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NCT05804799 Clinical Trial

Liver CT Dose Reduction With Deep Learning Based Reconstruction

Liver Cancer Clinical Trial

Official title:
Comparison of Image Quality and Diagnostic Pefromance of Low Dose Liver CT With Deep Learning Reconstuction to Standard Dose CT: A Prospective Multicenter Non-inferiority Trial

Clinical Trial Details — Status: Completed

Administrative data
NCT number NCT05804799
Other study ID # SNUH-2007-040-1139
Secondary ID
Status Completed
Phase
First received
Last updated
Start date January 1, 2021
Est. completion date December 31, 2022

Study information
Verified date April 2023
Source Seoul National University Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Observational [Patient Registry]

Clinical Trial Summary

A deep learning-based de-noising (DLD) reconstruction algorithm (ClariCT.AI) has the potential to reduce image noise and improve image quality. This capability of the CliriCT.AI program might enable dose reduction for contrast-enhanced liver CT examination. In this prospective multicenter study, whether the ClariCT.AI program can reduce the noise level of low-dose contrast-enhanced liver CT (LDCT) data and therefore, can provide comparable image quality to the standard dose of contrast-enhanced liver CT (SDCT) images will be evaluated. The aim of this study is to compare image quality and diagnostic capability in detecting malignant tumors of LDCT with DLD to those of SDCT with MBIR using the predefined non-inferiority margin.

Description:

A deep learning-based de-noising (DLD) reconstruction algorithm (ClariCT.AI) has the potential to reduce image noise and improve image quality. This capability of the CliriCT.AI program might enable dose reduction for contrast-enhanced liver CT examination. In this prospective multicenter study, whether the ClariCT.AI program can reduce the noise level of low-dose contrast-enhanced liver CT (LDCT) data and therefore, can provide comparable image quality to the standard dose of contrast-enhanced liver CT (SDCT) images will be evaluated. The aim of this study is to compare image quality and diagnostic capability in detecting malignant tumors of LDCT with DLD to those of SDCT with MBIR using the predefined non-inferiority margin.

Recruitment information / eligibility
Status Completed
Enrollment 300
Est. completion date December 31, 2022
Est. primary completion date August 31, 2022
Accepts healthy volunteers
Gender All
Age group 20 Years to 85 Years
Eligibility Inclusion Criteria: - Age between 20-year-old and 85 years old - patients referred to the Radiology department to perform contrast-enhanced liver CT under the suspicion of focal liver lesions Exclusion Criteria: - patients with estimated glomerular filtration rate < 60 mL/min/1.73m2 - previous history of severe adverse reaction to iodinated contrast media.

Study Design

Related Conditions & MeSH terms

Intervention

Diagnostic Test:
• Contrast-enhanced liver CT scan
The contrast-enhanced liver CT scans were obtained from all of the participants. The liver CT images were reconstructed by both low-dose scans with a deep-learning-based denoising program (ClariCT.AI) and standard-dose scans with model-based iterative reconstruction.

Locations
Country Name City State
Germany Tubingen University Hospital Tubingen
Korea, Republic of Korea University Guro Hospital Seoul
Korea, Republic of Seoul National University Hospital Seoul

Sponsors (1)
Lead Sponsor Collaborator
Seoul National University Hospital

Countries where clinical trial is conducted

Germany,  Korea, Republic of, 

Outcome
Type Measure Description Time frame Safety issue
Primary Measurement of standard deviation of CT attenuation values at the liver Standard deviation of CT attenuation values at the liver parenchyma within 6 months from acquisition of liver CT scans
Secondary Sensitivity to detect malignant liver tumor Sensitivity of liver CT scans to detect malignant liver tumor within 6 months from acquisition of liver CT scans
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