• DocumentCode
    3340940
  • Title

    Activity estimation in small volumes with non-uniform radiotracer uptake using a local projection-based fitting approach

  • Author

    Southekal, Sudeepti ; McQuaid, Sarah J. ; Moore, Stephen C.

  • Author_Institution
    Med. Sch., Brigham & Women´´s Hosp., Harvard Univ., Boston, MA, USA
  • fYear
    2011
  • fDate
    23-29 Oct. 2011
  • Firstpage
    3777
  • Lastpage
    3779
  • Abstract
    We have previously evaluated a local projection-based approach that provides robust estimates of activity concentration in small volumes-of-interest (VOI) affected by partial volume and tissue crosstalk in clinical SPECT imaging. The approach requires local segmentation of functionally distinct tissues within a VOI from a registered, high-resolution anatomical image of the object. Measured projection data are fitted to a statistical model of segmented-tissue projections. The resulting linear equations are solved to recover corrected values of tissue-activity concentration. In this work, we extended the approach to incorporate models of non-uniform radiotracer uptake into the fitting procedure. We evaluated the modified method using 25 independent noise realizations of simulated torso phantoms, each containing 20 identical, spherical “tumors” within a homogenous activity background. Radially varying quadratic functions were used to simulate two degrees (50% and 90%) of reduced central uptake inside the tumors (e.g., from necrosis), with an average integrated tumor-to-background concentration ratio of 7:1. Tumor-activity estimates were obtained by fitting projection data to models that assumed either uniform tracer uptake (UF) or radially varying non-uniform uptake (NUF). The sensitivity of the approach to registration errors was investigated by simulating a 1-pixel misspecification of the locations of the VOI. The NUF approach achieved better than 1% bias and 12% precision for total tumor-activity estimates. Increasing the degree of central count loss from 50% to 90% did not significantly affect the NUF bias. In comparison, the UF method yielded 16% bias and 1% precision (48% bias, 5% precision) for 50% (90%) central count loss. The simulated registration error did not affect the UF estimates, but degraded the accuracy (and precision) of NUF estimates to 11% (and 13%). Despite slightly inferior precision, NUF may permit improved assessment of inhomog- neous tumor uptake.
  • Keywords
    image registration; image segmentation; medical image processing; physiological models; radioactive tracers; single photon emission computed tomography; tumours; activity concentration estimation; clinical SPECT imaging; linear equations; local projection based fitting approach; local tissue segmentation; nonuniform radiotracer uptake models; partial volume; projection data; radially varying nonuniform uptake; radially varying quadratic functions; registered high resolution anatomical images; segmented tissue projection; simulated torso phantoms; small volume activity estimation; statistical model; tissue activity concentration; tissue crosstalk; tumor activity estimates; tumor-background concentration ratio; tumors; uniform tracer uptake; Biomedical imaging; Copper;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE
  • Conference_Location
    Valencia
  • ISSN
    1082-3654
  • Print_ISBN
    978-1-4673-0118-3
  • Type

    conf

  • DOI
    10.1109/NSSMIC.2011.6153714
  • Filename
    6153714