Purpose: A problem for clinicians is to mentally integrate information from multiple diagnostic sources, such as computed tomography (CT), magnetic resonance (MR), and single photon emission computed tomography (SPECT), whose images give anatomic and metabolic information.
Methods and materials: To combine this different imaging procedure information, and to overlay correspondent slices, we used commercially available software packages (SRS PLATO and IFS). The algorithms utilize a fiducial-based coordinate system (or frame) with 3 N-shaped markers, which allows coordinate transformation of a clinical examination data set (9 spots for each transaxial section) to a stereotactic coordinate system. The N-shaped markers were filled with fluids visible in each modality (gadolinium for MR, calcium chloride for CT, and 99mTc for SPECT). The frame is relocatable, in the different acquisition modalities, by means of a head holder to which a face mask is fixed so as to immobilize the patient. Position errors due to the algorithms were obtained by evaluating the stereotactic coordinates of five sources detectable in each modality.
Results: SPECT and MR position errors due to the algorithms were evaluated with respect to CT: deltax was < or = 0.9 mm for MR and < or = 1.4 mm for SPECT, deltay was < or = 1 mm and < or = 3 mm for MR and SPECT, respectively. Maximal differences in distance between estimated and actual fiducial centers (geometric mismatch) were in the order of the pixel size (0.8 mm for CT, 1.4 mm for MR, and 1.8 mm for SPECT). In an attempt to distinguish necrosis from residual disease, the image fusion protocol was studied in 35 primary or metastatic brain tumor patients.
Conclusions: The image fusion technique has a good degree of accuracy as well as the potential to improve the specificity of tissue identification and the precision of the subsequent treatment planning.