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


Journal

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
ISSN: 1000-503X
Titre abrégé: Zhongguo Yi Xue Ke Xue Yuan Xue Bao
Pays: China
ID NLM: 8006230

Informations de publication

Date de publication:
28 Feb 2021
Historique:
entrez: 5 3 2021
pubmed: 6 3 2021
medline: 28 4 2021
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 33663662
doi: 10.3881/j.issn.1000-503X.12280
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article

Langues

chi

Sous-ensembles de citation

IM

Pagination

47-52

Auteurs

Juan Li (J)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Xin Yue Chen (XY)

CT Collaboration,Siemens Healthineers,Chengdu 610041,China.

Kai Xu (K)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Ming He (M)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Ting Sun (T)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Liang Zhu (L)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Hua Dan Xue (HD)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

Zheng Yu Jin (ZY)

Department of Radiology,PUMC Hospital,CAMS and PUMC,Beijing 100730,China.

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