Despite the growing use of fluorine-18-fluorodeoxyglucose (18F-FDG) PET texture analysis to measure intratumoural heterogeneity in cancer research, the biologic basis of 18F-FDG PET-derived texture variables is poorly understood. We aimed to assess correlations between 18F-FDG PET-derived texture variables and whole-slide image (WSI)-derived metrics of tumour cellularity and spatial heterogeneity.
Twenty-two patients with non-small-cell lung cancer prospectively underwent 18F-FDG PET imaging before tumour resection. We tested nine 18F-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.
Tumour volumes ranged from 2.2 to 74 cm3 (median: 17.9 cm3). 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.
Our data suggest that histopathological MCD and lacunarity are associated with several commonly used 18F-FDG PET-derived indices including SUV-lacunarity, metabolically active tumour volume, SUVmean, entropy, skewness, and kurtosis, and thus may explain the biological basis of 18F-FDG PET-uptake heterogeneity in non-small-cell lung cancer.
aCentre for Cancer Imaging, The Institute of Cancer Research, Sutton
Departments of bClinical Pathology
cThoracic Surgery, Guy’s and St Thomas’ NHS Foundation Trust
dDepartment of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences
ePET Imaging Centre and the Division of Imaging Sciences and Biomedical Engineering, King’s College
fDepartment of Radiology, Guy’s Hospital, Great Maze Pond, London, UK
Correspondence to Usman Bashir, FRCR, Centre for Cancer Imaging, The Institute of Cancer Research, 15 Cotswold Road, Sutton SM2 5NG, UK Tel: +44 759 845 4470; fax: +44 20 7370 5261; e-mail: email@example.com
Received May 25, 2018
Received in revised form September 10, 2018
Accepted September 24, 2018