Liver Cirrhosis Clinical Trial
Official title:
Correlation of Ultrasound Based Measurements of Liver Stiffness and Steatosis With MRI
NCT number | NCT03342703 |
Other study ID # | 38649 |
Secondary ID | |
Status | Completed |
Phase | |
First received | |
Last updated | |
Start date | August 1, 2018 |
Est. completion date | December 31, 2020 |
Verified date | April 2021 |
Source | Stanford University |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
The investigators will assess the ability of ultrasound (US) to measure liver stiffness (cirrhosis) and liver fat content (steatosis).
Status | Completed |
Enrollment | 35 |
Est. completion date | December 31, 2020 |
Est. primary completion date | December 31, 2019 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: 1. participants who have a clinical indication for a standard of care MRI exam that included assessment of the liver 2. participant is at least 18 years of age Exclusion Criteria: 1. Participants unable to take part in the decision making process on whether to consent to the trial 2. Patients with previous chemoembolization or other focal liver therapies to the liver (* NOTE: for liver transplant patients, this criterion is only applicable to the transplanted liver) |
Country | Name | City | State |
---|---|---|---|
United States | Stanford University | Stanford | California |
United States | Stanford University Hospital | Stanford | California |
Lead Sponsor | Collaborator |
---|---|
Stanford University |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Discriminatory value (AUC) of US in assessing liver stiffness | Discriminatory value (the ability of the test to diagnose disease from healthy) will be calculated using nonparametric receiver operating characteristic (ROC) curve analysis. Sensitivity (i.e. true positive rate: the ability of a test to correctly identify patients with the disease being investigated) is plotted on the y axis and 1-specificity (i.e. false positive rate: the test incorrectly identifies patients who do not have the disease being investigated as having the disease) will be plotted on the x-axis. Cutoff points of US liver stiffness values will be chosen to create the graph of sensitivity versus 1-Specificity, i.e. the ROC curve, and the area under the curve (AUC) is used to determine how well US discriminates patients with liver stiffness from patients without liver stiffness.
The closer the AUC gets to 1, the more discriminatory the test. An AUC=0.5 is a test that is right 50% of the time, and is no better than flipping a coin. |
an estimated time of 30 minutes | |
Primary | Discriminatory value (AUC) of US in assessing liver fat content | Discriminatory value (the ability of the test to diagnose disease from healthy) will be calculated using nonparametric receiver operating characteristic (ROC) curve analysis. Sensitivity (i.e. true positive rate: the ability of a test to correctly identify patients with the disease being investigated) is plotted on the y axis and 1-specificity (i.e. false positive rate: the test incorrectly identifies patients who do not have the disease being investigated as having the disease) will be plotted on the x-axis. Cutoff points of US liver fat content values will be chosen to create the graph of sensitivity versus 1-specificity, i.e. the ROC curve, and the area under the curve (AUC) is used to determine how well US discriminates patients with liver fat content from patients without liver fat content.
The closer the AUC gets to 1, the more discriminatory the test. An AUC=0.5 is a test that is right 50% of the time, and is no better than flipping a coin. |
an estimated average of 30 minutes | |
Secondary | US Elastography Stiffness | MRI tissue stiffness is reported in shear modulus (S), while US uses Young's modulus (Y). Since Y = 2*(1+m)*S, where m is the Poisson's ratio for the material, and since that ratio is between 0.49 and 0.50 for tissue, the US measurements should be three times that of the MRI ones. In particular, treating the MRI measurements as the reference, theory predicts a linear relationship:
Y = 0 + 3*S which can be tested with a linear regression model. The most straightforward means is by calculating the expected Young's modulus values for US from the MR measurements, and regressing them on the observed US measurements. Both US and MRI values are given below. |
an estimated average of 30 minutes |
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