Steatotic Liver DiseaseNCT07613827
Interventional AI-Human Collaboration for Steatotic Liver Disease Screening
A study testing AI-human collaboration for SLD screening in people with Steatotic Liver Disease and Liver Fibrosis Progression in Chronic Liver Disease, run by Shengjing Hospital at 1 site in China.
Trial summary
Steatotic liver disease (SLD) is one of the most prevalent chronic liver diseases worldwide, affecting nearly 30% of the global population and projected to exceed 55% by 2040. Timely identification and management of intermediate- and high-risk SLD patients are essential, yet early detection remains challenging because… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Steatotic Liver Disease, Liver Fibrosis Progression in Chronic Liver Disease, Liver Steatosis
- What is being tested?
- AI-human collaboration for SLD screening
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 7,969 participants
- Where
- 1 siteChina
- Study dates
- 24 Feb 2026to 24 Feb 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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
- Adults aged ≥18 years undergoing routine non-contrast or contrast-enhanced chest or abdominal CT examination.
- CT images with adequate hepatic coverage and sufficient image quality for MAOSS analysis.
- Willing to undergo the recall evaluation and either: having a FIB-4 result within the past 1 month, or willing to complete blood testing (ALT, AST, platelet count) required for FIB-4 calculation and undergo FibroScan or MRE assessment.
- Willing to participate in the study and able to provide written informed consent at the time of recall.
Who cannot join
- Known malignant liver tumors (e.g., HCC, cholangiocarcinoma) or a history of liver transplantation or major hepatic resection.
- Known cirrhosis based on noninvasive fibrosis assessment tests, liver biopsy or complications of decompensated disease, or with a documented history of cirrhosis identified by clinical notes will be excluded.
- Biliary obstruction, acute cholangitis, or other conditions that may interfere with interpretation of liver biochemistry or fibrosis risk assessment.
- CT images with severe artifacts or incomplete liver coverage preventing reliable MAOSS analysis.
- Severe acute systemic illness (e.g., sepsis, shock, acute heart failure), or pregnancy or breastfeeding.
- Unwilling or unable to complete recall procedures, including required blood tests, FibroScan, or MRE when indicated, or unable to comply with study follow-up.
- Severe comorbidity with an expected survival of less than 1 year (e.g., terminal malignancy).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
Shengjing Hospital of China Medical University
Shenyang, Liaoning, 110004
About this study
Official title: AI-Driven Opportunistic Screening and Risk-Adapted Management of Steatotic Liver Disease
Steatotic liver disease (SLD) is one of the most prevalent chronic liver diseases worldwide, affecting nearly 30% of the global population and projected to exceed 55% by 2040. Timely identification and management of intermediate- and high-risk SLD patients are essential, yet early detection remains challenging because current diagnostic modalities, such as biopsy, ultrasonography, and serum indices, are invasive, insensitive, operator-dependent, or difficult to scale. In contrast, non-contrast CT is widely available in routine care and offers substantial potential for opportunistic SLD screening, although this value has not been fully utilized. Our previously developed MAOSS model accurately identifies intermediate- and high-risk individuals, with MAOSS score≥1.6 combined with Fibro Score ≥1.7, demonstrating high sensitivity and specificity in our large-scale retrospective study. However, despite these promising retrospective findings, the model has not undergone prospective interventional validation, and it remains unclear whether an AI-guided workflow can truly enhance clinical risk stratification, diagnostic yield, and downstream management in real-world SLD populations. Therefore, a prospective intervention study is needed to determine whether MAOSS-guided identification and recall of at-risk individuals can meaningfully improve fibrosis detection and optimize clinical care pathways for SLD.
Read the detailed description
The AIG-SLD Screening Project is a single-arm, open-label, prospective interventional study designed to evaluate the effectiveness of a MAOSS-guided identification and AI-human collaboration recall strategy for detecting individuals at intermediate or high risk of steatotic liver disease (SLD) and for assessing intervention outcomes. The trail will prospectively and consecutively enroll around 8000 eligible adults aged ≥18 years who undergo routine chest or abdominal non-contrast CT (NCCT) with adequate hepatic coverage .
