The precision of textural analysis in 18F-FDG-PET scans of oesophageal cancer

Objectives Measuring tumour heterogeneity by textural analysis in F-18-fluorodeoxyglucose positron emission tomography (F-18-FDG PET) provides predictive and prognostic information but technical aspects of image processing can influence parameter measurements. We therefore tested effects of image smoothing, segmentation and quantisation on the precision of heterogeneity measurements. Methods Sixty-four F-18-FDG PET/CT images of oesophageal cancer were processed using different Gaussian smoothing levels (2.0, 2.5, 3.0, 3.5, 4.0 mm), maximum standardised uptake value (SUVmax) segmentation thresholds (45 %, 50 %, 55 %, 60 %) and quantisation (8, 16, 32, 64, 128 bin widths). Heterogeneity parameters included grey-level co-occurrence matrix (GLCM), grey-level run length matrix (GLRL), neighbourhood grey-tone difference matrix (NGTDM), grey-level size zone matrix (GLSZM) and fractal analysis methods. The concordance correlation coefficient (CCC) for the three processing variables was calculated for each heterogeneity parameter. Results Most parameters showed poor agreement between different bin widths (CCC median 0.08, range 0.004-0.99). Segmentation and smoothing showed smaller effects on precision (segmentation: CCC median 0.82, range 0.33-0.97; smoothing: CCC median 0.99, range 0.58-0.99). Conclusions Smoothing and segmentation have only a small effect on the precision of heterogeneity measurements in F-18-FDG PET data. However, quantisation often has larger effects, highlighting a need for further evaluation and standardisation of parameters for multicentre studies.