Liver CT Dose Reduction With Deep Learning Based Reconstruction

Seoul National University

Status: Completed

Conditions: Liver Cancer; Radiation Exposure

Treatments: Diagnostic Test: Contrast-enhanced liver CT scan

Study type: Observational

Funder types: Other

Identifiers

NCT05804799

SNUH-2007-040-1139

Details and patient eligibility

About

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.

Full 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.

Enrollment: 300 patients

Sex: All

Ages: 20 to 85 years old

Volunteers: No Healthy Volunteers

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.

Trial design

300 participants in 1 patient group

Liver CT study group

Description:

Patients with a suspicion of focal liver lesions had the plan to perform a contrast-enhanced liver CT scan. 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.

Treatment:

Diagnostic Test: Contrast-enhanced liver CT scan