Improved activity estimation with MC-JOSEM versus TEW-JOSEM in 111In SPECT.
We have previously developed a fast Monte Carlo (MC)-based joint ordered-subset expectation maximization (JOSEM) iterative reconstruction algorithm, MC-JOSEM. A phantom study was performed to compare quantitative imaging performance of MC-JOSEM with that of a triple-energy-window approach (TEW) in which estimated scatter was also included additively within JOSEM, TEW-JOSEM. We acquired high-count projections of a 5.5 cm3 sphere of 111In at different locations in the water-filled torso phantom; high-count projections were then obtained with 111In only in the liver or only in the soft-tissue background compartment, so that we could generate synthetic projections for spheres surrounded by various activity distributions. MC scatter estimates used by MC-JOSEM were computed once after five iterations of TEW-JOSEM. Images of different combinations of liver/background and sphere/background activity concentration ratios were reconstructed by both TEW-JOSEM and MC-JOSEM for 40 iterations. For activity estimation in the sphere, MC-JOSEM always produced better relative bias and relative standard deviation than TEW-JOSEM for each sphere location, iteration number, and activity combination. The average relative bias of activity estimates in the sphere for MC-JOSEM after 40 iterations was -6.9%, versus -15.8% for TEW-JOSEM, while the average relative standard deviation of the sphere activity estimates was 16.1% for MC-JOSEM, versus 27.4% for TEW-JOSEM. Additionally, the average relative bias of activity concentration estimates in the liver and the background for MC-JOSEM after 40 iterations was -3.9%, versus -12.2% for TEW-JOSEM, while the average relative standard deviation of these estimates was 2.5% for MC-JOSEM, versus 3.4% for TEW-JOSEM. MC-JOSEM is a promising approach for quantitative activity estimation in 111In SPECT.
Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts 02115, USA. ouyang@bwh.harvard.edu
Jinsong
J
Ouyang
Georges
G
El Fakhri
Stephen C
SC
Moore
D000465:Algorithms; D004867:Equipment Design; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007205:Indium Radioisotopes / Q000494:pharmacology*; D008168:Lung / Q000473:pathology; D015233:Models, Statistical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012542:Scattering, Radiation; D012984:Software; D015899:Tomography, Emission-Computed, Single-Photon / Q000295:instrumentation* / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods
D007205:Indium Radioisotopes