The AI system i.e. MAOSS will be embedded within the standard clinical workflow to evaluate the real-world performance and the impact of AIG-SLD screening. All eligible NCCT scans will be evaluated through two parallel streams:
- Standard of Care (SoC) workflow: Radiologists perform independent assessments, first-line radiologists review followed by a senior radiologist finalizing the report.
- AIG workflow: The MAOSS system simultaneously analyzes the identical imaging data in real-time.
The system screens patients with clinically suspected SLD by flagging those with a MAOSS score ≥1.6 and a FIBRO Score ≥1.7 for recall. These algorithmic flags will be compared against radiologists' determinations of clinically significant SLD. Management pathways are defined as follows: (1) Concordant cases: If the Standard of Care (SoC) and the AIG pathway agree (both recommending recall or both recommending no recall), the agreed-upon decision will be executed. (2) Discordant cases: If the SoC and AIG pathways disagree, patients will be recalled for primary hepatology care to ensure safety.
Primary hepatology care begins with the collection of questionnaires regarding medical history, lifestyle, alcohol consumption, and metabolic risks (Type 2 Diabetes Mellitus, obesity, metabolic syndrome, significant alcohol consumption, or viral hepatitis) followed by further serum laboratory tests and Transient Elastography (e.g., FibroScan). Recalled patients will be managed according to the MAOSS pathway starting with FIB-4 stratification (<1.3, 1.3-2.67, >2.67), followed by FAST stratification (<0.35, ≥0.35) as needed. Intermediate-to-high-risk patients will proceed to escalated care involving MRE, MRI-PDFF, or liver biopsy. Management is then determined by MRE-derived Liver Stiffness Measurement (LSM): patients with LSM < 3.5 kPa will receive lifestyle interventions and annual reassessment; those with LSM 3.5-5.0 kPa (F2-F3) will receive pharmacological or therapeutic interventions; and those with LSM ≥ 5.0 kPa (F4) will undergo cirrhosis-based management. Patients in the latter two groups will be reassessed every six months to monitor changes in steatosis and fibrosis.
- Conditions
- Steatotic Liver Disease, Liver Fibrosis Progression in Chronic Liver Disease, Liver Steatosis, Liver Fibrosis, Steatotic Liver Disease of Mixed Origin (MetALD)
- Being tested
- AI-human collaboration for SLD screening
- Keywords
- opportunistic screening, non-contrast CT, risk stratification
- Medical subject headings
- Fatty Liver, Liver Cirrhosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-human collaboration for SLD screeningDiagnostic test
The system screens patients with clinically suspected SLD by flagging those with a MAOSS score ≥1.6 and a FIBRO Score ≥1.7 for recall. These algorithmic flags will be compared against radiologists' determinations of clinically significant SLD. Management pathways are defined as follows: (1) Concordant cases: If the Standard of Care (SoC) and the AIG pathway agree (both recommending recall or both recommending no recall), the agreed-upon decision will be executed. (2) Discordant cases: If the SoC and AIG pathways disagree, patients will be recalled for primary hepatology care to ensure safety and avoid potential missed diagnosis.
| Study group | Role | What they receive |
|---|---|---|
| AI-human collaboration for SLD screening | Experimental | In the prospective analysis phase, all eligible NCCT scans will be evaluated through two parallel streams: 1. Standard of Care (SoC) workflow: Radiologists perform independent assessments as per standard clinical procedures (e.g., first-line radiologists' reviews followed by senior radiologist finalizing the report). 2. AIG workflow: The MAOSS system simultaneously analyzes the identical imaging data in real-time. Receives: Diagnostic Test: AI-human collaboration for SLD screening |
What is being measured
The primary outcome is the main question the study is designed to answer.
