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Spots Global Cancer Trial Database for Liver CT Dose Reduction With Deep Learning Based Reconstruction

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Trial Identification

Brief Title: Liver CT Dose Reduction With Deep Learning Based Reconstruction

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

Study ID: NCT05804799

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.

Detailed 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.

Keywords

Eligibility

Minimum Age: 20 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Tubingen University Hospital, Tubingen, , Germany

Seoul National University Hospital, Seoul, , Korea, Republic of

Korea University Guro Hospital, Seoul, , Korea, Republic of

Contact Details

Name: Jeong Min Lee, M.D.

Affiliation: Seoul National University Hospital

Role: PRINCIPAL_INVESTIGATOR

Useful links and downloads for this trial

Clinicaltrials.gov

Google Search Results

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