Radiofrequency ablation (RFA) is emerging as the primary mode of treatment of unresectable malignant liver tumors.
With current intraoperative imaging modalities, quick, precise, and complete localization of lesions remains a challenge
for liver RFA. Fusion of intraoperative CT and preoperative PET images, which relies on PET and CT registration, can
produce a new image with complementary metabolic and anatomic data and thus greatly improve the targeting accuracy.
Unlike neurological images, alignment of abdominal images by combined PET/CT scanner is prone to errors as a result
of large nonrigid misalignment in abdominal images. Our use of a normalized mutual information-based 3D nonrigid
registration technique has proven powerful for whole-body PET and CT registration. We demonstrate here that this
technique is capable of acceptable abdominal PET and CT registration as well. In five clinical cases, both qualitative and
quantitative validation showed that the registration is robust and accurate. Quantitative accuracy was evaluated by
comparison between the result from the algorithm and clinical experts. The accuracy of registration is much less than the
allowable margin in liver RFA. Study findings show the technique's potential to enable the augmentation of
intraoperative CT with preoperative PET to reduce procedure time, avoid repeating procedures, provide clinicians with
complementary functional/anatomic maps, avoid omitting dispersed small lesions, and improve the accuracy of tumor
targeting in liver RFA.