CT Liver Fat Fraction Quantification
AI-based Quantification of Liver Fat Fraction Using Two-energy Ultra-low Dose CT Compared to MRI
1 other identifier
interventional
150
1 country
1
Brief 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. Secondary aim of our study is to validate the developed artificial intelligence (AI)-based model on a second group of participants ("external validation").
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jan 2023
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
December 6, 2022
CompletedFirst Posted
Study publicly available on registry
January 9, 2023
CompletedStudy Start
First participant enrolled
January 29, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2025
CompletedApril 12, 2023
April 1, 2023
1.9 years
December 6, 2022
April 11, 2023
Conditions
Outcome Measures
Primary Outcomes (1)
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.
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
Through study completion, up to 24 months
Study Arms (1)
Main study arm
EXPERIMENTALAll 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).
Interventions
* 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
Dual echo scans, as well as proton density fat fraction (PDFF) scans, will be performed to assess liver fat fraction
Eligibility Criteria
You may qualify if:
- 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.
You may not qualify if:
- 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
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Prof. Noam Tau
Ramat Gan, Israel
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- DIAGNOSTIC
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER GOV
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Staff Radiologist and Primary Investigator
Study Record Dates
First Submitted
December 6, 2022
First Posted
January 9, 2023
Study Start
January 29, 2023
Primary Completion
December 31, 2024
Study Completion
December 31, 2025
Last Updated
April 12, 2023
Record last verified: 2023-04
Data Sharing
- IPD Sharing
- Will not share