Comparing five different iterative reconstruction algorithms for computed tomography in an ROC study

• The purpose of this study was to evaluate lesion conspicuity achieved with five different iterative reconstruction techniques from four CT vendors at three different dose levels. Comparisons were made of iterative algorithm and filtered back projection (FBP) among and within systems. An anthropomorphic liver phantom was examined with four CT systems, each from a different vendor. CTDIvol levels of 5 mGy, 10 mGy and 15 mGy were chosen. Images were reconstructed with FBP and the iterative algorithm on the system. Images were interpreted independently by four observers, and the areas under the ROC curve (AUCs) were calculated. Noise and contrast-to-noise ratios (CNR) were measured. One iterative algorithm increased AUC (0.79, 0.95, and 0.97) compared to FBP (0.70, 0.86, and 0.93) at all dose levels (p < 0.001 and p = 0.047). Another algorithm increased AUC from 0.78 with FBP to 0.84 (p = 0.007) at 5 mGy. Differences at 10 and 15 mGy were not significant (p-values: 0.084-0.883). Three algorithms showed no difference in AUC compared to FBP (p-values: 0.008-1.000). All of the algorithms decreased noise (10-71 %) and improved CNR. Only two algorithms improved lesion detection, even though noise reduction was shown with all algorithms. aEuro cent Iterative reconstruction algorithms affected lesion detection differently at different dose levels. aEuro cent One iterative algorithm improved lesion detectability compared to filtered back projection. aEuro cent Three algorithms did not significantly improve lesion detectability. aEuro cent One algorithm improved lesion detectability at the lowest dose level.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

Keyword

Computed tomography

Image reconstruction

Radiological phantom

Liver

Publication and Content Type

art (subject category)

ref (subject category)