Non-Alcoholic Fatty Liver DiseaseNCT05676177
CT Liver Fat Fraction Quantification
A study testing Ultra Low Dose CT and Fat quantification MRI in people with Non-Alcoholic Fatty Liver Disease and Steatosis of Liver, run by Sheba Medical Center at 1 site in Israel.
Trial summary
Our aim is to develop an AI based tool to use ultra-low dose CT in two separate energy levels using a single-energy CT machine to quantify liver fat in individuals at risk for having non-alcoholic fatty liver disease (NAFLD), compared to MRI which serves as the standard of reference. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Non-Alcoholic Fatty Liver Disease, Steatosis of Liver
- What is being tested?
- Ultra Low Dose CT and Fat quantification MRI
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 150 participants
- Where
- 1 siteIsrael
- Study dates
- 29 Jan 2023to 31 Dec 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Adult patients (age ≥18 years)
- At risk for hepatic steatosis (defined as at least one of the followings: age >50 years, over weight (BMI>25), impaired fasting glucose or impaired glucose tolerance, T2DM, gestational diabetes, hyperlipidemia, hypertension, elevated liver enzymes, family history of steatosis or cirrhosis, increased liver span per medical examination, increased ferritin levels and the patatin-like phospholipase domain-containing 3 polymorphism), as decided by the treating endocrinologist in our institute's Medical screening department. 12-14
- No history of malignancy involving the liver.
- No known risk factors for hepatic iron deposition (multiple prior blood transfusions, known hemochromatosis).
- Subjects able to understand study procedures and provide informed consent.
- Subjects able to hold their breath during CT and MRI scans.
Who cannot join
- Patients younger than 18 years.
- Patients with risk factors from hepatic iron deposition (multiple prior blood transfusions, known hemochromatosis).
- Patients with known malignancy that involves the liver.
- Patients unable to hold their breath for both CT and MRI.
- Patients with severe claustrophobia.
- Patients with implanted devices of shrapnel.
- Pregnant people
Trial locations and contacts
1 site in 1 country.
About this study
Official title: AI-based Quantification of Liver Fat Fraction Using Two-energy Ultra-low Dose CT Compared to MRI
Our aim is to develop an AI based tool to use ultra-low dose CT in two separate energy levels using a single-energy CT machine to quantify liver fat in individuals at risk for having non-alcoholic fatty liver disease (NAFLD), compared to MRI which serves as the standard of reference.
Secondary aim of our study is to validate the developed artificial intelligence (AI)-based model on a second group of participants ("external validation").
Read the detailed description
Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. It affects 25% of the global population, with a higher proportion in Middle Eastern countries, especially in individuals with type 2 diabetes mellitus (T2DM), in whom NAFLD may be seen in up to 70% of patients. Studies have shown that in coming years, the disease is likely to become more prevalent, with increasing number of patients presenting with the more advanced disease form, nonalcoholic steatohepatitis (NASH), the latter gradually becoming a leading cause for liver transplantation, alongside viral hepatitis. NAFLD is characterized by excessive fat deposition (steatosis) in liver cells and can appear in both obese and non-obese individuals. Among individuals diagnosed with NAFLD, an estimated 12-14% have NASH, which can lead to liver fibrosis, cirrhosis and hepatocellular carcinoma (HCC). As NAFLD is associated with cardiometabolic disorders, including obesity, insulin resistance, T2DM, hypertension and atherogenic dyslipidemia, it increases the risk of cardiovascular events and death. When discovered early, NAFLD can be treated by both lifestyle modification and various drugs. Although the gold standard for detecting NAFLD and quantifying the fat contents in liver cells is a non-targeted liver biopsy, blood tests and non-invasive imaging can assist in early diagnosis of patients at risk for developing NASH and for follow-up after treatment. Ultrasound for detection and assessment of hepatic steatosis is limited by subjective assessment; and variable sensitivity and specificity (53-76% and 76-93%, respectively). US may fail in obese patients or those with ascites, and is highly operator- and platform-dependent (inter- and intra-reader agreement ~50%). Moreover, it has limited utility in fat fraction quantification. Novel US methods are being constantly developed for accurate quantification, but are yet to be agreed upon and used in daily clinical routine.
