Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.

A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

[Clinical target volume delineation for radiotherapy of the esophagus]. / Définition du volume cible anatomoclinique pour l'irradiation des cancers de l'œsophage.

The dense lymphatic network of the esophagus facilitates tumour spreading along the cephalo-caudal axis and to locoregional lymph nodes. A better understanding of microscopic invasion by tumour cells, based on histological analysis of surgical specimens and analysis of recurrence sites, has justified a reduction in radiotherapy target volumes. The delineation of the clinical target volume (CTV) depends on tumour characteristics (site, histology) and on its spread as assessed on endoscopic ultrasonography and ((18)F)-fluorodeoxyglucose positron-emission tomography (FDG-PET). We propose that positive and negative predictive values for FDG-PET should be used to adapt the CTV according to the risk of nodal involvement.