Fast Monte Carlo based joint iterative reconstruction for simultaneous SPECT imaging
Authors: Ouyang Jinsong , El Fakhri Georges , Moore Stephen C. 
Published: August 2007

Simultaneous SPECT allows the assessment of two physiological functions under identical conditions. The separation of these radionuclides is difficult, however, because their energies are close. Most energy‐window‐based scatter correction methods do not fully model either physical factors or patient‐specific activity and attenuation distributions. We have developed a fast Monte Carlo (MC) simulation‐based multiple‐radionuclide and multiple‐energy joint ordered‐subset expectation‐maximization (JOSEM) iterative reconstruction algorithm, MC‐JOSEM. MC‐JOSEM simultaneously corrects for scatter and cross talk as well as detector response within the reconstruction algorithm. We evaluated MC‐JOSEM for simultaneous brain profusion (‐HMPAO) and neurotransmission (‐altropane) SPECT. MC simulations of and studies were generated separately and then combined to mimic simultaneous SPECT. All the details of photon transport through the brain, the collimator, and detector, including Compton and coherent scatter, septal penetration, and backscatter from components behind the crystal, were modeled. We reconstructed images from simultaneous dual‐radionuclide projections in three ways. First, we reconstructed the photopeak‐energy‐window projections (with an asymmetric energy window for ) using the standard ordered‐subsets expectation‐maximization algorithm (NSC‐OSEM). Second, we used standard OSEM to reconstruct photopeak‐energy‐window projections, while including an estimate of scatter from a Compton‐scatter energy window (SC‐OSEM). Third, we jointly reconstructed both and images using projection data associated with two photopeak energy windows and an intermediate‐energy window using MC‐JOSEM. For 15 iterations of reconstruction, the bias and standard deviation of activity estimates in several brain structures were calculated for NSC‐OSEM, SC‐OSEM, and MC‐JOSEM, using images reconstructed from primary (unscattered) photons as a reference. Similar calculations were performed for images for NSC‐OSEM and MC‐JOSEM. For images, dopamine binding potential (BP) at equilibrium and its signal‐to‐noise ratio (SNR) were also calculated. Our results demonstrate that MC‐JOSEM performs better than NSC‐ and SC‐OSEM for quantitation tasks. After 15 iterations of reconstruction, the relative bias of activity estimates in the thalamus, striata, white matter, and gray matter volumes from MC‐JOSEM ranged from to 1.2%, while the same estimates for NSC‐OSEM (SC‐OSEM) ranged from 20.8% to 103.6% (7.2% to 41.9%). Similarly, the relative bias of activity estimates from 15 iterations of MC‐JOSEM in the striata and background ranged from to 2.9%, while the same estimates for NSC‐OSEM ranged from 1.6% to 10.0%. The relative standard deviation of activity estimates from MC‐JOSEM ranged from 1.1% to 4.8% versus 1.2% to 6.7% (1.2% to 5.9%) for NSC‐OSEM (SC‐OSEM). The relative standard deviation of activity estimates using MC‐JOSEM ranged from 1.1% to 1.9% versus 1.5% to 2.7% for NSC‐OSEM. Using the dopamine BP obtained from the reconstruction produced by primary photons as a reference, the result for MC‐JOSEM was 50.5% closer to the reference than that of NSC‐OSEM after 15 iterations. The SNR for dopamine BP was 23.6 for MC‐JOSEM as compared to 18.3 for NSC‐OSEM.