Abstract
Assessment of image noise is a relevant issue in computed tomography (CT). Noise is routinely measured by the standard deviation of density values (Hounsfield units, HU) within a circular region of interest (ROI). We explored the effect of a spherical volume of interest (VOI) on noise measurements. Forty-nine chronic obstructive pulmonary disease patients underwent CT with clinical protocol (regular dose [RD], volumetric CT dose index [CTDIvol] 3.04 mGy, 64-slice unit), and ultra-low dose (ULD) protocol (median CTDIvol 0.38 mGy, dual-source unit). Noise was measured in 27 1-cm2 ROIs and 27 0.75-cm3 VOIs inside the trachea. Median true noise was 21 HU (range 17-29) for RD-CT and 33 HU (26-39) for ULD-CT. The VOI approach resulted in a lower mean distance between limits of agreement compared to ROI: 5.9 versus 10.0 HU for RD-CT (−40%); 4.7 versus 9.9 HU for ULD-CT (−53%). Mean systematic bias barely changed: −1.6 versus −0.9HU for RD-CT; 0.0 to 0.4HU for ULD-CT. The average measurement time was 6.8 s (ROI) versus 9.7 (VOI), independent of dose level. For chest CT, measuring noise with a VOI-based instead of a ROI-based approach reduces variability by 40-53%, without a relevant effect on systematic bias and measurement time.
Highlights
In computed tomography (CT) imaging, the call for dose reduction has led to ongoing efforts to mitigate the effects of increased noise
The range of true noise based on the trachea segmentation was 17−29 Hounsfield units (HU) for regular dose (RD)-CT and 26
In this study, we showed that a volume of interest (VOI)-based noise measurement approach significantly improves precision compared to a region of interest (ROI)-based approach, especially in CT scans with a higher intrinsic noise level, without a relevant trade-off in terms of measurement time
Summary
In computed tomography (CT) imaging, the call for dose reduction has led to ongoing efforts to mitigate the effects of increased noise. In chest CT, optimal representation of image noise may be obtained by segmenting the entire tracheobronchial tree lumen, and measuring the SD of this air. This is not feasible in most clinical software. The current clinical practice is to measure the SD in a 1-cm circular region of interest (ROI) inside the trachea [2, 4]. Accurate noise measurements are important for protocol optimization and quantification processes [5,6,7]. In emphysema quantification by CT lung densitometry, image noise may affect the threshold needed for reliable distinction between emphysema and normal lung tissue [2, 5]
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