| Title |
Automatic extraction of forward stroke volume using dynamic PET/CT: a dual-tracer and dual-scanner validation in patients with heart valve disease
|
|---|---|
| Published in |
EJNMMI Physics, October 2015
|
| DOI | 10.1186/s40658-015-0133-0 |
| Pubmed ID | |
| Authors |
Hendrik Johannes Harms, Lars Poulsen Tolbod, Nils Henrik Stubkjær Hansson, Tanja Kero, Lovisa Holm Orndahl, Won Yong Kim, Tomas Bjerner, Kirsten Bouchelouche, Henrik Wiggers, Jørgen Frøkiær, Jens Sörensen |
| Abstract |
The 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. 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 13% |
| Researcher | 3 | 13% |
| Student > Bachelor | 1 | 4% |
| Lecturer | 1 | 4% |
| Professor > Associate Professor | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 14 | 61% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 22% |
| Nursing and Health Professions | 2 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Earth and Planetary Sciences | 1 | 4% |
| Computer Science | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 13 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2015.
All research outputs
#14,240,471
of 22,831,537 outputs
Outputs from EJNMMI Physics
#54
of 181 outputs
Outputs of similar age
#147,460
of 284,375 outputs
Outputs of similar age from EJNMMI Physics
#1
of 4 outputs
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