CT system and principles of an image reconstruction algorithm
Data were acquired using an Aquilion Exceed LB (Canon Medical). This CT has a 90 cm wide bore and wide field of view (FOV) and is available for image reconstruction using DLR and H-IR.
AiCE uses artificial intelligence nodes called "neurons," which are networked in multiple layers to mimic human neuron connections. This creates a self-correcting algorithm. The engine was trained using a sample dataset containing both high- and low-quality input data compared to gold standard images, allowing the system to distinguish signal from noise and reconstruct superior signal-to-noise ratios with the same radiation dose as conventional scanning techniques.
The H-IR algorithm used in this study is Adaptive Iterative Dose Reduction (AIDR). AIDR is a three-dimensional CT algorithm that reduces image noise while preserving image quality[20, 21]. AIDR is a commercial H-IR algorithm that combines reconstruction and denoising in the raw data and image space domains, AIDR manipulates the projection data using noise and scanner statistical models to adjust for variations in the patient, scan parameters, and scanner itself, and adapts the filter intensity based on the relative noise levels.
Data acquisition and reconstruction parameters
The tube voltage was 120 kV, and the tube currents were 265, 200, 100, and 25 mA. The detector configuration was 0.5 mm x 80-rows (160-slices), the rotation time was 0.5 s/rotation, and the field-of-view was LL size (500 mm). The reconstruction kernel and reconstruction strength of the AIDR were the same as those used in clinical settings (reconstruction kernel: FC13, reconstruction strength: Mild). The reconstruction kernel for AiCE was body-sharp, and the reconstruction strength was compared with three parameters: Mild, Standard, and Strong. The scan parameters are presented in Table 1.
Table 1
Summary of scan parameter
X-ray tube voltage (kV) | 120 |
X-ray tube current (mA) | 265 / 200 / 100 / 25 |
Detector configuration | 0.5 mm x 80-raw (160-slices) |
Field-of-view | LL (500 mm) |
Reconstruction parameter | AIDR | FC13, Mild |
| AiCE | Body_sharp, Mild / Standard / Strong |
Phantom and data analysis
A large-diameter CT-ED table phantom (Advanced Electron Density Phantom; SUN NUCLEAR) was used to measure the CT values and image noise of the various materials. The rods of the advanced electron density phantom mimic water, cortical/inner bone, lung, and liver. They are highly equivalent to the medical standards for human tissue densities and can optimally convert CT values to electron density. Figure 5 shows an overview and analytical view of the phantom. In this study, 10 materials were used, ranging from the lung (electron density:0.288 c/cm3) to the cortical bone (electron density:1.774 c/cm3). Moreover, regions of interest (ROI) of mimicked water (electron density:0.999 c/cm3) were created at the top, bottom, left, and right sides for analysis. The ROI size used in the analysis was approximately 300 mm2, and the ROI was set at the center of each material. CT values and variations (SD) within the ROI were analyzed.