The most commonly used method for quantifying the amount of fat in the liver is MRI, and specifically chemical shift imaging sequences. However, MRI has limitations, including the cost of scans, limited availability worldwide and patient-specific limitations, including claustrophobia and implanted electronic devices which may be unsafe in the MRI magnetic field. Currently, single and dual energy CT have shown limited utility in diagnosing and quantifying liver steatosis, and although CT is readily available worldwide, currently CT cannot be used for liver fat fraction quantification or for early NAFLD diagnosis. Attempts to utilize dual-energy CT, with and without use of artificial intelligence (AI) has shown limited success. Moreover, dual-energy CT is not readily available in most medical centers.
A prior study the investigators performed has already shown that ultra-low dose chest CT can diagnose liver steatosis, but the investigators have not yet assessed its capabilities in quantifying the amount of liver fat. Therefore, the investigators' aim is to develop a novel methodology in which ultra-low dose abdominal CT could be used for both diagnosing NAFLD and quantifying liver fat contents.
- Being tested
- Ultra Low Dose CT, Fat quantification MRI
- Medical subject headings
- Non-alcoholic Fatty Liver Disease, Fatty Liver
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Ultra Low Dose CTDiagnostic test
- Two immediately consecutive scans with either one or two breath-holds
- First scan (ULD_DECT_1) 140 kilovolt peak (kVp) - fixed current 10 or 20 milliampere (mA) (if body mass index (BMI)>30), that is 5 or 10 mAs
- Second scan (ULD_DECT_2) 80 kVp - fixed current 20 or 40 mA (if BMI>30), that is 10 or 20 mAs
Fat quantification MRIDiagnostic test
Dual echo scans, as well as proton density fat fraction (PDFF) scans, will be performed to assess liver fat fraction
| Study group | Role | What they receive |
|---|---|---|
| Main study arm | Experimental | All consenting participants will be invited to the radiology department during the medical screening rounds or at a different day (at their convenience). They will be scanned on both MRI and CT using dedicated protocols. Both scans will be conducted at the same day within a time-frame of 6 hours of each other. No follow up visit will be required.
MRI would be performed on a 3 Tesla magnet using a dedicated short protocol consisting of axial and coronal T2-weighted scans for anatomic assessment, and a dual-echo scan to assess for liver fat. The scan time would be less than 10 minutes.
CT scans will be performed using a single CT device. Ultra-low dose dual energy CT (ULD-DECT) scanning protocol parameters liver fat measurement (estimated scan time - less than 2 minutes). Receives: Diagnostic Test: Ultra Low Dose CT; Diagnostic Test: Fat quantification MRI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Developing AI model of liver fat fraction assessment on data obtained from ultra-low dose CT, using MRI data as a standard of reference
The investigators will develop an AI based tool to use ultra-low dose CT in two separate energy levels using a single-energy CT machine to quantify liver fat in individuals at risk for having NAFLD, compared to MRI which serves as the standard of reference. The MRI data will be extracted from the dual-echo scan, which can produce an MRI-based liver fat-fraction, and this data will be then used to create an AI CT model.
The AI model will be developed to be able to accurately produce an exact quantification of the liver fat fraction (exact percentage) on ultra-low dose CT.
Measured: Through study completion, up to 24 months
Secondary outcomes (1)
External validation of the AI CT liver fat fraction model using a second participant group not included in the development of the AI-based CT model
After developing the AI-based CT liver fat fraction model, the model will be tested on participants who will undergo the same study procedures (CT and MRI), but these participants' MRI and CT scans are not used to develop the AI model, but rather to test and validate the model.
