| Title |
Improved quantitation and reproducibility in multi-PET/CT lung studies by combining CT information
|
|---|---|
| Published in |
EJNMMI Physics, June 2018
|
| DOI | 10.1186/s40658-018-0212-0 |
| Pubmed ID | |
| Authors |
Beverley F. Holman, Vesna Cuplov, Lynn Millner, Raymond Endozo, Toby M. Maher, Ashley M. Groves, Brian F. Hutton, Kris Thielemans |
| Abstract |
Matched attenuation maps are vital for obtaining accurate and reproducible kinetic and static parameter estimates from PET data. With increased interest in PET/CT imaging of diffuse lung diseases for assessing disease progression and treatment effectiveness, understanding the extent of the effect of respiratory motion and establishing methods for correction are becoming more important. In a previous study, we have shown that using the wrong attenuation map leads to large errors due to density mismatches in the lung, especially in dynamic PET scans. Here, we extend this work to the case where the study is sub-divided into several scans, e.g. for patient comfort, each with its own CT (cine-CT and 'snap shot' CT). A method to combine multi-CT information into a combined-CT has then been developed, which averages the CT information from each study section to produce composite CT images with the lung density more representative of that in the PET data. This combined-CT was applied to nine patients with idiopathic pulmonary fibrosis, imaged with dynamic 18F-FDG PET/CT to determine the improvement in the precision of the parameter estimates. Using XCAT simulations, errors in the influx rate constant were found to be as high as 60% in multi-PET/CT studies. Analysis of patient data identified displacements between study sections in the time activity curves, which led to an average standard error in the estimates of the influx rate constant of 53% with conventional methods. This reduced to within 5% after use of combined-CTs for attenuation correction of the study sections. Use of combined-CTs to reconstruct the sections of a multi-PET/CT study, as opposed to using the individually acquired CTs at each study stage, produces more precise parameter estimates and may improve discrimination between diseased and normal lung. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 29% |
| Researcher | 4 | 24% |
| Student > Doctoral Student | 2 | 12% |
| Professor > Associate Professor | 2 | 12% |
| Other | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 3 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 29% |
| Physics and Astronomy | 4 | 24% |
| Psychology | 2 | 12% |
| Computer Science | 2 | 12% |
| Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 3 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 03 July 2018.
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#20,525,274
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Outputs from EJNMMI Physics
#137
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#289,341
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Outputs of similar age from EJNMMI Physics
#4
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