Biomedical subjects

Ing-Tsung Hsiao

Publications and source records attributed to Ing-Tsung Hsiao.

4 recordsLinked to original sources

PubMed2006

Brain SPECT imaging and whole-body biodistribution with [(123)I]ADAM - a serotonin transporter radiotracer in healthy human subjects.

INTRODUCTION: [(123)I]-2-((2-((dimethylamino)methyl)phenyl)thio)-5-iodophenylamine ([(123)I]ADAM), a novel radiotracer, has promising application in the imaging of the serotonin transporter (SERT) in the human brain. In this study, the optimal scanning time for acquiring brain single photon emission computed tomography (SPECT) images was determined by performing dynamic SPECT studies at intervals from 0 to 6 h postinjection of [(123)I]ADAM. Additionally, radiation-absorbed doses were determined for three healthy human subjects using attenuation-corrected images. METHODS: Twelve subjects were randomized into one of three study groups as follows: whole-body distribution imaging (n=3), dynamic SPECT imaging (n=3) and brain SPECT imaging (n=6). The radiation-absorbed dose was calculated using MIRDOSE 3.0 software with attenuation-corrected data. The specific binding (SB) ratio of the brain stem was measured from dynamic SPECT images to determine the optimal scanning time. RESULTS: Dynamic SPECT images showed that the SB of the brain stem gradually increased to a maximum 4 h postinjection. Single photon emission computed tomography images at 4 h postinjection showed a high uptake of the radiotracer (SB) in the hypothalamus (1.40+/-0.12), brain stem (1.44+/-0.16), pons (1.13+/-0.14) and medial temporal lobe (0.59+/-0.10). The mean adult male value of effective dose was 3.37 x 10(-2) mSv/MBq with a 4.8-h urine-voiding interval. Initial high uptake in SERT-rich sites was demonstrated in the lung and brain. A prominent washout of the radiotracer from the lung further increased brain radioactivity that reached a peak value of 5.03% of injected dose 40 min postinjection. CONCLUSIONS: [(123)I]ADAM is a promising radiotracer for SPECT imaging of SERT in humans with acceptable dosimetry and high uptake in SERT-rich regions. Brain SPECT images taken within 4 h following injection show optimal levels of radiotracer uptake in known SERT sites. However, dynamic changes in lung SERT distribution must be carefully evaluated.

Adult↗

PubMed2004

An accelerated convergent ordered subsets algorithm for emission tomography.

We propose an algorithm, E-COSEM (enhanced complete-data ordered subsets expectation-maximization), for fast maximum likelihood (ML) reconstruction in emission tomography. E-COSEM is founded on an incremental EM approach. Unlike the familiar OSEM (ordered subsets EM) algorithm which is not convergent, we show that E-COSEM converges to the ML solution. Alternatives to the OSEM include RAMLA, and for the related maximum a posteriori (MAP) problem, the BSREM and OS-SPS algorithms. These are fast and convergent, but require ajudicious choice of a user-specified relaxation schedule. E-COSEM itself uses a sequence of iteration-dependent parameters (very roughly akin to relaxation parameters) to control a tradeoff between a greedy, fast but non-convergent update and a slower but convergent update. These parameters are computed automatically at each iteration and require no user specification. For the ML case, our simulations show that E-COSEM is nearly as fast as RAMLA.

Algorithms↗

PubMed2003

Rapid calculation of detectability in Bayesian single photon emission computed tomography.

We consider the calculation of lesion detectability using a mathematical model observer, the channelized Hotelling observer (CHO), in a signal-known-exactly/background-known-exactly detection task for single photon emission computed tomography (SPECT). We focus on SPECT images reconstructed with Bayesian maximum a posteriori methods. While model observers are designed to replace time-consuming studies using human observers, the calculation of CHO detectability is usually accomplished using a large number of sample images, which is still time consuming. We develop theoretical expressions for a measure of detectability, the signal-to-noise-ratio (SNR) of a CHO observer, that can be very rapidly evaluated. Key to our expressions are approximations to the reconstructed image covariance. In these approximations, we use methods developed in the PET literature, but modify them to reflect the different nature of attenuation and distance-dependent blur in SPECT. We validate our expressions with Monte Carlo methods. We show that reasonably accurate estimates of the SNR can be obtained at a computational expense equivalent to approximately two projection operations, and that evaluating SNR for subsequent lesion locations requires negligible additional computation.

Algorithms↗

PubMed2003

A new convex edge-preserving median prior with applications to tomography.

In a Bayesian tomographic maximum a posteriori (MAP) reconstruction, an estimate of the object f is computed by iteratively minimizing an objective function that typically comprises the sum of a log-likelihood (data consistency) term and prior (or penalty) term. The prior can be used to stabilize the solution and to also impose spatial properties on the solution. One such property, preservation of edges and locally monotonic regions, is captured by the well-known median root prior (MRP), an empirical method that has been applied to emission and transmission tomography. We propose an entirely new class of convex priors that depends on f and also on m, an auxiliary field in register with f. We specialize this class to our median prior (MP). The approximate action of the median prior is to draw, at each iteration, an object voxel toward its own local median. This action is similar to that of MRP and results in solutions that impose the same sorts of object properties as does MRP. Our MAP method is not empirical, since the problem is stated completely as the minimization of a joint (on f and m) objective. We propose an alternating algorithm to compute the joint MAP solution and apply this to emission tomography, showing that the reconstructions are qualitatively similar to those obtained using MRP.

Algorithms↗