IQ-SPECT is an advanced high-speed SPECT modality for myocardial perfusion imaging (MPI), which uses a multi-focus fan beam collimator with resolution recovery reconstruction. The aim of this study was to compare IQ-SPECT with conventional SPECT in terms of performance, based on standard clinical protocols. In addition, we examined the concordance between conventional and IQ_SPECT in patients with coronary artery disease (CAD).Fifty-three patients, undergoing rest-gated MPI for the evaluation of known or suspected CAD, were enrolled in this study. In each patient, conventional SPECT ((99m)Tc-tetrofosmin, 9.6 min and (201)Tl, 12.9 min) was performed, immediately followed by IQ-SPECT, using a short acquisition time (4.3 min for (99m)Tc-tetrofosmin and 6.2 min for (201)Tl). A quantitative analysis was performed on an MPI polar map, using a 20-segment model of the left ventricle. An automated analysis by gated SPECT was carried out to determine the left ventricular volume and function including end-diastolic volume (EDV), end-systolic volume (ESV), and left ventricular ejection fraction (LVEF). The degree of concordance between conventional SPECT and IQ-SPECT images was evaluated according to linear regression and Bland-Altman analyses.The segmental percent uptake exhibited a significant correlation between IQ-SPECT and conventional SPECT (P<0.05). The mean differences in (99m)Tc-tetrofosmin studies were 1.1±6.6% (apex), 2.8±5.7% (anterior wall), 2.9±6.2% (septal wall), 4.9±6.7% (lateral wall), and 1.8±5.6% (inferior wall). Meanwhile, regarding the (201)Tl-SPECT studies, these values were 1.6±6.9%, 2.0±6.6%, 2.1±5.9%, 3.3±7.2%, and 2.4±5.8%, respectively. Although the mean LVEF in IQ-SPECT tended to be higher than that observed in conventional SPECT (conventional SPECT=64.8±11.8% and IQ-SPECT=68.3±12.1% for (99m)Tc-tetrofosmin; conventional SPECT= 56.0±11.7% and IQ-SPECT=61.5±12.2% for (201)Tl), quantitative parameters were not significantly different between IQ-SPECT and conventional SPECT.According to the (99m)Tc-tetrofosmin and (201)Tl protocols, IQ-SPECT images were comparable to and in agreement with conventional SPECT images. Our results suggest that IQ-SPECT is a useful technology for MPI SPECT, and can lead to an increase in scan efficiency and patient comfort.
Brain perfusion single-photon emission computed tomography (SPECT) image quality varies depending on SPECT systems. This study aimed to evaluate the relationship between physical parameters and visual analysis for assessment of the brain SPECT image quality. We conducted our phantom study under various conditions in a multi-center and multi-vendor study.
2607 Objectives The purpose of this study was to investigate the quality and accuracy of low-dose CT attenuation correction on PET image by CT iterative reconstruction method (CTIR) compared with filtered back-projection (FBP) using obesity-simulated phantom. Methods The obesity-simulated body phantom (400-mm diameter) filled with 18F-FDG solution was used for investigation. The CT tube voltage and current used were as follows: voltages 80, 100, and 120kVp, current 20, 40, 60, 100, 150, and 200mA. All CT images were reconstructed with FBP and CTIR, and attenuation correction maps were generated by CT with FBP and CTIR. Mean and standard deviation (SD) of the CT Hounsfield units (HU) were calculated in the ROIs. The linear attenuation coefficients and radioactivity concentrations were evaluated for the adequacy of PET attenuation correction using CT with CTIR. Results The change of HU values showed no significant difference between FBP images and CTIR images, whereas SD values were lower in CTIR images than in FBP images (decrease of 23-34%). As the tube voltage and current of CT shrank, the linear attenuation coefficient was significantly decreased, but it was coincident with true values by using CTIR reconstruction (FBP: 0.092cm-1; CTIR: 0.094cm-1). The radioactivity concentrations in CTIR-corrected images were minimally lower than those in FBP-corrected images, and the difference was calculated to be 1.9%. Conclusions Our study showed that CT iterative reconstruction improved accuracy of attenuation maps as a result of noise reduction in low-dose CT images. Use of CT iterative reconstruction would prove beneficial in low-dose CT attenuation correction, particularly in obese patients.
Abstract Purpose Given the potential risk of motion artifacts, acquisition time reduction is desirable in pediatric 99m Tc‐dimercaptosuccinic acid (DMSA) scintigraphy. The aim of this study was to evaluate the performance of predicted full‐acquisition‐time images from short‐acquisition‐time pediatric 99m Tc‐DMSA planar images with only 1/5th acquisition time using deep learning in terms of image quality and quantitative renal uptake measurement accuracy. Methods One hundred and fifty‐five cases that underwent pediatric 99m Tc‐DMSA planar imaging as dynamic data for 10 min were retrospectively collected for the development of three deep learning models (DnCNN, Win5RB, and ResUnet), and the generation of full‐time images from short‐time images. We used the normalized mean squared error (NMSE), peak signal‐to‐noise ratio (PSNR), and structural similarity index metrics (SSIM) to evaluate the accuracy of the predicted full‐time images. In addition, the renal uptake of 99m Tc‐DMSA was calculated, and the difference in renal uptake from the reference full‐time images was assessed using scatter plots with Pearson correlation and Bland–Altman plots. Results The predicted full‐time images from the deep learning models showed a significant improvement in image quality compared to the short‐time images with respect to the reference full‐time images. In particular, the predicted full‐time images obtained by ResUnet showed the lowest NMSE (0.4 [0.4−0.5] %) and the highest PSNR (55.4 [54.7−56.1] dB) and SSIM (0.997 [0.995−0.997]). For renal uptake, an extremely high correlation was achieved in all short‐time and three predicted full‐time images ( R 2 > 0.999 for all). The Bland–Altman plots showed the lowest bias (−0.10) of renal uptake in ResUnet, while short‐time images showed the lowest variance (95% confidence interval: −0.14, 0.45) of renal uptake. Conclusions Our proposed method is capable of producing images that are comparable to the original full‐acquisition‐time images, allowing for a reduction of acquisition time/injected dose in pediatric 99m Tc‐DMSA planar imaging.
Purpose: We conducted a field survey about pediatric nuclear medicine. As a result, it was suggested that 99mTc-DMSA scintigraphy was performed at many institutions, whereas various examinations such as image acquisition and processing are not carried out using the renal phantom. Therefore, we developed the body phantom for the evaluation of appropriate administered radioactivities and image quality with renal scintigraphy in pediatric nuclear medicine. Methods: We created three differently sized body phantoms (1-, 5-, and 20-year-old models). These pediatric body phantoms were filled with a 99mTc solution based on the consensus guideline of pediatric radiopharmaceutical administered radioactivity in Japan. The planar image was evaluated using acquisition count, uniformity and defect contrast. SPECT images were evaluated with a recovery coefficient (RC). Results: The acquisition counts for pediatric body phantoms were relatively corresponded to the clinical study. The appropriate acquisition counts and the pixel size for the planar image were approximately 140 counts per pixel and 1.23–1.35 mm at 5 min acquisition times in 1- and 5-year-old pediatric body phantom studies, respectively. Although the uniformity and the cold contrast did not depend on pixel size and body size, the cold contrast was affected by body size. The RC for SPECT images depended on the performance of SPECT systems, the resolution recovery algorithm and body phantom size. Conclusion: The developed pediatric body phantom could allow us to establish optimal image acquisition and more evidence on renal scintigraphy in pediatric nuclear medicine.
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