Background: In treatment of non-Hodgkin's lymphoma patients with predose-plus-I-131-labeled anti-B1 (anti-CD20) monoclonal antibody, an intratherapy single photon emission computed tomography (SPECT) image is an important part of research estimates of tumor dosimetry. For that imaging, a computed tomography (CT)-SPECT fusion is used both to obtain an attenuation map for the space-alternating generalized expectation maximization reconstruction and to provide CT-based volumes of interest (VoI) to determine activity in tumors and organs. Fusion based on external, skin-surface markers has been used but may not correctly superimpose internal structures.
Methods: A new algorithm, developed and implemented in the Department of Radiology, University of Michigan, and based on the mutual information of grayscale values, was investigated. Results from four anti-B1 therapy patients are presented.
Results: In one patient, the new intensity-based fusion provided total reconstructed counts for kidneys that were higher than those produced by marker-based fusion; therefore, the VoI was probably located more accurately. In a second patient, after an acquisition that did not include any skin markers, the new algorithm produced counts/pixel that were similar for four of five tumors consistent with what is expected from an ideal therapy combined with accurate count density estimates. The fifth tumor was quite small and will have its final activity estimate moved toward consistency with the others after a recovery coefficient multiplication. For four tumors in two patients, direct comparison of the two algorithms yielded count totals that were different by no more than 7.2%.
Conclusions: The use of CT-SPECT fusion and subsequent transfer of tumor VoI originally drawn in high-resolution CT space offers potential advantages for quantifying tumor uptake of radioactivity. A new, mutual-information-based fusion algorithm is usable without skin markers. Results indicate that the new fusion algorithm gives equal tumor count values within 7.2% compared with fusion based on external markers. It increases estimates of kidney activity by an average of 6.4%.