| Title |
Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745
|
|---|---|
| Published in |
EJNMMI Research, July 2018
|
| DOI | 10.1186/s13550-018-0412-6 |
| Pubmed ID | |
| Authors |
Hasan Sari, Kjell Erlandsson, Lisbeth Marner, Ian Law, Henrik B.W. Larsson, Kris Thielemans, Sébastien Ourselin, Simon Arridge, David Atkinson, Brian F. Hutton |
| Abstract |
Kinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma. In this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (11C-SB207145) and estimated parameter results are compared to results obtained using the original SIME and gold standard AIFs derived from arterial samples. Reproducibility of the method was assessed using test-retest data. It was shown that the incorporation of image-derived information increased the accuracy of total volume of distribution (V T) estimates, averaged across all regions, by 40% and non-displaceable binding potential (BP ND) estimates by 16% compared to the original SIME. Particular improvements were observed in K1 parameter estimates. BP ND estimates, based on the proposed method and the gold standard arterial sample-derived AIF, were not significantly different (P=0.7). The results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 50% |
| Switzerland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 32% |
| Student > Ph. D. Student | 9 | 29% |
| Student > Master | 2 | 6% |
| Lecturer | 1 | 3% |
| Student > Doctoral Student | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 7 | 23% |
| Neuroscience | 5 | 16% |
| Medicine and Dentistry | 4 | 13% |
| Agricultural and Biological Sciences | 2 | 6% |
| Computer Science | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 7 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 10 July 2018.
All research outputs
#7,753,975
of 23,577,654 outputs
Outputs from EJNMMI Research
#155
of 579 outputs
Outputs of similar age
#130,749
of 328,988 outputs
Outputs of similar age from EJNMMI Research
#5
of 22 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 579 research outputs from this source. They receive a mean Attention Score of 2.6. This one has gotten more attention than average, scoring higher than 67% of its peers.
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We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.