Abstract
Abstract In this research computer tomography (CT) iterative reconstruction (IR) algorithms are investigated, specifically the impact of their statistical and model-based strength on image quality in low-dose lung screening CT protocols in comparison to filtered back projection (FBP). It has been probed whether statistical, model-based IR in conjunction with low-dose, and ultra-low-dose protocols are suitable for lungcancer screening. To this end, artificial lung nodules shaped as spheres and spicules made from material with calibrated Hounsfield units (HU) were attached on marked positions in the lung structure of an anthropomorphic phantom. Nodule positions were selected by distinguished radiologists. The phantom with nodules was scanned on a CT Scanner using standard high contrast (SHC), low-dose (LD) and ultra low-dose (ULD) protocol. For reconstruction FBP and the IR algorithm ADMIRE at three different strength levels were used. Volume CT dose index (CTDIvol) and dose-length product were recorded. Radiologists assessed subjective image quality using a six-point Likert scale by reading all image series in terms detectability of lung nodules. As a measurable objective image quality parameter signal-to-noise ratios (SNR) were investigated. The CTDIvol decreases by more than 70% for all protocols and nodules compared to diagnostic reference value for chest CT (p<0.00001). The evaluation of image quality parameters, i.e. SNR, indicates that LD and ULD protocols in conjunction with IR assert high quality lung-nodule detection. The results reveal that IR algorithm with moderate to high strength is an indispensable alternative to FBP in low-dose scanning, thus, potentially suitable for lung-tumour screening.
Highlights
Introduction and BackgroundThe Center for Cancer Registry Data predicted 33700 new cases of lung cancer among men and 22000 among women in Germany in 2018
According to the US Lung Cancer Screening Trial (NLST) in 2011, the low-dose computer tomography screening procedure could reduce the relative risk of dying of lung cancer in the risk group by 20%, which corresponds to an absolute risk reduction of 0.3% [1,2]
Britta König et al, Phantom study on iterative reconstruction for computer tomography (CT) lung-cancer screening mance with regard to the detection of lung nodes in low-dose CT are an incentive for a comparative investigation of objective and subjective image quality factors and diagnostic performance
Summary
Introduction and BackgroundThe Center for Cancer Registry Data predicted 33700 new cases of lung cancer among men and 22000 among women in Germany in 2018. High contrast CT scanning could be used in conjunction with low dose. Compared to FBP, the perception of ADMIRE reconstructed low-dose CT images is different and increases with increasing strength of the algorithm.
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