2015
DOI: 10.1186/s40658-015-0133-0
|View full text |Cite
|
Sign up to set email alerts
|

Automatic extraction of forward stroke volume using dynamic PET/CT: a dual-tracer and dual-scanner validation in patients with heart valve disease

Abstract: BackgroundThe aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners.Methods35 subjects underwent a dynamic 11C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic 15O-water PET and 11C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ve… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

2
22
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
5
1

Relationship

3
3

Authors

Journals

citations
Cited by 20 publications
(24 citation statements)
references
References 24 publications
2
22
0
Order By: Relevance
“…Therefore, care has to be taken in interpretation of LVEF and stroke volume values. Indicator-dilution methods can be applied to dynamic PET data for assessing forward stroke volume (15), which may serve as an alternative.…”
Section: Discussionmentioning
confidence: 99%
See 4 more Smart Citations
“…Therefore, care has to be taken in interpretation of LVEF and stroke volume values. Indicator-dilution methods can be applied to dynamic PET data for assessing forward stroke volume (15), which may serve as an alternative.…”
Section: Discussionmentioning
confidence: 99%
“…Arterial (C A (t)), venous (C V (t)), and plasma (C P (t)) input functions were obtained using cluster analysis as described previously (15), applying a previously described metabolite correction (16). Using these input functions, parametric images were calculated using a basis-function approach (12,17) of the single-tissue-compartment model (18):…”
Section: Parametric Imagesmentioning
confidence: 99%
See 3 more Smart Citations