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Comparative Study
. 2013 Mar;86(1023):20120500.
doi: 10.1259/bjr.20120500. Epub 2013 Feb 7.

Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT

K L Dobeli  1 , S J Lewis, S R Meikle, D L Thiele, P C Brennan
Affiliations
Comparative Study

Noise-reducing algorithms do not necessarily provide superior dose optimisation for hepatic lesion detection with multidetector CT

K L Dobeli et al. Br J Radiol. 2013 Mar.

Abstract

Objective: To compare the dose-optimisation potential of a smoothing filtered backprojection (FBP) and a hybrid FBP/iterative algorithm to that of a standard FBP algorithm at three slice thicknesses for hepatic lesion detection with multidetector CT.

Methods: A liver phantom containing a 9.5-mm opacity with a density of 10 HU below background was scanned at 125, 100, 75, 50 and 25 mAs. Data were reconstructed with standard FBP (B), smoothing FBP (A) and hybrid FBP/iterative (iDose(4)) algorithms at 5-, 3- and 1-mm collimation. 10 observers marked opacities using a four-point confidence scale. Jackknife alternative free-response receiver operating characteristic figure of merit (FOM), sensitivity and noise were calculated.

Results: Compared with the 125-mAs/5-mm setting for each algorithm, significant reductions in FOM (p<0.05) and sensitivity (p<0.05) were found for all three algorithms for all exposures at 1-mm thickness and for all slice thicknesses at 25 mAs, with the exception of the 25-mAs/5-mm setting for the B algorithm. Sensitivity was also significantly reduced for all exposures at 3-mm thickness for the A algorithm (p<0.05). Noise for the A and iDose(4) algorithms was approximately 13% and 21% lower, respectively, than for the B algorithm.

Conclusion: Superior performance for hepatic lesion detection was not shown with either a smoothing FBP algorithm or a hybrid FBP/iterative algorithm compared with a standard FBP technique, even though noise reduction with thinner slices was demonstrated with the alternative approaches.

Advances in knowledge: Reductions in image noise with non-standard CT algorithms do not necessarily translate to an improvement in low-contrast object detection.

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Figures

Figure 1.
Figure 1.
An image of the phantom through the midline of the opacities. The opacity under investigation is indicated (arrow).
Figure 2.
Figure 2.
An edited image containing a pasted opacity (arrow).
See this image and copyright information in PMC

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