Clinical trial NCT05804799: 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 type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Radiation Exposure
Liver Cancer
Lead sponsor: Seoul National University Hospital
Sponsor class: OTHER
First posted: 2023-04-07
Enrollment: 300
Sex: ALL
Minimum age (years): 20
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with a suspicion of focal liver lesions had the plan to do a contrast-enhanced liver CT scan.

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Measurement of standard deviation of CT attenuation values at the liver
timeFrame: within 6 months from acquisition of liver CT scans
Secondary outcomes:
measure: Sensitivity to detect malignant liver tumor
timeFrame: within 6 months from acquisition of liver CT scans
Other outcomes:
Locations:
city: Tubingen
country: Germany
facility: Tubingen University Hospital
city: Seoul
country: Korea, Republic of
facility: Seoul National University Hospital
city: Seoul
country: Korea, Republic of
facility: Korea University Guro Hospital
Study officials:
affiliation: Seoul National University Hospital
name: Jeong Min Lee, M.D.
role: PRINCIPAL_INVESTIGATOR
References: