The purpose of this study is to investigate the image quality and clinical feasibility of double low-dose liver computed tomography using a deep-learning-based iodine contrast boosting algorithm in participants at high risk for hepatocellular carcinoma.
The purpose of this study is to investigate the image quality (CNR, subjective inage quality, vessel and lesion conspicuity) and clinical feasibility (rate of lesion detection) of double low-dose liver computed tomography using a deep-learning-based iodine contrast boosting algorithm in participants at high risk for hepatocellular carcinoma.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
68
Underwent liver CT with 30% lower radiation dose
Underwent liver CT without change of radiation.
Underwent liver CT 20% lower dose contrast media.
Seoul National University Hospital
Seoul, South Korea
Detection rate of solid focal lesion in liver
diagnostic performance
Time frame: 12 months after last patient's image work up
Quantitative image quality analysis
Contrast-to-Noise
Time frame: Immediate after study enrollement
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Underwent liver CT without change of contrast media doses.
Applied deep-learning based contrast boosting algorithms on acquired CT images