Image fusion using CT, MRI and PET for treatment planning, navigation and follow up in percutaneous RFA

To evaluate the feasibility of fusion of morphologic and functional imaging modalities to facilitate treatment planning, probe placement, probe re-positioning, and early detection of residual disease following radiofrequency ablation (RFA) of cancer.

Multi-modality datasets were separately acquired that included functional (FDG-PET and DCE-MRI) and standard morphologic studies (CT and MRI). Different combinations of imaging modalities were registered and fused prior to, during, and following percutaneous image-guided tumor ablation with radiofrequency. Different algorithms and visualization tools were evaluated for both intra-modality and inter-modality image registration using the software MIPAV (Medical Image Processing, Analysis and Visualization). Semi-automated and automated registration algorithms were used on a standard PC workstation: 1) landmark-based least-squares rigid registration, 2) landmark-based thin-plate spline elastic registration, and 3) automatic voxel-similarity, affine registration.

Intra- and inter-modality image fusion were successfully performed prior to, during and after RFA procedures. Fusion of morphologic and functional images provided a useful view of the spatial relationship of lesion structure and functional significance. Fused axial images and segmented three-dimensional surface models were used for treatment planning and post-RFA evaluation, to assess potential for optimizing needle placement during procedures.

Fusion of morphologic and functional images is feasible before, during and after radiofrequency ablation of tumors in abdominal organs. For routine use, the semi-automated registration algorithms may be most practical. Image fusion may facilitate interventional procedures like RFA and should be further evaluated.