Clinical trial · Observational
Liver CT Dose Reduction With Deep Learning Based Reconstruction
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
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Liver Cancer | Malignant Liver Neoplasm | CURATED_EXACT | 0.92 |
| Radiation Exposure | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Contrast-enhanced liver CT scan | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- 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.
- interventionNames
- Diagnostic Test: Contrast-enhanced liver CT scan
Primary outcomes (1)
- measure
- Measurement of standard deviation of CT attenuation values at the liver
- timeFrame
- within 6 months from acquisition of liver CT scans
- description
- Standard deviation of CT attenuation values at the liver parenchyma
Secondary outcomes (1)
- measure
- Sensitivity to detect malignant liver tumor
- timeFrame
- within 6 months from acquisition of liver CT scans
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 20 Years
- Maximum age
- 85 Years
Show eligibility criteria text
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.
References
Publications (1)
- DERIVEDLee DH, Lee JM, Lee CH, Afat S, Othman A. Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT. Radiol Artif Intell. 2024 Mar;6(2):e230192. doi: 10.1148/ryai.230192. PMID 38231025