| Title |
Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation
|
|---|---|
| Published in |
Molecular Imaging and Biology, February 2016
|
| DOI | 10.1007/s11307-016-0940-2 |
| Pubmed ID | |
| Authors |
Floris H. P. van Velden, Gerbrand M. Kramer, Virginie Frings, Ida A. Nissen, Emma R. Mulder, Adrianus J. de Langen, Otto S. Hoekstra, Egbert F. Smit, Ronald Boellaard |
| Abstract |
To assess (1) the repeatability and (2) the impact of reconstruction methods and delineation on the repeatability of 105 radiomic features in non-small-cell lung cancer (NSCLC) 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) positron emission tomorgraphy/computed tomography (PET/CT) studies. Eleven NSCLC patients received two baseline whole-body PET/CT scans. Each scan was reconstructed twice, once using the point spread function (PSF) and once complying with the European Association for Nuclear Medicine (EANM) guidelines for tumor PET imaging. Volumes of interest (n = 19) were delineated twice, once on PET and once on CT images. Sixty-three features showed an intraclass correlation coefficient ≥ 0.90 independent of delineation or reconstruction. More features were sensitive to a change in delineation than to a change in reconstruction (25 and 3 features, respectively). The majority of features in NSCLC [(18)F]FDG-PET/CT studies show a high level of repeatability that is similar or better compared to simple standardized uptake value measures. |
X Demographics
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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 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 1% |
| China | 2 | 1% |
| Korea, Republic of | 1 | <1% |
| France | 1 | <1% |
| Unknown | 194 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 51 | 26% |
| Researcher | 31 | 16% |
| Student > Master | 26 | 13% |
| Other | 13 | 7% |
| Student > Postgraduate | 11 | 6% |
| Other | 34 | 17% |
| Unknown | 34 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 70 | 35% |
| Physics and Astronomy | 26 | 13% |
| Engineering | 25 | 13% |
| Computer Science | 13 | 7% |
| Nursing and Health Professions | 6 | 3% |
| Other | 21 | 11% |
| Unknown | 39 | 20% |
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 28 September 2017.
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#20,657,128
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Outputs from Molecular Imaging and Biology
#621
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Outputs of similar age
#230,866
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Outputs of similar age from Molecular Imaging and Biology
#8
of 11 outputs
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