Effects of temporal modeling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections
Abstract
Artifacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projections acquired by a slowly rotating gantry. The artifacts can lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. To overcome these biases in conventional image based dynamic data analysis, we have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In previous work we developed computationally efficient methods for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions [1] and their statistical uncertainties [2] from dynamic SPECT projection data, using a spatial segmentation and temporal B-splines. In addition, we studied the bias that results from modeling various orders of temporal continuity and using various time samplings [1]. In the present work, we use the methods developed in [1, 2] and Monte Carlo simulations to study the effects of the temporal modeling on the statistical variability of the reconstructed distributions.
- Authors:
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Director, Office of Science. Office of Biological and Environmental Research. Medical Sciences Division; National Institutes of Health (US)
- OSTI Identifier:
- 785289
- Report Number(s):
- LBNL-47795
R&D Project: 802317; TRN: US0108423
- DOE Contract Number:
- AC03-76SF00098
- Resource Type:
- Conference
- Resource Relation:
- Conference: 2001 IEEE Nuclear Science Symposium and Medical Imaging Conference, San Diego, CA (US), 11/04/2001--11/10/2001; Other Information: PBD: 30 Apr 2001
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 62 RADIOLOGY AND NUCLEAR MEDICINE; DATA ANALYSIS; DISTRIBUTION; KINETICS; RADIOPHARMACEUTICALS; SINGLE PHOTON EMISSION COMPUTED TOMOGRAPHY; DATA COVARIANCES; MONTE CARLO METHOD; COMPUTERIZED SIMULATION
Citation Formats
Reutter, Bryan W, Gullberg, Grant T, and Huesman, Ronald H. Effects of temporal modeling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections. United States: N. p., 2001.
Web.
Reutter, Bryan W, Gullberg, Grant T, & Huesman, Ronald H. Effects of temporal modeling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections. United States.
Reutter, Bryan W, Gullberg, Grant T, and Huesman, Ronald H. 2001.
"Effects of temporal modeling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections". United States. https://www.osti.gov/servlets/purl/785289.
@article{osti_785289,
title = {Effects of temporal modeling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections},
author = {Reutter, Bryan W and Gullberg, Grant T and Huesman, Ronald H},
abstractNote = {Artifacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projections acquired by a slowly rotating gantry. The artifacts can lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. To overcome these biases in conventional image based dynamic data analysis, we have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In previous work we developed computationally efficient methods for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions [1] and their statistical uncertainties [2] from dynamic SPECT projection data, using a spatial segmentation and temporal B-splines. In addition, we studied the bias that results from modeling various orders of temporal continuity and using various time samplings [1]. In the present work, we use the methods developed in [1, 2] and Monte Carlo simulations to study the effects of the temporal modeling on the statistical variability of the reconstructed distributions.},
doi = {},
url = {https://www.osti.gov/biblio/785289},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Apr 30 00:00:00 EDT 2001},
month = {Mon Apr 30 00:00:00 EDT 2001}
}