Liver CT Dose Reduction With Deep Learning Based Reconstruction

Sponsor

Seoul National University Hospital (Other)

Overall Status

Completed

CT.gov ID

NCT05804799

Collaborator

(none)

300

Enrollment

Locations

Actual Duration (Months)

100

Patients Per Site

4.2

Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease	Intervention/Treatment	Phase
Radiation Exposure Liver Cancer	Diagnostic Test: Contrast-enhanced liver CT scan

Detailed Description

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.

Study Design

Study Type:

Observational [Patient Registry]

Actual Enrollment :

300 participants

Observational Model:

Cohort

Time Perspective:

Prospective

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

Actual Study Start Date :

Jan 1, 2021

Actual Primary Completion Date :

Aug 31, 2022

Actual Study Completion Date :

Dec 31, 2022

Arms and Interventions

Arm	Intervention/Treatment
Liver CT study group 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.	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.

Arm

Intervention/Treatment

Liver CT study group

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.

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.

Outcome Measures

Primary Outcome Measures

Measurement of standard deviation of CT attenuation values at the liver [within 6 months from acquisition of liver CT scans]
Standard deviation of CT attenuation values at the liver parenchyma

Secondary Outcome Measures

Sensitivity to detect malignant liver tumor [within 6 months from acquisition of liver CT scans]
Sensitivity of liver CT scans to detect malignant liver tumor

Eligibility Criteria

Criteria

Ages Eligible for Study:

20 Years to 85 Years

Sexes Eligible for Study:

All

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.

Contacts and Locations

Locations

	Site	City	Country	Postal Code
1	Tubingen University Hospital	Tubingen	Germany	72076
2	Seoul National University Hospital	Seoul	Korea, Republic of	03080
3	Korea University Guro Hospital	Seoul	Korea, Republic of	08308

Sponsors and Collaborators

Seoul National University Hospital

Investigators

Principal Investigator: Jeong Min Lee, M.D., Seoul National University Hospital

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Jeong Min Lee, Professor, Seoul National University Hospital

ClinicalTrials.gov Identifier:

NCT05804799

Other Study ID Numbers:

SNUH-2007-040-1139

First Posted:

Apr 7, 2023

Last Update Posted:

Apr 12, 2023

Last Verified:

Apr 1, 2023

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Yes

Product Manufactured in and Exported from the U.S.:

Additional relevant MeSH terms:

Liver Neoplasms

Study Results

No Results Posted as of Apr 12, 2023