An automatic method for accurate volume delineation of heterogeneous tumors in PET

Objectives: Accurate volumetric tumor delineation is of increasing importance in radiation treatment planning. Many tumors exhibit only moderate tracer uptake heterogeneity and delineation methods using an adaptive threshold lead to robust results. These methods use a tumor reference value R (e.g. ROI maximum) and the tumor background Bg to compute the volume reproducing threshold. This threshold corresponds to an iso-contour which defines the tumor boundaries. However, the boundaries of strongly heterogeneous tumors can not be described by an iso-contour anymore and therefore conventional threshold methods are not suitable for accurate delineation. The aim of this work is the development and validation of a delineation method for heterogeneous tumors.

Methods: The new method (TV) can be considered as an extension of the adaptive threshold methods (TK), where instead of a single threshold for the whole ROI a local threshold is computed by determining for each voxel Bg and R in the close vicinity of the voxel. The absolute threshold for the considered voxel is then given by T_abs=Tx(R -Bg)+Bg, where T=0.39 was determined with phantom measurements. Validation: 10 clinical datasets (5 patients with lung cancer, 5 with head and neck cancer) were used to generate 10 realistic anthropomorphic software phantoms of strongly heterogeneous tumors with well known volume and boundaries. Volume delineation was performed with TK and TV.

Results: In contrast to TK, TV was able to reproduce the true tumor boundaries accurately. The deviation of the determined volume from the true volume was 6.9+/-6.6% for TV and 47.5+/-16.8% for TK.

Conclusions: In anthropomoric software phantoms the new method leads to promising results and a clear improvement of volume delineation in comparison to conventional background-corrected thresholding. In the next step, the suitability for clinical routine will be further investigated.