Ultrasonography based imaging criterion to ascertain pancreatic enlargement in pediatric acute pancreatitis

Dhanraj S Raut, Shubhangi A Desai, Dhananjay V Raje, Dinesh Singh, Vithalrao P Dandge

Abstract


Introduction: Imaging studies have shown enlargement of pancreatic parts in children diagnosed with acute pancreatitis. The purpose here is to develop imaging based diagnostic evaluation criterion for acute pancreatitis in children.
Materials and Methods: This study included 62 children of acute pancreatitis in the age range of 0.33 to 13 years, as reported in a single hospital center (1994-2019). A study was planned including 1116 normal healthy children in the age range of 0.16 to 18 years for pancreatic evaluation during 2016-17.
Ultrasonography based measurement of three pancreatic parts were obtained for each individual in disease and normal groups. Age-adjusted receiver operating characteristics curve analysis was performed on each pancreatic part independently to derive respective cut-offs using a training set. These cut-offs were further referred to dichotomize the measurement data for each individual and was subjected to multiple logistic regression with presence/absence of acute pancreatitis as dependent variable. A probability score and accordingly the cut-off were obtained indicating a collective impression of enlargement of pancreas in disease condition independently for males and females.
Result: On test data, the accuracy of age-adjusted cut-offs for three parts was near 80% for males, while it ranged between 81-85% for females. ROC analysis of probability score resulted into threshold value of 0.024 for males and 0.044 for females, with sensitivity of 94.11% and 90.91% respectively. The classification accuracy of score derived for males and females was nearly same (83%).
Conclusion: The extent of enlargement of pancreas in acute pancreatitis in children can be determined using the MLR method along with hypoechogenicity.

Keywords: Amylase, Computed Tomography, Gastroenterology, Lipase, Multiple logistic regression, Radiology and Receiver operating, characteristics curve.


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