Abstract
ObjectiveTo evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm.MethodsForty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP), and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV), muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR) was calculated.ResultIn terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP.ConclusionCompared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.
Highlights
Several techniques, like automatic adjustment of tube current [1], reduced tube voltage [2], noise reduction filters [3] and a higher pitch [4] allowed radiologists to effectively diagnose diseases using lower radiation doses during computed tomography (CT) scans
Compared with filtered back-projection (FBP) and Adaptive statistical iterative reconstruction (ASIR), overall image quality and noise reduction were significantly improved by model-based iterative reconstruction (MBIR)
Like automatic adjustment of tube current [1], reduced tube voltage [2], noise reduction filters [3] and a higher pitch [4] allowed radiologists to effectively diagnose diseases using lower radiation doses during computed tomography (CT) scans. These techniques are limited by an increased noise and a degraded image quality when the radiation dose is too low, mostly due to the reconstruction algorithm used in most CT systems
Summary
Like automatic adjustment of tube current [1], reduced tube voltage [2], noise reduction filters [3] and a higher pitch [4] allowed radiologists to effectively diagnose diseases using lower radiation doses during computed tomography (CT) scans. These techniques are limited by an increased noise and a degraded image quality when the radiation dose is too low, mostly due to the reconstruction algorithm used in most CT systems. Subsequent phantom and patients studies showed that ASIR provides images that are suitable for diagnosis using low radiation doses [9,10,11,12,13]
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