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| Name | Class |
|---|---|
| Samsung Medison | INDUSTRY |
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The purpose of this study is to investigate the diagnostic performance of quantitative ultrasound imaging parameter for the assessment of hepatic steatosis in patients with non-alcoholic fatty liver disease using magnetic resonance imaging proton density fat fraction (MRI-PDFF) and MR spectroscopy as the reference standard.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Quantitative ultrasound imaging parameter | Experimental | Quantitative ultrasound imaging parameter (QUS) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Quantitative ultrasound imaging parameter (QUS) | Diagnostic Test | Quantitative ultrasound imaging parameters (QUS) are analyzed to evaluate hepatic steatosis |
|
| Measure | Description | Time Frame |
|---|---|---|
| Correlation between quantitative US imaging parameter (QUS) and MR fat fraction | reference standard: MR spectroscopy or MRI-proton density fat fraction value | 3 months |
| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic performance of QUS to detect mild fatty liver and moderate fatty liver | reference standard: MR fat fraction | 3 months |
| Correlation between S-shearwave elastography and MR elastography |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Jeon Min Lee | Seoul National University Hospital | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Seoul National University Hospital | Seoul | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36594835 | Derived | Jeon SK, Lee JM, Joo I, Yoon JH, Lee G. Two-dimensional Convolutional Neural Network Using Quantitative US for Noninvasive Assessment of Hepatic Steatosis in NAFLD. Radiology. 2023 Apr;307(1):e221510. doi: 10.1148/radiol.221510. Epub 2023 Jan 3. |
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| ID | Term |
|---|---|
| D005234 | Fatty Liver |
| ID | Term |
|---|---|
| D008107 | Liver Diseases |
| D004066 | Digestive System Diseases |
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Reference standard: liver stiffness at MR elastography, using Pearson's correlation analysis or Spearman rank correlation analysis
| 3 months |
| Intra-observer agreement of quantitative ultrasound imaging parameter | intraclass correlation coefficient (ICC) | same 1 day |
| Development and validation of deep learning model for prediction of hepatic steatosis | ROC analysis and C-index for deep learning model for prediction of hepatic steatosis | 1 month |