Effective referral yield for escalated hepatology care
Effective referral yield: the proportion of patients referred for escalated hepatology care confirmed with clinically significant (or above) fibrosis by MRE/liver biposy. A non-inferiority test (and estimates of the associated absolute and relative differences) will be performed for effective referral yield between SoC and AIG workflow.
Measured: 6 months
Secondary outcomes (8)
Real-World Screening Specificity
A critical safety endpoint is to determine if AIG-SLD care pathway maintains a high specificity to prevent false referral, thereby avoiding unnecessary interventions.
Measured: Duration of the study (12 months)
Real-World Screening Sensitivity
A critical efficacy endpoint is to determine if AIG-SLD care pathway is sufficiently sensitive to identify patients who actually need interventions.
Measured: Duration of the study (12 months)
Real-World Screening Negative predictive value
This evaluates the AIG-SLD care pathway's ability to correctly exclude low-risk patients who actually do not need interventions.
Measured: Duration of the study (12 months)
Intervention Success (Fibrosis Reversion)
The proportion of patients referred for escalated care achieves fibrosis stage reversion.
Measured: Duration of the study (12 months)
Intervention Success (Steatosis Reversion)
The proportion of patients referred for escalated care achieves steatosis stage Reversion.
Measured: Duration of the study (12 months)
Quantitative Liver Stiffness Trends
The overall longitudinal changes in Liver Stiffness Measurement (LSM) values for all patients referred to escalated care.
Measured: Duration of the study (12 months)
Quantitative Liver Steatosis Trends
The overall longitudinal changes in Liver Fat Content (CAP/PDFF) values for all patients referred to escalated care.
Measured: Duration of the study (12 months)
Intervention Patient Adherence
The overall intervention adherence rate for all patients referred to escalated care.
Measured: Duration of the study (12 months)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 May 2026
- Study start24 Feb 2026
- Primary completion30 Aug 2026 (estimated)
- Study completion24 Feb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Steatotic 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
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 7,969 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shengjing Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yu Shi, Shengjing Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07613827
- Sponsor's protocol ID
- SH-CMU-SLD-Intervention
- Status last verified
- May 2026
- First submitted
- 23 May 2026
- Last updated
- 29 May 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Publications
Gao Y, Li C, Chang W, Du B, Ye X, Yeo YH, Xia Y, Guo H, Zhang X, Liu W, Bai R, Li B, Hong Y, Yao J, Lu L, Cao K, Yan K, Chen J, Li J, Hou Y, Zhang L, Shi Y. Multi-modal AI for opportunistic screening, staging and progression risk stratification of steatotic liver disease. Nat Commun. 2026 Feb 11;17(1):1562. doi: 10.1038/s41467-026-68414-3.
PubMed 41672973
Study at a glance
From the registry record, last updated by the sponsor on 29 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-Driven Opportunistic Screening and Risk-Adapted Management of Steatotic Liver Disease
- ClinicalTrials.gov ID
- NCT07613827
- Acronym / sponsor ID
- SH-CMU-SLD-Intervention
- Conditions
- Steatotic Liver Disease, Liver Fibrosis Progression in Chronic Liver Disease, Liver Steatosis, Liver Fibrosis, Steatotic Liver Disease of Mixed Origin (MetALD)
- Keywords
- opportunistic screening, non-contrast CT, risk stratification
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 7,969 participants (estimated)
- Lead sponsor
- Shengjing HospitalUniversity, hospital or other
- Study start
- 24 Feb 2026 (actual)
- Primary completion
- 30 Aug 2026 (estimated)
- Study completion
- 24 Feb 2027 (estimated)
- First posted
- 29 May 2026 (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.
