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
• Status: Completed
• 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
• 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
• 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.

Related Conditions & MeSH terms

• Liver Cancer
• Liver Neoplasms
• Radiation Exposure

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