Journal
JOURNAL OF NUCLEAR MEDICINE
Volume 49, Issue 12, Pages 1973-1979Publisher
SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.108.053397
Keywords
F-18-FDG; PET; sarcoma; image analysis
Funding
- NIH/NCI [R01 CA65537]
- NCRR [S10 RR17229]
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F-18-FDG PET images of tumors often display highly heterogeneous spatial distribution of F-18-FDG-positive pixels. We proposed that this heterogeneity in F-18-FDG spatial distribution can be used to predict tumor biologic aggressiveness. This study presents data to support the hypothesis that a new heterogeney-analysis algorithm applied to F-18-FDG PET images of tumors in patients is predictive of patient outcome. Methods: F-18-FDG PET images from 238 patients with sarcoma were analyzed using a new algorithm for heterogeneity analysis in tumor F-18-FDG spatial distribution. Patient characteristics, tumor histology, and patient outcome were compared with image analysis results using univariate and multivarate analysis. Cox proportional hazards models were used to further analyze the significance of the data associations. Results: Statistical analyses show that heterogeneity analysis is a strong independent predictor of patient outcome. Conclusion: The new F-18-FDG PET tumor image heterogeneity analysis method is validated for the ability to predict patient outcome in a clinical population of patients with sarcoma. This method can be extended to other PET image datasets in which heterogeneity in tissue uptake of a radiotracer may predict patient outcome.
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