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
Link To Document :
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