[Averaging Strategy to Form the Imaging for Routine Reading of Insulinoma from Pancreatic Perfusion Dataset]

Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2021 Feb 28;43(1):47-52. doi: 10.3881/j.issn.1000-503X.12280.
[Article in Chinese]

Abstract

Objective To determine the appropriate averaging strategy for pancreatic perfusion datasets to create images for routine reading of insulinoma.Methods Thirty-nine patients undergoing pancreatic perfusion CT in Peking Union Medical College Hospital and diagnosed as insulinoma by pathology were enrolled in this retrospective study.The time-density curve of abdominal aorta calculated by software dynamic angio was used to decide the timings for averaging.Five strategies,by averaging 3,5,7,9 and 11 dynamic scans in perfusion,all including peak enhancement of the abdominal aorta,were investigated in the study.The image noise,pancreas signal-to-noise ratio(SNR),lesion contrast and lesion contrast-to-noise ratio(CNR)were recorded and compared.Besides,overall image quality and insulinoma depiction were also compared.ANOVA and Friedman's test were performed.Results The image noise decreased and the SNR of pancreas increased with the increase in averaging time points(all P<0.001).The lesion contrast(69.81±41.35)averaged from 5 scans showed no significant difference compared with that(72.77±45.25)averaged from 3 scans(P=0.103),both of which were higher than that in other groups(all P≤0.001).The lesion CNRs of the last four groups showed no significant difference(all P>0.99)and were higher than that of the first group(all P<0.05).There was no significant difference in overall image quality among the 5 groups(P=0.977).Conclusions Image averaged from 5 scans showed moderate image noise,pancreas SNR and relatively high lesion contrast and lesion CNR.Therefore,it is advised to be used in image averaging to detect insulinoma.

Keywords: CT; insulinoma; pancreas; perfusion.

MeSH terms

  • Contrast Media
  • Humans
  • Insulinoma* / diagnostic imaging
  • Pancreas / diagnostic imaging
  • Pancreatic Neoplasms* / diagnostic imaging
  • Perfusion
  • Radiographic Image Interpretation, Computer-Assisted
  • Reading
  • Retrospective Studies
  • Signal-To-Noise Ratio

Substances

  • Contrast Media