4.7 Article

Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions

Journal

EUROPEAN RADIOLOGY
Volume 32, Issue 5, Pages 2865-2874

Publisher

SPRINGER
DOI: 10.1007/s00330-021-08380-0

Keywords

Multidetector computed tomography; Deep learning; Radiation dosage

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This study compared the overall image quality and lesion detectability between low-dose liver CT and standard-dose CT. The results showed that low-dose CT using deep learning denoising provided comparable overall image quality and lesion detectability to standard-dose CT.
Objectives To compare the overall image quality and detectability of significant (malignant and pre-malignant) liver lesions of low-dose liver CT (LDCT, 33.3% dose) using deep learning denoising (DLD) to standard-dose CT (SDCT, 100% dose) using model-based iterative reconstruction (MBIR). Methods In this retrospective study, CT images of 80 patients with hepatic focal lesions were included. For noninferiority analysis of overall image quality, a margin of - 0.5 points (scored in a 5-point scale) for the difference between scan protocols was pre-defined. Other quantitative or qualitative image quality assessments were performed. Additionally, detectability of significant liver lesions was compared, with 64 pairs of CT, using the jackknife alternative free-response ROC analysis, with noninferior margin defined by the lower limit of 95% confidence interval (CI) of the difference of figure-of-merit less than - 0.1. Results The mean overall image quality scores with LDCT and SDCT were 3.77 +/- 0.38 and 3.94 +/- 0.34, respectively, demonstrating a difference of - 0.17 (95% CI: - 0.21 to - 0.12), which did not cross the predefined noninferiority margin of - 0.5. Furthermore, LDCT showed significantly superior quantitative results of liver lesion contrast to noise ratio (p < 0.05). However, although LDCT scored higher than the average score in qualitative image quality assessments, they were significantly lower than those of SDCT (p < 0.05). Figure-of-merit for lesion detection was 0.859 for LDCT and 0.878 for SDCT, showing noninferiority (difference: - 0.019, 95% CI: - 0.058 to 0.021). Conclusion LDCT using DLD with 67% radiation dose reduction showed non-inferior overall image quality and lesion detectability, compared to SDCT. Key Points Low-dose liver CT using deep learning denoising (DLD), at 67% dose reduction, provided non-inferior overall image quality compared to standard-dose CT using model-based iterative reconstruction (MBIR). Low-dose CT using DLD showed significantly less noise and higher CNR lesion to liver than standard-dose CT using MBIR and demonstrated at least average image quality score among all readers, albeit with lower scores than standard-dose CT using MBIR. Low-dose liver CT showed noninferior detectability for malignant and pre-malignant liver lesions, compared to standarddose CT.

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