Evaluation of computed tomography vascular reconstruction for the localization diagnosis of perigastric mass

The aim of this study was to evaluate the utility of computed tomography (CT) vascular reconstruction in the localization diagnosis of perigastric mass.

Fifty-eight patients with pathologically detected perigastric mass underwent abdominal dynamic contrast-enhanced CT. CT vascular reconstructions were produced from arterial phase data using volume rendering (VR), multiplanar reconstruction (MPR), and maximal intensity projection (MIP). Image analysis was focused on the relationship between the mass, perigastric arteries, and the gastric wall. Localization diagnosis values were compared between CT vascular reconstruction and dynamic-enhanced CT images.

Among the 58 cases of perigastric mass, 41 cases originated from the stomach, 7 cases from the left liver lobe, 6 from the pancreas, 2 from lessor omental bursa, 1 from transverse mesocolon, and 1 from left adrenal gland. The accuracy of CT vascular reconstruction images in the localization diagnosis of perigastric mass was higher than that of dynamic-enhanced CT images (98.3% and 86.2%, respectively, P = .04). On the reference level, 35 (35/41) patients with stomach-originated masses showed the mass adjacent perigastric arteries pushed away from the stomach (arterial displacement sign), and 15 (15/17) patients with nonstomach-originated masses showed perigastric arteries between the mass and the stomach (arterial entrapment sign). The sensitivity, specificity, positive predictive value, and negative predictive value of the localization diagnosis of perigastric mass with arterial displacement sign were 85.4%, 100%, 100%, and 73.9%, respectively, and with arterial entrapment sign, 88.2%, 100%, 100%, and 95.3%, respectively.

CT vascular reconstruction can clearly depict the relationship between perigastric mass and adjacent perigastric arteries, which may help us more accurately differentiate between stomach-originated and nonstomach-originated masses compared with original dynamic-enhanced CT images.