Background 99mTc–prostate-specific membrane antigen (PSMA) SPECT/CT is less expensive and readily available modality compared with 68Ga-PSMA PET/CT for imaging prostate cancer (PC). The aim of this study is to compare the value of these 2 modalities in patients confirmed or suspicious to have metastatic prostate cancer. Patients and Methods Twenty-two patients with the mean age of 66.6 ± 10.1 years were studied using 99mTc-PSMA SPECT/CT and 68Ga-PSMA PET/CT, with less than 7 days interval between the 2 imaging procedures. Whole-body PET/CT was done 60 minutes after IV injection of 185 MBq (5 mCi) of 68Ga-PSMA. 99mTc-PSMA SPECT/CT was performed 3 hours after IV injection of 555 to 740 MBq (15–20 mCi) of 99mTc-PSMA. The images of each modality were interpreted independently, and the results were compared according to patient-based as well as region-based analyses. Results In patient-based evaluation, both 99mTc-PSMA SPECT/CT and 68Ga-PSMA PET/CT scans were positive in 95.45% (21/22). In region-based evaluation, 68Ga-PSMA PET/CT detected 53 regions (median of 2 regions per patient; range, 0–5), whereas 43 (median of 2 regions per patient; range, 0–5) were detected by 99mTc-PSMA SPECT/CT. Most of these differences could be explained by lower detection rate of 99mTc-PSMA SPECT/CT in prostate bed (n = 6). PET/CT detected more involved regions than SPECT/CT (P = 0.007), whereas similar frequency of extraprostatic lesions were diagnosed in both modalities (P = 0.102). Significant correlation was also demonstrated between serum prostate-specific antigen level and imaging parameters of disease extension detected by 2 modalities. Conclusions 99mTc-PSMA SPECT/CT could be a potential substitute for 68Ga-PSMA PET/CT in high-risk patients, except when evaluation of prostate bed is of major concern.
NLDO may be considered as a side effect of I-131 therapy, especially with a cumulative dose of 11.1 GBq or more.
Purpose This work was set out to investigate the feasibility of dose reduction in SPECT myocardial perfusion imaging (MPI) without sacrificing diagnostic accuracy. A deep learning approach was proposed to synthesize full-dose images from the corresponding low-dose images at different dose reduction levels in the projection space. Methods Clinical SPECT-MPI images of 345 patients acquired on a dedicated cardiac SPECT camera in list-mode format were retrospectively employed to predict standard-dose from low-dose images at half-, quarter-, and one-eighth-dose levels. To simulate realistic low-dose projections, 50%, 25%, and 12.5% of the events were randomly selected from the list-mode data through applying binomial subsampling. A generative adversarial network was implemented to predict non-gated standard-dose SPECT images in the projection space at the different dose reduction levels. Well-established metrics, including peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and structural similarity index metrics (SSIM) in addition to Pearson correlation coefficient analysis and clinical parameters derived from Cedars-Sinai software were used to quantitatively assess the predicted standard-dose images. For clinical evaluation, the quality of the predicted standard-dose images was evaluated by a nuclear medicine specialist using a seven-point (− 3 to + 3) grading scheme. Results The highest PSNR (42.49 ± 2.37) and SSIM (0.99 ± 0.01) and the lowest RMSE (1.99 ± 0.63) were achieved at a half-dose level. Pearson correlation coefficients were 0.997 ± 0.001, 0.994 ± 0.003, and 0.987 ± 0.004 for the predicted standard-dose images at half-, quarter-, and one-eighth-dose levels, respectively. Using the standard-dose images as reference, the Bland–Altman plots sketched for the Cedars-Sinai selected parameters exhibited remarkably less bias and variance in the predicted standard-dose images compared with the low-dose images at all reduced dose levels. Overall, considering the clinical assessment performed by a nuclear medicine specialist, 100%, 80%, and 11% of the predicted standard-dose images were clinically acceptable at half-, quarter-, and one-eighth-dose levels, respectively. Conclusion The noise was effectively suppressed by the proposed network, and the predicted standard-dose images were comparable to reference standard-dose images at half- and quarter-dose levels. However, recovery of the underlying signals/information in low-dose images beyond a quarter of the standard dose would not be feasible (due to very poor signal-to-noise ratio) which will adversely affect the clinical interpretation of the resulting images.
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