Detection and characterization of the tumor change between two FDG PET scans using parametric imaging

Abstract

Patient follow-up based on PET scans is a promising approach for early assessment of tumor response and for detection of tumor recurrence. In this work, we introduce a parametric imaging method to detect and analyze the tumor changes between 2 consecutive PET scans. Fifteen pairs of consecutives PET/CT images obtained during the course of lung cancer patient monitoring were considered. For each pair, after CT- based registration of the PET images, the two PET datasets were subtracted. A biparametric graph of subtracted voxel values versus voxel values in the first scan was obtained. A model- based analysis of this graph was used to identify the tumor voxels in which significant changes occurred between the 2 scans, and yielded indices characterizing the changes. In our patients, the proposed approach correctly identified all tumor changes as confirmed using a conventional analysis. In addition, the parametric imaging approach can reveal heterogeneities in tumor response and does not require the preliminary identification of the tumors.