The AI-model based ultra-low dose CT fat fraction data obtained from these participants will be compared to the data from the MRI standard of reference, and a difference of up to 2% between CT liver fat fraction and MRI fat fraction will be considered a successful validation of the developed AI model.
Measured: Through study completion, up to 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jan 2023
- Study start29 Jan 2023
- Primary completion31 Dec 2024 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Non-Alcoholic Fatty Liver DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sheba Medical Center
- Sponsor type
- Other government
- Responsible party
- Principal investigator, Prof. Noam Tau, Sheba Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05676177
- Sponsor's protocol ID
- 9785-22-SMC
- Status last verified
- Apr 2023
- First submitted
- 6 Dec 2022
- Last updated
- 12 Apr 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 Apr 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-based Quantification of Liver Fat Fraction Using Two-energy Ultra-low Dose CT Compared to MRI
- ClinicalTrials.gov ID
- NCT05676177
- Acronym / sponsor ID
- 9785-22-SMC
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Sheba Medical CenterOther government
- Study start
- 29 Jan 2023 (actual)
- Primary completion
- 31 Dec 2024 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 9 Jan 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Our aim is to develop an AI based tool to use ultra-low dose CT in two separate energy levels using a single-energy CT machine to quantify liver fat in individuals at risk for having non-alcoholic fatty liver disease (NAFLD), compared to MRI which serves as the standard of reference.
Secondary aim of our study is to validate the developed artificial intelligence (AI)-based model on a second group of participants ("external validation").
Detailed description
Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. It affects 25% of the global population, with a higher proportion in Middle Eastern countries, especially in individuals with type 2 diabetes mellitus (T2DM), in whom NAFLD may be seen in up to 70% of patients. Studies have shown that in coming years, the disease is likely to become more prevalent, with increasing number of patients presenting with the more advanced disease form, nonalcoholic steatohepatitis (NASH), the latter gradually becoming a leading cause for liver transplantation, alongside viral hepatitis. NAFLD is characterized by excessive fat deposition (steatosis) in liver cells and can appear in both obese and non-obese individuals. Among individuals diagnosed with NAFLD, an estimated 12-14% have NASH, which can lead to liver fibrosis, cirrhosis and hepatocellular carcinoma (HCC). As NAFLD is associated with cardiometabolic disorders, including obesity, insulin resistance, T2DM, hypertension and atherogenic dyslipidemia, it increases the risk of cardiovascular events and death. When discovered early, NAFLD can be treated by both lifestyle modification and various drugs. Although the gold standard for detecting NAFLD and quantifying the fat contents in liver cells is a non-targeted liver biopsy, blood tests and non-invasive imaging can assist in early diagnosis of patients at risk for developing NASH and for follow-up after treatment. Ultrasound for detection and assessment of hepatic steatosis is limited by subjective assessment; and variable sensitivity and specificity (53-76% and 76-93%, respectively). US may fail in obese patients or those with ascites, and is highly operator- and platform-dependent (inter- and intra-reader agreement ~50%). Moreover, it has limited utility in fat fraction quantification. Novel US methods are being constantly developed for accurate quantification, but are yet to be agreed upon and used in daily clinical routine.
The most commonly used method for quantifying the amount of fat in the liver is MRI, and specifically chemical shift imaging sequences. However, MRI has limitations, including the cost of scans, limited availability worldwide and patient-specific limitations, including claustrophobia and implanted electronic devices which may be unsafe in the MRI magnetic field. Currently, single and dual energy CT have shown limited utility in diagnosing and quantifying liver steatosis, and although CT is readily available worldwide, currently CT cannot be used for liver fat fraction quantification or for early NAFLD diagnosis. Attempts to utilize dual-energy CT, with and without use of artificial intelligence (AI) has shown limited success. Moreover, dual-energy CT is not readily available in most medical centers.
