# New-Generation ASiR-V for Dose Reduction While Maintaining Image Quality in CT: A Phantom Study
## 4 Discussion  
The use of ionizing radiation in medical imaging is associated with a risk of cancer, however small, and should therefore be subject to safety standards and optimization. In recent decades, technological progress has offered the possibility to reduce the radiation  
Figure 5: Comparison of Catphan 600 phantom slices used for quantitative MTF analysis for the different reconstruction algorithms, noise index values, and blending percentages. Figure 6: The 50% MTF as a function of various reconstruction methods measured using the Catphan 600 phantom. dose from medical exposure, with the international literature mostly focusing on CT due to having higher doses than other X-ray techniques. The main instrument for dose reduction is represented by the optimization of examinations and techniques. As a general rule, the optimization principle should be applied on an individual basis with the goal of obtaining an acceptable image quality that can ensure an accurate diagnosis with the least amount of radiation exposure to the patient. One of the most important factors affecting CT image quality, diagnostic accuracy, and the outcome of a CT scan is radiation dose. On the one hand, increasing the CT dose results in images with less noise and fewer streak artifacts (although not always with more diagnostic information). On the other hand, radiation dose should only be reduced if the diagnostic image quality is not compromised. In addition, reduced-dose CT can be achieved by varying the scanning parameters (tube potential/current, pitch, and rotation time). In this scenario, image reconstruction algorithms may play a key role in improving or maintaining image quality in reduced-dose CT. In the past, the first commercial CT scanners relied on FBP for image reconstruction because it was quicker and easier to implement since it made fewer assumptions about the image chain. All projections are equally weighted in FBP, which offers a quick analytical solution to the reconstruction process. However, when dose levels are reduced, FBP is more likely to produce inadequate image quality. For almost 30 years, FBP was the industry standard. However, its performance has been hindered by the need to lessen radiation exposure while enhancing spatial and temporal resolution. To address such issues, scanner manufacturers have introduced iterative reconstruction algorithms to the market. In order to independently reduce noise and preserve resolution and image quality, IR methods use statistical and geometric models to variably weight the image data in a process that can be solved iteratively. Today, IR algorithms represent the primary technique in image reconstruction, providing the possibility to implement low-dose protocols without compromising diagnostic quality [24; 32; 33]. Although IR algorithms were first used in clinical settings in 2009, this was actually a revival of an older technology due to improvements in computer computational power. To iterate various elements of the image reconstruction algorithm, different vendors have developed various algorithmic approaches. All iterative reconstruction algorithms, however, work toward the same goal of generating lower noise and higher resolution while preserving edges and minimizing artifacts. By lowering some scanning parameters, such as tube current or even tube potential, reduced-dose CT can be used thanks to an essential feature of IR techniques. Previous research has shown that applications of IR techniques in a clinical setting can result in lower doses on the order of 20-40%, compared with a standard FBP reconstruction algorithm reconstruction for most exams [34]. According to a previous ASiR-V white paper [35], the dose reduction achievable with this algorithm is close to 82%, with respect to FBP. Regarding ASiR images, previous research [36] has shown that a reduction in radiation dose to 36% compared with FBP is possible when abdominal CT images are reconstructed with ASiR.