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. 2008 Sep-Oct;32(5):757-63.
doi: 10.1097/RCT.0b013e318157b100.

Pancreatic cystic lesions: discrimination accuracy based on clinical data and high-resolution computed tomographic features

Vinika V Chaudhari  1 , Steven S Raman, Ng L Vuong, Peter Zimmerman, James Farrell, Howard Reber, James Sayre, David S K Lu
Affiliations

Pancreatic cystic lesions: discrimination accuracy based on clinical data and high-resolution computed tomographic features

Vinika V Chaudhari et al. J Comput Assist Tomogr. 2008 Sep-Oct.

Abstract

Objective: To determine the frequency of typical features of pancreatic cystic lesions on high-resolution computed tomography and the combination of features that best influences discrimination.

Methods: Ten computed tomography features of 100 proven pancreatic cystic lesions were retrospectively tabulated by 2 blinded imagers. After final diagnosis was revealed, each lesion was categorized as typical or atypical. Stepwise multivariable logistic regression was used to determine which of 10 imaging and 4 clinical features significantly distinguished between benign and malignant lesions.

Results: There were 38 benign cysts and 62 cystic tumors. Serous lesions presented with greater than 6 cysts (83%) and cysts of less than 2 cm (44%). Mucinous lesions presented with cysts of 2 cm or greater (82%) and less than 6 cysts (64%). Pseudocysts, serous, and mucinous lesions presented typically in 77%, 67%, and 64% of cases, respectively. The significant variables in classifying malignant lesions are pancreatitis history, cyst size, symptoms, and calcification pattern (area under the curve, 0.837).

Conclusions: Four specific imaging and clinical features in combination best predict a malignant lesion.

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