A prior study the investigators performed has already shown that ultra-low dose chest CT can diagnose liver steatosis, but the investigators have not yet assessed its capabilities in quantifying the amount of liver fat. Therefore, the investigators' aim is to develop a novel methodology in which ultra-low dose abdominal CT could be used for both diagnosing NAFLD and quantifying liver fat contents.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Main study arm | Experimental | Diagnostic Test: Ultra Low Dose CT, Diagnostic Test: Fat quantification MRIAll consenting participants will be invited to the radiology department during the medical screening rounds or at a different day (at their convenience). They will be scanned on both MRI and CT using dedicated protocols. Both scans will be conducted at the same day within a time-frame of 6 hours of each other. No follow up visit will be required. MRI would be performed on a 3 Tesla magnet using a dedicated short protocol consisting of axial and coronal T2-weighted scans for anatomic assessment, and a dual-echo scan to assess for liver fat. The scan time would be less than 10 minutes. CT scans will be performed using a single CT device. Ultra-low dose dual energy CT (ULD-DECT) scanning protocol parameters liver fat measurement (estimated scan time - less than 2 minutes). |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Adult patients (age ≥18 years)
- At risk for hepatic steatosis (defined as at least one of the followings: age >50 years, over weight (BMI>25), impaired fasting glucose or impaired glucose tolerance, T2DM, gestational diabetes, hyperlipidemia, hypertension, elevated liver enzymes, family history of steatosis or cirrhosis, increased liver span per medical examination, increased ferritin levels and the patatin-like phospholipase domain-containing 3 polymorphism), as decided by the treating endocrinologist in our institute's Medical screening department. 12-14
- No history of malignancy involving the liver.
- No known risk factors for hepatic iron deposition (multiple prior blood transfusions, known hemochromatosis).
- Subjects able to understand study procedures and provide informed consent.
Key exclusion criteria (7 listed)
- Patients younger than 18 years.
- Patients with risk factors from hepatic iron deposition (multiple prior blood transfusions, known hemochromatosis).
- Patients with known malignancy that involves the liver.
- Patients unable to hold their breath for both CT and MRI.
- Patients with severe claustrophobia.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Ultra Low Dose CT* Two immediately consecutive scans with either one or two breath-holds * First scan (ULD_DECT_1) 140 kilovolt peak (kVp) - fixed current 10 or 20 milliampere (mA) (if body mass index (BMI)>30), that is 5 or 10 mAs * Second scan (ULD_DECT_2) 80 kVp - fixed current 20 or 40 mA (if BMI>30), that is 10 or 20 mAs | Diagnostic test | Main study arm |
| Fat quantification MRIDual echo scans, as well as proton density fat fraction (PDFF) scans, will be performed to assess liver fat fraction | Diagnostic test | Main study arm |
Primary outcome
Developing AI model of liver fat fraction assessment on data obtained from ultra-low dose CT, using MRI data as a standard of reference
Time frame: Through study completion, up to 24 months
The investigators will develop an AI based tool to use ultra-low dose CT in two separate energy levels using a single-energy CT machine to quantify liver fat in individuals at risk for having NAFLD, compared to MRI which serves as the standard of reference. The MRI data will be extracted from the dual-echo scan, which can produce an MRI-based liver fat-fraction, and this data will be then used to create an AI CT model. The AI model will be developed to be able to accurately produce an exact quantification of the liver fat fraction (exact percentage) on ultra-low dose CT.
1 secondary outcome
External validation of the AI CT liver fat fraction model using a second participant group not included in the development of the AI-based CT model
Time frame: Through study completion, up to 24 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Apr 2023.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Ultra Low Dose CT and Fat quantification MRI in people with Non-Alcoholic Fatty Liver Disease and Steatosis of Liver, run by Sheba Medical Center at 1 site in Israel.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 12 Apr 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Israel. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Developing AI model of liver fat fraction assessment on data obtained from ultra-low dose CT, using MRI data as a standard of reference (time frame: Through study completion, up to 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Apr 2023.