Steatotic liver disease (SLD) is one of the most prevalent chronic liver diseases worldwide, affecting nearly 30% of the global population and projected to exceed 55% by 2040. Timely identification and management of intermediate- and high-risk SLD patients are essential, yet early detection remains challenging because current diagnostic modalities, such as biopsy, ultrasonography, and serum indices, are invasive, insensitive, operator-dependent, or difficult to scale. In contrast, non-contrast CT is widely available in routine care and offers substantial potential for opportunistic SLD screening, although this value has not been fully utilized. Our previously developed MAOSS model accurately identifies intermediate- and high-risk individuals, with MAOSS score≥1.6 combined with Fibro Score ≥1.7, demonstrating high sensitivity and specificity in our large-scale retrospective study. However, despite these promising retrospective findings, the model has not undergone prospective interventional validation, and it remains unclear whether an AI-guided workflow can truly enhance clinical risk stratification, diagnostic yield, and downstream management in real-world SLD populations. Therefore, a prospective intervention study is needed to determine whether MAOSS-guided identification and recall of at-risk individuals can meaningfully improve fibrosis detection and optimize clinical care pathways for SLD.
Detailed description
The AIG-SLD Screening Project is a single-arm, open-label, prospective interventional study designed to evaluate the effectiveness of a MAOSS-guided identification and AI-human collaboration recall strategy for detecting individuals at intermediate or high risk of steatotic liver disease (SLD) and for assessing intervention outcomes. The trail will prospectively and consecutively enroll around 8000 eligible adults aged ≥18 years who undergo routine chest or abdominal non-contrast CT (NCCT) with adequate hepatic coverage .
The AI system i.e. MAOSS will be embedded within the standard clinical workflow to evaluate the real-world performance and the impact of AIG-SLD screening. All eligible NCCT scans will be evaluated through two parallel streams:
- Standard of Care (SoC) workflow: Radiologists perform independent assessments, first-line radiologists review followed by a senior radiologist finalizing the report.
- AIG workflow: The MAOSS system simultaneously analyzes the identical imaging data in real-time.
The system screens patients with clinically suspected SLD by flagging those with a MAOSS score ≥1.6 and a FIBRO Score ≥1.7 for recall. These algorithmic flags will be compared against radiologists' determinations of clinically significant SLD. Management pathways are defined as follows: (1) Concordant cases: If the Standard of Care (SoC) and the AIG pathway agree (both recommending recall or both recommending no recall), the agreed-upon decision will be executed. (2) Discordant cases: If the SoC and AIG pathways disagree, patients will be recalled for primary hepatology care to ensure safety.
Primary hepatology care begins with the collection of questionnaires regarding medical history, lifestyle, alcohol consumption, and metabolic risks (Type 2 Diabetes Mellitus, obesity, metabolic syndrome, significant alcohol consumption, or viral hepatitis) followed by further serum laboratory tests and Transient Elastography (e.g., FibroScan). Recalled patients will be managed according to the MAOSS pathway starting with FIB-4 stratification (<1.3, 1.3-2.67, >2.67), followed by FAST stratification (<0.35, ≥0.35) as needed. Intermediate-to-high-risk patients will proceed to escalated care involving MRE, MRI-PDFF, or liver biopsy. Management is then determined by MRE-derived Liver Stiffness Measurement (LSM): patients with LSM < 3.5 kPa will receive lifestyle interventions and annual reassessment; those with LSM 3.5-5.0 kPa (F2-F3) will receive pharmacological or therapeutic interventions; and those with LSM ≥ 5.0 kPa (F4) will undergo cirrhosis-based management. Patients in the latter two groups will be reassessed every six months to monitor changes in steatosis and fibrosis.
Study design
- Primary purpose
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| AI-human collaboration for SLD screening | Experimental | Diagnostic Test: AI-human collaboration for SLD screeningIn the prospective analysis phase, all eligible NCCT scans will be evaluated through two parallel streams: 1. Standard of Care (SoC) workflow: Radiologists perform independent assessments as per standard clinical procedures (e.g., first-line radiologists' reviews followed by senior radiologist finalizing the report). 2. AIG workflow: The MAOSS system simultaneously analyzes the identical imaging data in real-time. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Adults aged ≥18 years undergoing routine non-contrast or contrast-enhanced chest or abdominal CT examination.
