  Clinical SPECT-MPI images of 345 patients acquired from a dedicated cardiac
SPECT in list-mode format were retrospectively employed to predict normal-dose
images from low-dose data at the half, quarter, and one-eighth-dose levels. A
generative adversarial network was implemented to predict non-gated normal-dose
images in the projection space at the different reduced dose levels.
Established metrics including the peak signal-to-noise ratio (PSNR), root mean
squared error (RMSE), and structural similarity index metrics (SSIM) in
addition to Pearson correlation coefficient analysis and derived parameters
from Cedars-Sinai software were used to quantitatively assess the quality of
the predicted normal-dose images. For clinical evaluation, the quality of the
predicted normal-dose images was evaluated by a nuclear medicine specialist
using a seven-point (-3 to +3) grading scheme. By considering PSNR, SSIM, and
RMSE quantitative parameters among the different reduced dose levels, the
highest PSNR (42.49) and SSIM (0.99), and the lowest RMSE (1.99) were obtained
at the half-dose level in the reconstructed images. Pearson correlation
coefficients were measured 0.997, 0.994, and 0.987 for the predicted
normal-dose images at the half, quarter, and one-eighth-dose levels,
respectively. Regarding the normal-dose images as the reference, the
Bland-Altman plots sketched for the Cedars-Sinai selected parameters exhibited
remarkably less bias and variance in the predicted normal-dose images compared
with the low-dose data at the entire reduced dose levels. Overall, considering
the clinical assessment performed by a nuclear medicine specialist, 100%, 80%,
and 11% of the predicted normal-dose images were clinically acceptable at the
half, quarter, and one-eighth-dose levels, respectively.
