A Liver Phantom Study: CT Radiation Dose Reduction and Different Image Reconstruction Algorithms Affect Diagnostic...

Area of Science:

• Radiology
• Medical Imaging
• Image Reconstruction

Background:

• Liver lesion detection is crucial in medical imaging.
• Iterative reconstruction techniques offer potential for improving image quality and diagnostic accuracy.
• Optimizing dose levels and tube potential is essential for balancing image quality and radiation exposure.

Purpose of the Study:

• To evaluate the impact of iterative reconstruction algorithms on liver lesion detectability.
• To assess the effects of varying dose levels (CTDIvol) and tube potentials (kVp) on lesion detection.
• To compare the performance of filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR), and model-based iterative reconstruction (Veo).

Main Methods:

• An anthropomorphic liver phantom was scanned using different dose levels (2.6-15 mGy) and tube potentials (80-120 kVp).
• Images were reconstructed using FBP, ASiR 40%, and Veo algorithms.
• Four readers independently assessed lesion presence/absence, and areas under the receiver operating characteristic curve (AUC) were calculated.

Main Results:

• Veo significantly improved hyperdense liver lesion detectability compared to FBP and ASiR 40% across most tested dose levels (P < 0.05).
• Veo also enhanced detectability at reduced tube potentials (5 mGy) compared to FBP and ASiR 40% (P < 0.05).
• ASiR 40% showed improvement over FBP only at lower dose levels (7.5 and 2.6 mGy at 120 kVp); reduced tube potential generally decreased lesion detectability.

Conclusions:

• Iterative reconstruction algorithms, particularly Veo, enhance liver lesion detectability in phantom studies.
• Aggressive dose reduction can compromise image quality, necessitating careful parameter selection.
• The impact of reduced tube potential on lesion detectability is variable, requiring cautious application.