| Title |
FDG PET/CT texture analysis for predicting the outcome of lung cancer treated by stereotactic body radiation therapy
|
|---|---|
| Published in |
European Journal of Nuclear Medicine and Molecular Imaging, January 2016
|
| DOI | 10.1007/s00259-016-3314-8 |
| Pubmed ID | |
| Authors |
Pierre Lovinfosse, Zsolt Levente Janvary, Philippe Coucke, Sébastien Jodogne, Claire Bernard, Mathieu Hatt, Dimitris Visvikis, Nicolas Jansen, Bernard Duysinx, Roland Hustinx |
| Abstract |
With (18)F-FDG PET/CT, tumor uptake intensity and heterogeneity have been associated with outcome in several cancers. This study aimed at investigating whether (18)F-FDG uptake intensity, volume or heterogeneity could predict the outcome in patients with non-small cell lung cancers (NSCLC) treated by stereotactic body radiation therapy (SBRT). Sixty-three patients with NSCLC treated by SBRT underwent a (18)F-FDG PET/CT before treatment. Maximum and mean standard uptake value (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), as well as 13 global, local and regional textural features were analysed. The predictive value of these parameters, along with clinical features, was assessed using univariate and multivariate analysis for overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS). Cutoff values were obtained using logistic regression analysis, and survivals were compared using Kaplan-Meier analysis. The median follow-up period was 27.1 months for the entire cohort and 32.1 months for the surviving patients. At the end of the study, 25 patients had local and/or distant recurrence including 12 who died because of the cancer progression. None of the clinical variables was predictive of the outcome, except age, which was associated with DFS (HR 1.1, P = 0.002). None of the (18)F-FDG PET/CT or clinical parameters, except gender, were associated with OS. The univariate analysis showed that only dissimilarity (D) was associated with DSS (HR = 0.822, P = 0.037), and that several metabolic measurements were associated with DFS. In multivariate analysis, only dissimilarity was significantly associated with DSS (HR = 0.822, P = 0.037) and with DFS (HR = 0.834, P < 0.01). The textural feature dissimilarity measured on the baseline (18)F-FDG PET/CT appears to be a strong independent predictor of the outcome in patients with NSCLC treated by SBRT. This may help selecting patients who may benefit from closer monitoring and therapeutic optimization. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| China | 1 | 1% |
| Unknown | 66 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 19% |
| Other | 9 | 13% |
| Student > Ph. D. Student | 8 | 12% |
| Student > Postgraduate | 7 | 10% |
| Student > Doctoral Student | 6 | 9% |
| Other | 17 | 25% |
| Unknown | 8 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 33 | 49% |
| Physics and Astronomy | 7 | 10% |
| Computer Science | 3 | 4% |
| Engineering | 2 | 3% |
| Nursing and Health Professions | 1 | 1% |
| Other | 4 | 6% |
| Unknown | 18 | 26% |
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 February 2016.
All research outputs
#21,153,429
of 23,806,312 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#2,610
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#337,550
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Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#42
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