volume or increased fatty infiltration may be a proxy for frailty. In conjunction with other preoperative clinical risk factors, radiographic measures of sarcopenia using both muscle size and density may enhance prediction of outcomes after pancreaticoduodenectomy (PD) for malignancy. 
Methods: Preoperative computed tomography (CT) scans of patients undergoing PD for malignancy were analyzed from a prospective pancreatic surgery database. Sarcopenia was assessed both manually and with a semi-automated technique by measuring the total psoas area index (TPAI) and average Hounsfield units (HU) at the L3 lumbar level to estimate psoas muscle volume and density, respectively. Adjusting for known pre-operative risk factors, preoperative sarcopenia measurements were analyzed relative to perioperative outcomes. 
Results: Sarcopenia assessments of 116 subjects demonstrated good correlation between the semi-automated and the manual techniques (P},
	issn = {2219-679X},	url = {https://jgo.amegroups.org/article/view/15423}
}