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

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<0.0001). Lower TPAI (OR 0.34, P=0.009) and HU (OR 0.84, P=0.002) measurements were predictive of discharge to skilled nursing facility (SNF), but not major complications, length of stay, readmissions or recurrence on univariate analysis. Lower TPAI was protective against the risk of organ/space surgical site infection (SSI) including pancreatic fistula (OR 3.12, P=0.019). On multivariate analysis, the semi-automated measurements of TPAI and HU remained as independent predictors of organ/space SSI including pancreatic fistula (OR 4.23, P=0.014) and discharge to SNF (OR 0.79, P=0.019) respectively.

Conclusions: When combined with preoperative clinical assessments in patients with pancreatic malignancy, semi-automated sarcopenia metrics are a simple, reproducible method that may enhance prediction of outcomes after PD and help guide clinical management.