title: Measurement of canine pancreatic perfusion using dynamic computed tomography: influence of input-output vessels on deconvolution and maximum slope methods.
abstract: OBJECTIVE
  We 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.
  
  
  METHODS
  We 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.
  
  
  RESULTS
  The 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.
  
  
  CONCLUSIONS
  Selection 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.
authors.affiliation: Department of Clinical Veterinary Science, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan. miori@mx6.et.tiki.ne.jp
authors.forename: Miori
authors.initials: M
authors.lastname: Kishimoto
authors.forename: Yoshihisa
authors.initials: Y
authors.lastname: Tsuji
authors.forename: Nana
authors.initials: N
authors.lastname: Katabami
authors.forename: Junichiro
authors.initials: J
authors.lastname: Shimizu
authors.forename: Ki-Ja
authors.initials: KJ
authors.lastname: Lee
authors.forename: Toshiroh
authors.initials: T
authors.lastname: Iwasaki
authors.forename: Yoh-Ichi
authors.initials: Y
authors.lastname: Miyake
authors.forename: Shujiro
authors.initials: S
authors.lastname: Yazumi
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Chiba
authors.forename: Kazutaka
authors.initials: K
authors.lastname: Yamada
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D000818:Animals; D001783:Blood Flow Velocity; D004285:Dogs; D010179:Pancreas / Q000098:blood supply* / Q000000981:diagnostic imaging / Q000502:physiology*; D055420:Perfusion Imaging / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012039:Regional Blood Flow / Q000502:physiology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*