Segmentation des images TEP au 18F-FDG. Principe et revue de la littérature

Several segmentation methods of lesion uptake in ¹⁸F-FDG PET imaging have been proposed in the literature. Their principles are presented along with their clinical results. The main approach proposed in the literature is the thresholding method. The most commonly used is a constant threshold around 40% of the maximum uptake within the lesion. This simple approach is not valid for small (< 4 or 5 mL), poorly contrasted positive tissue (SUV < 2) or lesion in movement. To limit these problems, more complex thresholding algorithms have been proposed to define the optimal threshold value to be applied to segment the lesion. The principle is to adapt the threshold following a fitting model according to one or two characteristic image parameters. Those algorithms based on iterative approaches to find the optimal threshold value are preferred as they take into account patient data. The main drawback is the need of a calibration step depending on the PET device, the acquisition conditions and the algorithm used for image reconstruction. To avoid this problem, some more sophisticated segmentation methods have been proposed in the literature: derivative methods, watershed and pattern recognition algorithms. The delineation of positive tissue on FDG-PET images is a complex problem, always under investigation.