Analysis of dynamic SPECT/CT measurements of the arterial input function in human subjects

Measurement of the arterial input function (AIF) is essential to deriving quantitative estimates of regional myocardial blood flow using kinetic models. Accurate measurements have been possible with a wide range of radiotracers in both research and clinical PET/CT imaging. However, accurate measurements of the AIF with dynamic SPECT or SPECT/CT have posed various challenges; foremost being that imaging a rapidly evolving radiotracer distribution with a slowly-rotating single- or dual-head SPECT scanner yields temporally inconsistent projection data. A method is developed for quantifying the AIF in human subjects from dynamic SPECT/CT measurements of
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Tc-tetrofosmin concentration in the left atrium imaged with a Philips Precedence SPECT/CT scanner. A 2-minute infusion is imaged in a series of eight back-to-back 180-degree continuous-mode acquisitions (or rotations), with the dual camera heads. In each acquisition a set of 36 projections (128 ? 128 pixels of dimension 3.19 mm ? 3.19 mm) is acquired in each rotation each over a time span of 54 seconds yielding a total acquisition time of 432 seconds. The AIF is computed using both traditional image-based analysis and full spatiotemporal image reconstruction methods (referred to as 4D recon). The errors induced by data inconsistency are evaluated by two approaches. The first method derives SPECT-like dynamic (inconsistent) projection data from selected forward projections, chosen from modeled SPECT acquisitions, of existing dynamic
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Tc-MIBI PET images. The second validation method uses a database of SPECT measurements of an anthropomorphic phantom to generate SPECT-like projections. The first validation study using a two minute infusion showed very little bias in the time-activity curves estimated from the simulated dynamic cardiac SPECT patient study; whereas, the second validation study using a one minute infusion showed considerable more bias in the estimated time-activity curves and parametric parameters. We believe that this is the result of selecting non optimum basis functions.