- CT images with adequate hepatic coverage and sufficient image quality for MAOSS analysis.
- Willing to undergo the recall evaluation and either: having a FIB-4 result within the past 1 month, or willing to complete blood testing (ALT, AST, platelet count) required for FIB-4 calculation and undergo FibroScan or MRE assessment.
- Willing to participate in the study and able to provide written informed consent at the time of recall.
Key exclusion criteria (7 listed)
- Known malignant liver tumors (e.g., HCC, cholangiocarcinoma) or a history of liver transplantation or major hepatic resection.
- Known cirrhosis based on noninvasive fibrosis assessment tests, liver biopsy or complications of decompensated disease, or with a documented history of cirrhosis identified by clinical notes will be excluded.
- Biliary obstruction, acute cholangitis, or other conditions that may interfere with interpretation of liver biochemistry or fibrosis risk assessment.
- CT images with severe artifacts or incomplete liver coverage preventing reliable MAOSS analysis.
- Severe acute systemic illness (e.g., sepsis, shock, acute heart failure), or pregnancy or breastfeeding.
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 |
|---|---|---|
| AI-human collaboration for SLD screeningThe system screens patients with clinically suspected SLD by flagging those with a MAOSS score ≥1.6 and a FIBRO Score ≥1.7 for recall. These algorithmic flags will be compared against radiologists' determinations of clinically significant SLD. Management pathways are defined as follows: (1) Concordant cases: If the Standard of Care (SoC) and the AIG pathway agree (both recommending recall or both recommending no recall), the agreed-upon decision will be executed. (2) Discordant cases: If the SoC and AIG pathways disagree, patients will be recalled for primary hepatology care to ensure safety and avoid potential missed diagnosis. | Diagnostic test | AI-human collaboration for SLD screening |
Primary outcome
Effective referral yield for escalated hepatology care
Time frame: 6 months
Effective referral yield: the proportion of patients referred for escalated hepatology care confirmed with clinically significant (or above) fibrosis by MRE/liver biposy. A non-inferiority test (and estimates of the associated absolute and relative differences) will be performed for effective referral yield between SoC and AIG workflow.
8 secondary outcomes
Real-World Screening Specificity
Time frame: Duration of the study (12 months)
Real-World Screening Sensitivity
Time frame: Duration of the study (12 months)
Real-World Screening Negative predictive value
Time frame: Duration of the study (12 months)
Intervention Success (Fibrosis Reversion)
Time frame: Duration of the study (12 months)
Intervention Success (Steatosis Reversion)
Time frame: Duration of the study (12 months)
Quantitative Liver Stiffness Trends
Time frame: Duration of the study (12 months)
Quantitative Liver Steatosis Trends
Time frame: Duration of the study (12 months)
Intervention Patient Adherence
Time frame: Duration of the study (12 months)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 May 2026.
- Background: PubMed 41672973Gao Y, Li C, Chang W, Du B, Ye X, Yeo YH, Xia Y, Guo H, Zhang X, Liu W, Bai R, Li B, Hong Y, Yao J, Lu L, Cao K, Yan K, Chen J, Li J, Hou Y, Zhang L, Shi Y. Multi-modal AI for opportunistic screening, staging and progression risk stratification of steatotic liver disease. Nat Commun. 2026 Feb 11;17(1):1562. doi: 10.1038/s41467-026-68414-3.
- Individual participant dataSharing planned: Yes
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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.
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 AI-human collaboration for SLD screening in people with Steatotic Liver Disease and Liver Fibrosis Progression in Chronic Liver Disease, run by Shengjing Hospital at 1 site in China.
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 4 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: enrolling by invitation, as of the sponsor's last update on 29 May 2026. 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 China. 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?
This study is still under way. Results are not available in the source record yet.
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?
Effective referral yield for escalated hepatology care (time frame: 6 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07613827, which also lists 1 linked publication.
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 29 May 2026; AzTrials last refreshed its copy on 26 Oct 2026.