Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.

. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis.

Comparison of deep learning-based denoising methods in cardiac SPECT.

Background: Myocardial perfusion SPECT (MPS) images often suffer from artefacts caused by low-count statistics. Poor-quality images can lead to misinterpretations of perfusion defects. Deep learning (DL)-based methods have been proposed to overcome the noise artefacts.

Quantitative bone SPECT/CT reconstruction utilizing anatomical information.

Background: Bone SPECT/CT has been shown to offer superior sensitivity and specificity compared to conventional whole-body planar scanning. Furthermore, bone SPECT/CT allows quantitative imaging, which is challenging with planar methods. In order to gain better quantitative accuracy, Bayesian reconstruction algorithms, including both image derived and anatomically guided priors, have been utilized in reconstruction in PET/CT scanning, but they have not been widely used in SPECT/CT studies.

Quantitative Monte Carlo-based brain dopamine transporter SPECT imaging.

Objective: Brain dopamine transporter imaging with I-123-labeled radioligands is technically demanding due to the small size of the imaging target relative to the spatial resolution of most SPECT systems. In addition, I-123 has high-energy peaks which can penetrate or scatter in the collimator and be detected in the imaging energy window. The aim of this study was to implement Monte Carlo (MC)-based full collimator-detector response (CDR) compensation algorithm for I-123 into a third-party commercial SPECT reconstruction software package and to evaluate its effect on the quantitative accuracy of dopaminergic-image analysis compared to a method where only the geometric component of the CDR is compensated.

Evaluation of quantitative 123I and 131I SPECT with Monte Carlo-based down-scatter compensation.

Objective: Quantitative I and I single-photon emission computed tomography (SPECT) is hampered by down-scatter from the high-energy peaks. This paper presents a down-scatter compensation method, where down-scatter generated in the patient and gamma camera collimator and detector is modelled using Monte Carlo simulation in the ordered subsets expectation maximization SPECT reconstruction algorithm.

Materials And Methods: The new down-scatter compensation method was compared with conventional triple energy window (TEW) scatter compensation and Gaussian convolution-based forced detection Monte Carlo methods.

Multicenter evaluation of single-photon emission computed tomography quantification with third-party reconstruction software.

Reliable and reproducible quantification is essential in many clinical situations. Previously, single-photon emission computed tomography (SPECT) has not been considered a quantitative imaging modality, but recent advances in reconstruction algorithm development have made SPECT quantitative. In this study, we investigate the reproducibility of SPECT quantification with phantoms in a multicenter setting using novel third-party reconstruction software.

Optimisation of reconstruction--reprojection-based motion correction for cardiac SPECT.

Objective: Cardiac motion is a challenging cause of image artefacts in myocardial perfusion SPECT. A wide range of motion correction methods have been developed over the years, and so far automatic algorithms based on the reconstruction--reprojection principle have proved to be the most effective. However, these methods have not been fully optimised in terms of their free parameters and implementational details.

Optimisation of simultaneous tl-201/tc-99m dual isotope reconstruction with monte-carlo-based scatter correction.

Simultaneous Tl-201/Tc-99m dual isotope myocardial perfusion SPECT is seriously hampered by down-scatter from Tc-99m into the Tl-201 energy window. This paper presents and optimises the ordered-subsets-expectation-maximisation-(OS-EM-) based reconstruction algorithm, which corrects the down-scatter using an efficient Monte Carlo (MC) simulator. The algorithm starts by first reconstructing the Tc-99m image with attenuation, collimator response, and MC-based scatter correction.

Half-time myocardial perfusion SPECT imaging with attenuation and Monte Carlo-based scatter correction.

Purpose: To test the potential of a new reconstruction algorithm with Monte Carlo-based scatter correction in half-time myocardial perfusion single-photon emission computed tomography (SPECT).

Materials And Methods: The mathematical four-dimensional NURBS-based Cardiac-Torso phantom and the SIMIND Monte Carlo simulation package were used to simulate full-time and half-time SPECT projection data. The data were reconstructed using the standard ordered subset expectation maximization-based algorithm and the new Monte Carlo-based algorithm.

Reduction of collimator correction artefacts with bayesian reconstruction in spect.

Poor resolution of single photon emission computed tomography (SPECT) has degraded its use in clinical practice. Collimator correction has been shown to improve the reconstructed resolution, but the correction can generate ringing artefacts, which lower image quality. This paper investigates whether Bayesian reconstruction methods could reduce these artefacts.

Differential hypometabolism patterns according to mild cognitive impairment subtypes.

Aims: The present study investigated cerebral glucose metabolism and structural atrophy in controls and subjects with mild cognitive impairment (MCI).

Methods: The study included 13 controls, 7 MCI subjects considered as prodromal Alzheimer's disease (MCI of the Alzheimer type, aMCI) and 7 MCI subjects having cognitive decline due to other causes, established by clinical evaluation (MCI of the non-Alzheimer type, naMCI). Glucose metabolism in the frontal, parietal and posterior cingulate cortices, the hippocampus and parahippocampal gyrus was evaluated using Statistical Parametric Mapping 2 (SPM2).