Absolute activity quantitation from projections using an analytical approach: Comparison with iterative methods in Tc-99m and I-123 brain SPECT

Estimates of SPECT activity within certain deep brain structures could be u seful for clinical tasks such as early prediction of Alzheimer's disease wi th Tc-99m or Parkinson's disease with I-123; however, such estimates are bi ased by poor spatial resolution and inaccurate scatter and attenuation corr ections. We compared an analytical approach (AA) of more accurate quantitat ion to a slower iterative approach (TA). Monte Carlo simulated projections of 12 normal and 12 pathologic Tc-99m perfusion studies, as well as 12 norm al and 12 pathologic I-123 neurotransmission studies, were generated using a digital brain phantom and corrected for scatter by a multispectral fittin g procedure. The AA included attenuation correction by a modified Metz-Pan algorithm and activity estimation by a technique that incorporated Metz fil tering to compensate for variable collimator response (VCR), IA-modeled att enuation, and VCR in the projector/backprojector of an ordered subsets-expe ctation maximization (OSEM) algorithm. Bias and standard deviation over the 12 normal and 12 pathologic patients were calculated with respect to the r eference values in the corpus callosum, caudate nucleus, and putamen. The I A and AA yielded similar quantitation results in both Tc-99m and I-123 stud ies in all brain structures considered in both normal and pathologic patien ts. The bias with respect to the reference activity distributions was less than 7% for Tc-99m studies, but greater than 30% for I-123 studies, due to partial volume effect in the striata. Our results were validated using I-12 3 physical acquisitions of an anthropomorphic brain phantom. The AA yielded quantitation accuracy comparable to that obtained with IA, while requiring much less processing time. However. in most conditions, IA yielded lower n oise for the same bias than did AA.