Textural features of F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection.
Background: The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although F-fluorodeoxyglucose (F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of t...
| Published in: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 44; no. 5; pp. 886 - 895 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
May2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122047520&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122047520 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: May2017 vid: 44 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 122047520 144079686 10.1007/s00259-016-3599-7 122047520 ppf: 886 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Textural features of F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection. aug: au: Saleem, Ben Beukinga, Roelof Boellaard, Ronald Glaudemans, Andor Reijnen, Michel Zeebregts, Clark Slart, Riemer affil: Department of Surgery, Division of Vascular Surgery , University of Groningen, University Medical Center Groningen , 9700 RB Groningen The Netherlands sug: ab: Background: The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although F-fluorodeoxyglucose (F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Methods: Thirty patients with a history of aortic graft reconstruction who underwent F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different F-FDG PET based textural features were applied to characterize F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. Results: The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive. SUVmax was found predictive in distinguishing these groups, but showed an unsatisfactory accuracy (AUC = 0.75). Conclusion: Textural analysis to characterize F-FDG uptake heterogeneity is feasible and shows promising results in diagnosing AGI, but requires additional external validation and refinement before it can be implemented in the clinical decision-making process. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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