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Compartmental Analysis of Technetium-99m-Teboroxime Kinetics Employing Fast Dynamic SPECT at Rest and Stress

Department of Internal Medicine, Division of Nuclear Medicine, University of Michigan Medical Center, Ann Arbor, Michigan

Correspondence: For correspondence and reprints contact: Ping-Chun Chiao, PhD, The University of Michigan Medical Center, Cyclotron/PET Facility, 3480 Kresge III Bldg., Ann Arbor, MI 48109-0552.

ABSTRACT

We have examined the feasibility of compartmental analysis of ^99mTc-teboroxime kinetics in measuring physiological changes in response to adenosine-induced coronary vasodilation. To evaluate the effect of tracer recirculation on ^99mTc-teboroxime kinetics in the myocardium, we also compared compartmental analysis with washout analysis (monoexponential fitting), which does not account for this effect. Methods: Eight healthy male volunteers were imaged using fast dynamic SPECT protocols (5 sec per tomographic image) at rest and during adenosine infusion. A two-compartment model was used and compartmental parameters K1 and k2 (characterizing the diffusion of ^99mTc-teboroxime from the blood to the myocardium and from the myocardium to the blood, respectively) were fitted from myocardial time-activity curves and left ventricular input functions. Results: Both K1 and washout estimates for the whole left ventricular myocardium changed significantly in response to coronary vasodilation. Mean stress-to-rest (S/R) ratios were almost two times higher for K1 (S/R = 2.7 ± 1.1) than for washout estimates (S/R = 1.5 ± 0.3). Estimation of K1 for all local regions, except the septal wall, is feasible because variations in K1 estimates for all local regions, except the septum during stress, are comparable with those for the global region. Conclusions: We conclude that quantitative compartmental analysis of ^99mTc-teboroxime kinetics provides a sensitive indicator for changes in response to adenosine-induced coronary vasodilation.

Key Words: SPECT • technetium-99m teboroxime • cardiac imaging • compartmental modeling