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Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a
André Euler1, Bram Stieltjes1, Zsolt Szucs-Farkas2
1Clinic of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland.
Objectives:
To evaluate the impact of model-based iterative reconstruction (MBIR) on image quality and low-contrast lesion detection compared with filtered back projection (FBP) in abdominal computed tomography (CT) of simulated medium and large patients at different tube voltages.
Methods:
A phantom with 45 hypoattenuating lesions was placed in two water containers and scanned at 70, 80, 100, and 120 kVp. The 120-kVp protocol served as reference, and the volume CT dose index (CTDIvol) was kept constant for all protocols. The datasets were reconstructed with MBIR and FBP. Image noise and contrast-to-noise-ratio (CNR) were assessed. Low-contrast lesion detectability was evaluated by 12 radiologists.
Results:
MBIR decreased the image noise by 24% and 27%, and increased the CNR by 30% and 29% for the medium and large phantoms, respectively. Lower tube voltages increased the CNR by 58%, 46%, and 16% at 70, 80, and 100 kVp, respectively, compared with 120 kVp in the medium phantom and by 9%, 18% and 12% in the large phantom. No significant difference in lesion detection rate was observed (medium: 79-82%; large: 57-65%; P > 0.37).
Conclusions:
Although MBIR improved quantitative image quality compared with FBP, it did not result in increased low-contrast lesion detection in abdominal CT at different tube voltages in simulated medium and large patients.
Key Points:
• MBIR improved quantitative image quality but not lesion detection compared with FBP. • Increased CNR by low tube voltages did not improve lesion detection. • Changes in image noise and CNR do not directly influence diagnostic accuracy.