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Fast direct estimation of the blood input function and myocardial time activity curve from dynamic SPECT projections via reduction in spatial and temporal dimensions
Author(s) -
Zan Yunlong,
Boutchko Rostyslav,
Huang Qiu,
Li Biao,
Chen Kewei,
Gullberg Grant T.
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4816944
Subject(s) - imaging phantom , iterative reconstruction , computer science , single photon emission computed tomography , reduction (mathematics) , computation , parametric statistics , basis function , algorithm , artificial intelligence , medical imaging , computer vision , mathematics , nuclear medicine , physics , optics , statistics , medicine , mathematical analysis , geometry
Purpose: Reconstruction of parametric images from dynamic single photon emission computed tomography (SPECT) data acquired with slow rotating cameras is a challenge because the estimation of the time–activity curves (TACs) may involve fitting data to an inconsistent underdetermined system of equations. This work presents a novel algorithm for the estimation of the blood input function and myocardial TAC with high accuracy and high efficiency directly from these projections.Methods: In the proposed dynamic reconstruction method, the information from the segmentation of functional regions from the static reconstructed image was used as a prior to construct a sparse matrix, through which the spatial distribution of the radioactive tracer was represented. Then the temporal distribution of the radioactive tracer was modeled by nonuniform B‐spline basis functions which were determined according to a new selection rule. With reduction in both the spatial and temporal dimensions of the reconstructed image, the blood input function and myocardial TAC were estimated using the 4D maximum likelihood expectation maximization algorithm. The method was validated using data from both digital phantom simulations and an experimental rat study.Results: Compared with the conventional dynamic SPECT reconstruction method without the reduction in spatial dimensions, the proposed method provides more accurate TACs with less computation time in both phantom simulation studies and a rat experimental study.Conclusions: The proposed method is promising in both providing more accurate time–activity curves and reducing the computation time, which makes it practical for small animal studies using clinical systems with slow rotating cameras.