How Real Are Computed Tomography Low Dose Simulations? An Investigational In-Vivo Large Animal Study

Published:January 18, 2023DOI:


      CT low-dose simulation methods have gained significant traction in protocol development, as they lack the risk of increased patient exposure. However, in-vivo validations of low-dose simulations are as uncommon as prospective low-dose image acquisition itself. Therefore, we investigated the extent to which simulated low-dose CT datasets resemble their real-dose counterparts.

      Materials and Methods

      Fourteen veterinarian-sedated alive pigs underwent three CT scans on the same third generation dual-source scanner with 2 months between each scan. At each time, three additional scans ensued, with mAs reduced to 50%, 25%, and 10%. All scans were reconstructed using wFBP and ADMIRE levels 1-5. Matching low-dose datasets were generated from the 100% scans using reconstruction-based and DICOM-based simulations. Objective image quality (CT numbers stability, noise, and signal-to-noise ratio) was measured via consistent regions of interest. Three radiologists independently rated all possible dataset combinations per time point for subjective image quality (-1=inferior, 0=equal, 1=superior). The points were averaged for a semiquantitative score, and inter-rater-agreement was measured using Spearman's correlation coefficient. A structural similarity index (SSIM) analyzed the voxel-wise similarity of the volumes. Adequately corrected mixed-effects analysis compared objective and subjective image quality. Multiple linear regression with three-way interactions measured the contribution of dose, reconstruction mode, simulation method, and rater to subjective image quality.


      There were no significant differences between objective and subjective image quality of reconstruction-based and DICOM-based simulation on all dose levels (p≥0.137). However, both simulation methods produced significantly lower objective image quality than real-dose images below 25% mAs due to noise overestimation (p<0.001; SSIM≤89±3). Overall, inter-rater-agreement was strong (r≥0.68, mean 0.93±0.05, 95% CI 0.92-0.94; each p<0.001). In regression analysis, significant decreases in subjective image quality were observed for lower radiation doses (b ≤ -0.387, 95%CI -0.399 to -0.358; p<0.001) but not for reconstruction modes, simulation methods, raters, or three-way interactions (p≥0.103).


      Simulated low-dose CT datasets are subjectively and objectively indistinguishable from their real-dose counterparts down to 25% mAs, making them an invaluable tool for efficient low-dose protocol development.


      ADMIRE (Advanced Modeled Iterative Reconstruction), ALARA (As Low As Reasonably Achievable), BMI (Body Mass Index), CTDIvol (Computed Tomography Dose Index), DicomSIM (DICOM-based Low-Dose Simulations), DLP (Dose-length Product), ED (Effective Radiation dose), HU (Hounsfield Units), kV (denoting Tube Voltage), mAs (denoting Tube Current-Exposure Time Product), ReconSIM (Reconstruction-based Low-Dose Simulation), Scan (Reference Real Dose Datasets), SD (Standard Deviation), SSDE (Size-specific Dose Estimate), SSIM (Structural Similarity Index), SNR (Signal-to-Noise Ratio), wFBP (Weighted Filtered Back Projection)
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