Non-Alcoholic Fatty Liver Disease Clinical Trial
Official title:
Investigation of the Electrical Impedance Tomography (EIT) Effectiveness in Detecting Fatty Liver Disease
Non-alcoholic fatty liver disease (NAFLD) is a condition where hepatocytes contain an abnormally high fat percentage. This condition is becoming increasingly common due to unhealthy food habits and sedentary lifestyle. Since NAFLD is a silent disease, many patients would be diagnosed at the advanced stages when fat accumulation, scarring and liver cell damage are irreversible. Therefore, early diagnosis of fatty liver disease during its reversible stages is warranted. Current diagnostic techniques for fatty liver disease, such as the FibroScan® and MRI proton density fat fraction (PDFF) are expensive, and require the active work of certified professionals. Electrical Impedance Tomography (EIT) is an alternative low cost, non-invasive imaging technique that does not involve radiation nor a trained operator. The electrical conductivity of biological tissues varies according to the tissue type and frequency of AC current. Fat tissue conductivity is known to be substantially stable across the EIT current injection frequency spectrum. On the other hand, liver tissue conductivity significantly increases over frequency change. Hence, the liver fat content can be measured using frequency-difference EIT (fdEIT). The aim of this study is to investigate the feasibility and effectiveness of fdEIT in detecting fatty liver. To achieve this goal, a total of 160 subjects will be recruited, paired fdEIT-Fibroscan data will be acquired. First, optimal fdEIT current injection frequency range will be determined. Second, fdEIT derived indicators will be computed and statistical analysis will be performed to verify the significance of correlation between the two. Comparative exploration between EIT and MRI-PDFF will be performed on a subset of the study population, looking at both spatial localization and image derived indicators. Finally, demographics, clinical assessment and patient history will be analysed to produce demographic group-based insights.
Status | Recruiting |
Enrollment | 160 |
Est. completion date | February 29, 2024 |
Est. primary completion date | December 31, 2023 |
Accepts healthy volunteers | |
Gender | All |
Age group | 20 Years to 75 Years |
Eligibility | Inclusion Criteria: - Fatty liver patients diagnosed with fatty liver at S1, S2 and S3 stages, will be included. - Control subjects will also be included (who do not have any known liver diseases). Healthy subjects will be chosen to be age and gender matched with case subjects. Exclusion Criteria: - Subjects with previous liver diseases (in the control group) or any liver diseases other than fatty liver (in fatty liver patients). - Subjects who had any kind of liver surgery or liver transplantation. - Subjects with damaged skin on the abdomen. - Subjects with implanted electronic devices. - Subjects with spinal diseases/discomfort - Subjects who had any recent abdominal surgery - Pregnant women - Ascites - Heavy alcohol intake - Metallic implants |
Country | Name | City | State |
---|---|---|---|
China | The University of Hong Kong | Hong Kong | Select A State Or Province |
Lead Sponsor | Collaborator |
---|---|
The University of Hong Kong | Gense Technologies Ltd., Innovation and Technology Commission, Hong Kong |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Optimal electrical impedance tomography (EIT) injection frequencies for fatty liver detection | The optimal EIT current injection frequencies used in the novel EIT-liver device for fatty liver assessment will be determined by gross data collection and fine-tuning, to shorten the EIT scan time | 24 months | |
Secondary | The performance characteristics of EIT liver device in hepatic steatosis assessment compared to transient elastography | The correlation between the novel EIT-liver device derived data and liver stiffness obtained from transient elastography (a well-established ultrasound-based imaging for liver fat and fibrosis quantification) | 24 months |
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