Detection of inter-hemispheric metabolic asymmetries in FDG-PET images using prior anatomical information

[(18)F] FDG positron emission tomography (PET) is commonly used to highlight brain regions with abnormal metabolism. Correct interpretation of FDG images is important for investigation of diseases. When the FDG uptake is compared between hemispheres, confusion can arise because it might be difficult to determine whether an observed asymmetry is physiological and due to normal anatomical variation or pathological. In this paper we propose a new method, which calculates an anatomy-corrected asymmetry index (ACAI), to highlight inter-hemispheric metabolic asymmetry in FDG images without the influence of anatomical asymmetry. Using prior anatomical information from MRI, the ACAI method only takes into account voxels that belong to a certain anatomical class. For the evaluation of detection performance, this method is applied on homogeneous brain phantoms and realistic analytical simulated FDG-PET images with known asymmetries. Results from these simulations demonstrated the validity of ACAI and its potential perspective in the future.