Single-photon emission computed tomography (SPECT) is still considered a nonquantitative imaging modality because it cannot perform attenuation correction. To acquire a quantitative SPECT image, Beijing Novel Medical Equipment Co., Ltd. developed a domestic SPECT/CT system, Insight NM/CT Pro. It was equipped with dual digital detectors and enabled various scanning geometries. In addition to better spatial resolution, the system can correct attenuation effects in SPECT and realize quantitative reconstruction using CT. In this study, we evaluated the imaging accuracy of this domestic SPECT/CT system and compared it with advanced abroad systems.

To obtain quantitatively correct results, physical effects, including collimator blurring, object attenuation, scatter, and radionuclide decay, were modeled and corrected in the reconstruction algorithm. Moreover, a large cylindrical phantom was employed to obtain the calibration factor for the system so that we could convert the reconstruction result to a quantitative image in terms of Bq/mL. Then, the performance of CT-based attenuation correction was tested according to testing method for SPECT imaging based on CT-attenuation correction (YY/T 1546—2017). A cylinder phantom with three cylindrical inserts corresponding to air, nonradioactive water, and bone was filled with a radioactive solution for imaging. The biases inside the air, water, and bone regions of the reconstructed image were calculated to evaluate the performance of CT-based attenuation correction. In addition, the quantitative accuracy of the equipment was tested using the Notional Electrical Manufactures Association (NEMA) torso phantom according to performance measurements of Gamma cameras (NEMA NU 1—2018). Six fillable spheres with different diameters were set as targets for recovery evaluation, and the target-to-background concentration ratio was approximately 8∶1. A large volume of interest (VOI) was placed in the background region to calculate the quantitative bias of the reconstruction. VOIs with the same size of six spheres were drawn based on the registered CT to evaluate recovery coefficients of different sizes. Radionuclide technetium-99m and a low-energy, high-resolution collimator with Insight NM/CT Pro were used for all these tests, and the evaluation results were compared with those of the GE Discovery NM/CT 670.

For attenuation accuracy testing, the biases inside the air, water, and bone regions of Insight NM/CT Pro were 7.84%, 8.38%, and 4.66%, respectively, whereas the corresponding biases in GE Discovery NM/CT 670 were 16.64%, 18.01%, and 11.02%, respectively. For quantitative accuracy testing, in GE discovery NM/CT 670, the quantitative recovery coefficients of the hot spheres with diameters of 13, 17, 22, and 28 mm were 31.04%, 51.36%, 59.91%, and 66.39%, respectively, and the background concentration bias was 10.84%. Insight NM/CT Pro achieved higher recovery coefficients and lower bias. The recovery coefficients were 38.22%, 50.98%, 66.55%, and 71.32% for 13, 17, 22, and 28 mm hot rods, respectively, and the bias in the background region was 7.95%.

Phantom studies have demonstrated that the domestic Insight NM/CT Pro imaging system can obtain smaller biases after CT attenuation correction and achieve quantitative images with high accuracy. The reliability of the Insight NM/CT Pro system for quantitative imaging is validated in this study, and its performance is comparable to that of the advanced GE Discovery NM/CT 670 imaging system.

Iodine-131 SPECT (single photon emission computed tomography) planar imaging has been widely used in the clinical diagnosis and treatment evaluation of thyroid cancer. Because of the high-energy emissions of iodine-131, the photons have a high probability of penetrating the collimator septa of SPECT, causing "spoke" artifacts in the final result. The "spoke" artifacts make it difficult to distinguish accurate concentration regions of iodine-131, and they may o b scure lower uptake regions nearby, such as metastatic spread to lymph nodes. In this paper, a deconvolution method based on the point spread function was com b ined with a priori regularization to suppress the spoke artifacts and to improve the diagnostic accuracy in clinical studies.

This study is based on the NET632 SPECT system with the corresponding high-energy general purpose collimator. The collected data follow the Poisson distribution, and they consist of two parts, a forward projection of the true activity distribution and the scatter data. The forward projection progress can be well modeled using a shift-invariant PSF (point spread function). An objective function is built based on the aforementioned approximation, and a priori function is introduced to regularize the reconstruction. A monotonic and convergent algorithm is derived to iteratively solve the o b jective function. In contrast, the conventional deconvolution method regularizes the solution using a total variation term, and the ob jective function is optimized based on the "one-step-late" algorithm; thus, nonnegativity and convergence can not be guaranteed. The triple-energy window method is employed to estimate scattering data, and PSFs of different sizes are generated based on Monte Carlo simulations. Simulated NEMA torso phantom data are reconstructed with different parameters to validate the monotonicity and convergence of the proposed method. Moreover, the dataset is also used to evaluate the effects of PSF size and regularization strength on reconstruction images. Normalized spoke counts and background noise are calculated for quantitative comparison. Simulation data are also used to compare the reconstruction performance of the proposed method and the conventional deconvolution method. With the optimized parameters determined by simulation data, the proposed method is further validated by clinical point data and volunteer data.

With different reconstruction parameters, the objective function value increased monotonically, and the image differences between two adjacent iterations rapidly reduced to a value close to zero. The simulation study also demonstrated that a 127×127 PSF size could provide performance similar to a 255×255 PSF size, which was significantly better than 63×63 and 31×31 PSF sizes. A study on different regularization strengths suggested an optimized regularization parameter, 0.01. When the PSF size and regularization parameter were set as 127×127 and 0.01, the mean spoke counts could be reduced to 4% of the original value with a low background noise level. A comparison study based on simulation data showed the superiority of the proposed method over the conventional deconvolution method. The clinical point data and volunteer data also validated the performance of the proposed method, and the mean spoke counts could be reduced to 35% and 28% of the original values, respectively.

The proposed method suppresses the spoke artifacts in iodine-131 imaging using a PSF that models the physical response, and it also introduces a priori regularization to suppress noise amplified by deconvolution. The derived algorithm can guarantee the monotonicity and convergence of the iterative reconstruction. Studies on simulation data and clinical data have demonstrated that the proposed method can achieve the desired performance and is expected to improve the diagnostic accuracy in clinical studies.