Dual-isotope acquisition for CT-SPECT registration of infection studies.
The registration of CT and NM images can enhance patient diagnosis since it allows for the fusion of anatomical and functional information as well as attenuation correction of NM images. However, irrespective of the methods used, registration accuracy depends heavily on the characteristics of the input images and the degree of similarity between them. This poses a challenge for registering CT and NM images as they may have very different characteristics. To address the particular problem of CT and In-111 SPECT registration, we propose to perform a dual-isotope study which involves an additional injection of Tc-99m MDP to generate two inherently registered images: In-111 SPECT and Tc-99m SPECT. As skeletal structures are visible in both CT and Tc-99m SPECT, performing registration of these images may be much more effective. The very same spatial transformation derived can be immediately applied to complete the registration of CT and the corresponding In-111 SPECT. Accordingly, we hypothesize that the registration of CT and Tc-99m SPECT can be more accurately performed than the registration of CT and In-111 SPECT and seek to compare the accuracies between the aforementioned registrations. In this paper, we have collected three clinical datasets, with the ground-truth transformations known, and tested the proposed approach by using a mutual information-based algorithm to solve for the rigid/non-rigid misalignments introduced to them. Based on the results of our experiments, we conclude that registration using Tc-99m SPECT can achieve 100% success rate, and is thus much more superior to the registration using In-111 SPECT, which at best, achieves only 38% success rate. Clearly, the introduction of a dual-isotope acquisition can substantially improve the registration of SPECT and CT images.
Tang
Lisa
L
Medical Image Analysis Lab, Simon Fraser University, Burnaby, BC, Canada. lisat@sfu.ca
Hamarneh
Ghassan
G
Celler
Anna
A
D003141:Communicable Diseases / Q000175:diagnosis*; D006801:Humans; D013004:Somatostatin / Q000031:analogs & derivatives*; D013669:Technetium Tc 99m Medronate; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*
D013004:Somatostatin; C081788:pentetreotide; D013669:Technetium Tc 99m Medronate