Increased pixel noise and streak artifact reduce CT image quality and limit the potential for radiation dose reduction during CT of the thoracic inlet. We propose to quantify the pixel noise of mediastinal structures in the thoracic inlet, during low-dose (LDCT) and ultralow-dose (uLDCT) thoracic CT, and assess the utility of new software (quantum denoising system and BOOST3D) in addressing these limitations. Twelve patients had LDCT (120 kV, 25 mAs) and uLDCT (120 kV, 10 mAs) images reconstructed initially using standard mediastinal and lung filters followed by the quantum denoising system (QDS) to reduce pixel noise and BOOST3D (B3D) software to correct photon starvation noise as follows: group 1 no QDS, no B3D; group 2 B3D alone; group 3 QDS alone and group 4 both QDS and B3D. Nine regions of interest (ROIs) were replicated on mediastinal anatomy in the thoracic inlet, for each patient resulting in 3456 data points to calculate pixel noise and attenuation. QDS reduced pixel noise by 18.4% (lung images) and 15.8% (mediastinal images) at 25 mAs. B3D reduced pixel noise by ∼8% in the posterior thorax and in combination there was a 35.5% reduction in effective radiation dose (E) for LDCT (1.63-1.05 mSv) in lung images and 32.2% (1.55-1.05 mSv) in mediastinal images. The same combination produced 20.7% reduction (0.53-0.42 mSv) in E for uLDCT, for lung images and 17.3% (0.51-0.42) for mediastinal images. This quantitative analysis of image quality confirms the utility of dedicated processing software in targeting image noise and streak artifact in thoracic LDCT and uLDCT images taken in the thoracic inlet. This processing software potentiates substantial reductions in radiation dose during thoracic LDCT and uLDCT.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging