Abstract
PURPOSE:
Despite the growing use of fluorine-18-fluorodeoxyglucose (F-FDG) PET texture analysis to measure intratumoural heterogeneity in cancer research, the biologic basis of F-FDG PET-derived texture variables is poorly understood. We aimed to assess correlations between F-FDG PET-derived texture variables and whole-slide image (WSI)-derived metrics of tumour cellularity and spatial heterogeneity.
PATIENTS AND METHODS:
Twenty-two patients with non-small-cell lung cancer prospectively underwent F-FDG PET imaging before tumour resection. We tested nine F-FDG PET parameters: metabolically active tumour volume, total lesion glycolysis, mean standardized uptake value (SUVmean), first-order entropy, energy, skewness, kurtosis, grey-level co-occurrence matrix entropy and lacunarity (SUV-lacunarity). From the haematoxylin and eosin-stained WSIs, we derived mean tumour-cell density (MCD) and lacunarity (path-lacunarity). Spearman's correlation analysis and agglomerative hierarchical clustering were performed to assess variable associations.
RESULTS:
Tumour volumes ranged from 2.2 to 74 cm (median: 17.9 cm). MCD correlated positively with total lesion glycolysis (rs: 0.46, P: 0.007) and SUVmean (rs : 0.55; P: 0.008) and negatively with skewness and kurtosis (rs: -0.47 for both; P: 0.028 and 0.026, respectively). SUV-lacunarity and path-lacunarity were positively correlated (rs: 0.5; P: 0.018). On cluster analysis, larger tumours trended towards higher SUVmean and entropy with a predominance of tightly concentrated high SUV-voxels (negative skewness and low kurtosis on the histogram); on WSI analysis such larger tumours also displayed generally higher MCD and low SUV-lacunarity and path-lacunarity.
CONCLUSION:
Our data suggest that histopathological MCD and lacunarity are associated with several commonly used F-FDG PET-derived indices including SUV-lacunarity, metabolically active tumour volume, SUVmean, entropy, skewness, and kurtosis, and thus may explain the biological basis of F-FDG PET-uptake heterogeneity in non-small-cell lung cancer.
Despite the growing use of fluorine-18-fluorodeoxyglucose (F-FDG) PET texture analysis to measure intratumoural heterogeneity in cancer research, the biologic basis of F-FDG PET-derived texture variables is poorly understood. We aimed to assess correlations between F-FDG PET-derived texture variables and whole-slide image (WSI)-derived metrics of tumour cellularity and spatial heterogeneity.
PATIENTS AND METHODS:
Twenty-two patients with non-small-cell lung cancer prospectively underwent F-FDG PET imaging before tumour resection. We tested nine F-FDG PET parameters: metabolically active tumour volume, total lesion glycolysis, mean standardized uptake value (SUVmean), first-order entropy, energy, skewness, kurtosis, grey-level co-occurrence matrix entropy and lacunarity (SUV-lacunarity). From the haematoxylin and eosin-stained WSIs, we derived mean tumour-cell density (MCD) and lacunarity (path-lacunarity). Spearman's correlation analysis and agglomerative hierarchical clustering were performed to assess variable associations.
RESULTS:
Tumour volumes ranged from 2.2 to 74 cm (median: 17.9 cm). MCD correlated positively with total lesion glycolysis (rs: 0.46, P: 0.007) and SUVmean (rs : 0.55; P: 0.008) and negatively with skewness and kurtosis (rs: -0.47 for both; P: 0.028 and 0.026, respectively). SUV-lacunarity and path-lacunarity were positively correlated (rs: 0.5; P: 0.018). On cluster analysis, larger tumours trended towards higher SUVmean and entropy with a predominance of tightly concentrated high SUV-voxels (negative skewness and low kurtosis on the histogram); on WSI analysis such larger tumours also displayed generally higher MCD and low SUV-lacunarity and path-lacunarity.
CONCLUSION:
Our data suggest that histopathological MCD and lacunarity are associated with several commonly used F-FDG PET-derived indices including SUV-lacunarity, metabolically active tumour volume, SUVmean, entropy, skewness, and kurtosis, and thus may explain the biological basis of F-FDG PET-uptake heterogeneity in non-small-cell lung cancer.
| Original language | English |
|---|---|
| Journal | Nuclear Medicine Communications |
| Early online date | 30 Oct 2018 |
| DOIs | |
| Publication status | Published - 30 Oct 2018 |
