Accuracy assessment of an automatic image-based PET/CT registration for ultrasound-guided biopsies and ablations

The multimodal fusion of spatially tracked real-time ultrasound (US) with a prior CT scan has demonstrated clinical utility, accuracy, and positive impact upon clinical outcomes when used for guidance during biopsy and radiofrequency ablation in the treatment of cancer. Additionally, the combination of CT-guided procedures with positron emission tomography (PET) may not only enhance navigation, but add valuable information regarding the specific location and volume of the targeted masses which may be invisible on CT and US. The accuracy of this fusion depends on reliable, reproducible registration methods between PET and CT. This can avoid extensive manual efforts to correct registration which can be long and tedious in an interventional setting. In this paper, we present a registration workflow for PET/CT/US fusion by analyzing various image metrics based on normalized mutual information and cross-correlation, using both rigid and affine transformations to automatically align PET and CT. Registration is performed between the CT component of the prior PET-CT and the intra-procedural CT scan used for navigation to maximize image congruence. We evaluate the accuracy of the PET/CT registration by computing fiducial and target registration errors using anatomical landmarks and lesion locations respectively. We also report differences to gold-standard manual alignment as well as the root mean square errors for CT/US fusion. Ten patients with prior PET/CT who underwent ablation or biopsy procedures were selected for this study. Studies show that optimal results were obtained using a cross-correlation based rigid registration with a landmark localization error of 1.1 +/- 0.7 mm using a discrete graph-minimizing scheme. We demonstrate the feasibility of automated fusion of PET/CT and its suitability for multi-modality ultrasound guided navigation procedures.