Interventional AI-Human Collaboration for Steatotic Liver Disease Screening

NCT07613827 | Enrolling By Invitation DMC

• 1 other identifier: SH-CMU-SLD-Intervention
• Study Type: interventional
• Target: 7,969
• Locations: 1 country
• Sites: 1

Brief 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 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.

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

Outcome Measures

Primary Outcomes (1)

• 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.

  6 months

Secondary Outcomes (8)

• Real-World Screening Specificity

  Duration of the study (12 months)

• Real-World Screening Sensitivity

  Duration of the study (12 months)

• Real-World Screening Negative predictive value

  Duration of the study (12 months)

• Intervention Success (Fibrosis Reversion)

  Duration of the study (12 months)

• Intervention Success (Steatosis Reversion)

  Duration of the study (12 months)

Study Arms (1)

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.

Diagnostic Test: AI-human collaboration for SLD screening

Interventions

AI-human collaboration for SLD screening DIAGNOSTIC_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.

AI-human collaboration for SLD screening

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• 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).

Sponsors & Collaborators

• Shengjing Hospital: lead

Study Sites (1)

Shengjing Hospital of China Medical University

Shenyang, Liaoning, 110004, China

Location

Related Publications (1)

• 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.

  PMID: 41672973 BACKGROUND

MeSH Terms

Conditions

Fatty Liver; Liver Cirrhosis

Condition Hierarchy (Ancestors)

Liver Diseases; Digestive System Diseases; Fibrosis; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Deputy director of department of radiology

Study Record Dates

• First Submitted: May 23, 2026
• First Posted: May 29, 2026
• Study Start: February 24, 2026
• Primary Completion (Estimated): August 30, 2026
• Study Completion (Estimated): February 24, 2027
• Last Updated: May 29, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL

Locations

CN (1)