A Feasibility Study of Pulmonary Nodule Detection by Ultralow-dose CT Withadaptive Statistical Iterative Reconstruction-V Technique

Lung cancer is the most common cancer in the world and characterized by the highest mortality rate. In 2016, 224000 new cases of lung cancer were reported in the United States, 60% of which were in the advanced stage. Compared to the overall 5-year survival rate of 18% for lung cancer, the 5-year survival rate for non-small cell lung cancer can be obviously improved to 80% with appropriate treatment in the early stage. Therefore, we believe lung cancer screening in the early stage to be significant. The National Lung Screening Trial in the United States has shown a relative risk reduction in death from lung cancer by 20% with low-dose computed tomography (LDCT) screening compared to that associated with plain-film chest radiography. The maximum radiation dose of LDCT recommended by guidelines is 3 mSv for small people(BMI≤30 kg/m2), which is far higher than that recommended for plain-film chest radiography, 0.03 to 0.1 mSv. In addition, a large number of indeterminate nodules need to be examined by follow-up evaluations with repeated LDCT to monitor for changes in diameter, which could result in an increase in the cumulative radiation dose that cannot be ignored. Hence, lung cancer screening with ultralow-dose CT (ULDCT) has attracted great attention from radiologists. In recent times, several strategies have been proposed to reduce the dose of ionizing radiation, including modification of tube potential and tube current and use of iterative reconstruction (IR). Reducing tube potential and tube current alone impairs image quality and lowers accuracies for radiologists. However, IR can obviously improve the image quality and reduce the noise at the same radiation exposure level, allowing for further reduction of the radiation dose.Recently, a new IR technique adaptive statistical iterative reconstruction-V (ASiR-V, GE Healthcare, USA) was developed. ASiR-V can increase noise reduction performance over the original IR technique even at lower doses and it has been widely applied in phantom and clinical studies. To the best of our knowledge, no data are available on ULDCT with ASiR-V for research on pulmonary nodules. Therefore, the purpose of this study was to investigate whether ULDCT with ASiR-V can be used for the detection and diameter measurement of pulmonary nodules at an extremely low dose comparable to those associated with plain-film chest radiography. Furthermore, mixed-effects logistic regression analysis was used to determine independent predictors for the sensitivity of pulmonary nodule detection to explore the application range of ULDCT in Chinese patients.