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. Therefore, the aim of this work was to evaluate the performance of CT-guided reconstruction in quantitative bone SPECT. METHODS: Three Bayesian reconstruction methods were evaluated against the conventional ordered subsets expectation maximization (OSEM) reconstruction method. One of the studied Bayesian methods was the relative difference prior (RDP), which has recently gained popularity in PET reconstruction. The other two methods, anatomically guided smoothing prior (AMAP-S) and anatomically guided relative difference prior (AMAP-R), utilized anatomical information from the CT scan. The reconstruction methods were evaluated in terms of quantitative accuracy with artificial lesions inserted in clinical patient studies and with 20 real clinical patients. Maximum and mean standardized uptake values (SUVs) of the lesions were defined. RESULTS: The analyses showed that all studied Bayesian methods performed better than OSEM and the anatomical priors also outperformed RDP. The average relative error in mean SUV for the artificial lesion study for OSEM, RDP, AMAP-S, and AMAP-R was - 53%, - 35%, - 15%, and - 10%, when the CT study had matching lesions. In the patient study, the RDP method gave 16 ± 9% higher maximum SUV values than OSEM, while AMAP-S and AMAP-R offered increases of 36 ± 8% and 36 ± 9%, respectively. Mean SUV increased for RDP, AMAP-S, and AMAP-R by 18 ± 9%, 26 ± 5%, and 33 ± 5% when compared to OSEM. CONCLUSIONS: The Bayesian methods with anatomical prior, especially the relative difference prior-based method (AMAP-R), outperformed OSEM and reconstruction without anatomical prior in terms of quantitative accuracy.

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. The comparison was made with the NEMA-IEC phantom using six spherical inserts (diameters from 10 to 37 mm) and a lung compartment. The phantom was filled with I and I solutions to known sphere-to-background concentration ratios. Spherical volumes of interest with the same diameter as the inserts were drawn on the images, and recovery coefficients for the spheres were calculated in addition to lung-to-background ratio. RESULTS: The new down-scatter compensation method provided higher recovery coefficients than the TEW scatter compensation or Gaussian convolution-based forced detection Monte Carlo algorithm for both isotopes. Background activity concentration could be accurately estimated with the new down-scatter compensation method and with the TEW scatter compensation, whereas activity concentration of the spheres was severely underestimated even with the new method. CONCLUSION: Down-scatter compensation with Monte Carlo-simulation effectively reduces down-scatter effects in I and I SPECT imaging.

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. A total of five hospitals and eight scanners (three GE scanners and five Siemens scanners) participated in the study. A Jaszczak phantom without inserts was used to calculate counts to activity concentration conversion factors. The quantitative accuracy was tested using the NEMA-IEC phantom with six spherical inserts (diameters from 10 to 37 mm) filled to an 8 : 1 insert-background concentration ratio. Phantom studies were reconstructed at one central location using HERMES HybridRecon applying corrections for attenuation, collimator-detector response, and scatter. Spherical volumes of interest with the same diameter as the inserts were drawn on the images and recovery coefficients for the spheres were calculated. The coefficient of variation (CoV) of the NEMA-IEC phantom recovery coefficients ranged from ∼19 to 5% depending on the insert diameter so that the lowest CoV was obtained with the largest spheres. The intersite CoV was almost equal to intrasite CoV. In conclusion, quantitative SPECT is reproducible in a multicenter setting with 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. METHODS: Two slightly different implementations of reconstruction--reprojection-based motion correction techniques were optimised for effective, good-quality motion correction and then compared with each other. The first of these methods (Method 1) was the traditional reconstruction-reprojection motion correction algorithm, where the motion correction is done in projection space, whereas the second algorithm (Method 2) performed motion correction in reconstruction space. The parameters that were optimised include the type of cost function (squared difference, normalised cross-correlation and mutual information) that was used to compare measured and reprojected projections, and the number of iterations needed. The methods were tested with motion-corrupt projection datasets, which were generated by adding three different types of motion (lateral shift, vertical shift and vertical creep) to motion-free cardiac perfusion SPECT studies. RESULTS: Method 2 performed slightly better overall than Method 1, but the difference between the two implementations was small. The execution time for Method 2 was much longer than for Method 1, which limits its clinical usefulness. The mutual information cost function gave clearly the best results for all three motion sets for both correction methods. Three iterations were sufficient for a good quality correction using Method 1. CONCLUSIONS: The traditional reconstruction--reprojection-based method with three update iterations and mutual information cost function is a good option for motion correction in clinical myocardial perfusion SPECT.

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. Defect contrast, myocardium versus ventricle contrast and resolution were calculated. In addition to the simulation studies, full-time and half-time SPECT projection data of 30 patients were reconstructed with the standard and the new method. The patient data were qualitatively evaluated by four nuclear medicine experts on a scale from 1 (poor quality) to 5 (high quality). RESULTS: The new reconstruction method with half-time data produced higher contrast and better resolution in the simulations and also achieved higher qualitative scores in the patient study than the standard reconstruction with full-time data. CONCLUSION: Half-time myocardial perfusion imaging using the new reconstruction algorithm with Monte Carlo-based scatter correction produced images with superior quality when compared with full-time imaging with standard reconstruction.