کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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4227372 | 1609807 | 2011 | 7 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Measurement of canine pancreatic perfusion using dynamic computed tomography: Influence of input–output vessels on deconvolution and maximum slope methods Measurement of canine pancreatic perfusion using dynamic computed tomography: Influence of input–output vessels on deconvolution and maximum slope methods](/preview/png/4227372.png)
ObjectiveWe investigated whether the prerequisite of the maximum slope and deconvolution methods are satisfied in pancreatic perfusion CT and whether the measured parameters between these algorithms are correlated.MethodsWe examined nine beagles injected with iohexol (200 mgI kg−1) at 5.0 ml s−1. The abdominal aorta and splenic and celiac arteries were selected as the input arteries and the splenic vein, the output veins. For the maximum slope method, we determined the arterial contrast volume of each artery by measuring the area under the curve (AUC) and compared the peak enhancement time in the pancreas with the contrast appearance time in the splenic vein. For the deconvolution method, the artery-to-vein collection rate of contrast medium was calculated. We calculated the pancreatic tissue blood flow (TBF), tissue blood volume (TBV), and mean transit time (MTT) using both algorithms and investigated their correlation based on vessel selection.ResultsThe artery AUC significantly decreased as it neared the pancreas (P < 0.01). In all cases, the peak time of the pancreas (11.5 ± 1.6) was shorter than the appearance time (14.1 ± 1.6) in the splenic vein. The splenic artery–vein combination exhibited the highest collection rate (91.1%) and was the only combination that was significantly correlated between TBF, TBV, and MTT in both algorithms.ConclusionSelection of a vessel nearest to the pancreas is considered as a more appropriate prerequisite. Therefore, vessel selection is important in comparison of the semi-quantitative parameters obtained by different algorithms.
Journal: European Journal of Radiology - Volume 77, Issue 1, January 2011, Pages 175–181