Is FDG-PET texture analysis related to intratumor biological heterogeneity in lung cancer?

Objectives We aimed at investigating the origin of the correlations between tumor volume and F-18-FDG-PET texture indices in lung cancer. Methods Eighty-five consecutive patients with newly diagnosed non-small cell lung cancer (NSCLC) underwent a F-18-FDG-PET/CT scan before treatment. Seven phantom spheres uniformly filled with F-18-FDG, and covering a range of activities and volumes similar to that found in lung tumors, were also scanned. Established texture indices were computed for lung tumors and homogeneous spheres. The dependence between textural indices and volume in homogeneous spheres was modeled and then used to predict texture indices in lung tumors. Correlation analyses were carried out between predicted and texture features measured in lung tumors. Cox proportional hazards regression was used to investigate the associations between overall survival and volume-adjusted textural features. Results All textural features showed strong, non-linear correlations with volume, both in tumors and homogeneous spheres. Correlations between predicted versus measured texture features were very high for contrast (r(2) = 0.91), dissimilarity (r(2) = 0.90), ZP (r(2) = 0.90), GLNN (r(2) = 0.86), and homogeneity (r(2) = 0.82); high for entropy (r(2) = 0.50) and HILAE (r(2) = 0.53); and low for energy (r(2) = 0.30). Cox regressions showed that among volume-adjusted features, only HILAE was associated with overall survival (b = - 0.35, p = 0.008). Conclusion We have shown that texture indices previously found to be correlated with a number of clinically relevant outcomes might not provide independent information apart from that driven by their correlation with tumor volume, suggesting that these metrics might not be suitable as intratumor heterogeneity markers.

Automated summary

The study revealed strong correlations between tumor volume and F-18-FDG-PET texture indices in lung cancer, suggesting that texture indices might not provide independent information apart from being driven by their correlation with tumor volume, and may not be suitable as intratumor heterogeneity markers.