This study is a 12-month pilot clinical trial designed to evaluate the feasibility, usability, provider trust, and preliminary effectiveness of FibroX, an explainable artificial intelligence (AI) tool developed to improve the diagnosis of significant liver fibrosis (≥F2) and clinically significant portal hypertension in adults with metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD is a common and progressive liver condition that can lead to cirrhosis, liver failure, and increased cardiovascular risk. Early detection of these conditions is critical because current guidelines recommend initiating therapy (e.g., resmetirom or semaglutide for ≥F2 fibrosis and beta-blockers for portal hypertension). However, existing tools like FIB-4 often lack accuracy and usability in routine primary care.
FibroX addresses these limitations by using routinely available clinical data-such as age, liver enzymes, platelet count, BMI, and kidney function-to estimate the probability of significant fibrosis and portal hypertension. It provides a triage band (rule-out, indeterminate, rule-in) and a one-line explanation of which clinical factors most influenced the prediction. This transparency is achieved using Shapley Additive Explanations (SHAP), which helps clinicians understand how the AI reached its conclusion.
In retrospective studies, FibroX demonstrated superior diagnostic performance compared to FIB-4 (AUROC 0.97 vs. 0.62) and was associated with long-term mortality risk, suggesting prognostic value beyond diagnostic utility.
This pilot trial will simulate real-world primary care workflows to test whether FibroX can be effectively used by clinicians. The study will recruit 30-40 primary care providers (MDs, DOs, NPs, PAs) from 4-6 diverse clinics. Each provider will participate in two simulation periods, each involving 16 synthetic or de-identified patient cases reflecting adults with MASLD risk factors. Ground truth for fibrosis stage and portal hypertension will be determined by biopsy or expert consensus using Vibration-Controlled Transient Elastography (VCTE) and guideline-based criteria.
Providers will be randomly assigned to review cases in one of two sequences:
* FibroX-Enabled Care: Providers will receive FibroX's risk probability, triage band, and explainability panel.
* Usual Care: Providers will use standard labs and vitals, with optional access to the FIB-4 calculator.
After a one-week washout period, providers will switch to the other condition. For each case, providers will make a management decision (e.g., no action, order VCTE, refer to hepatology), record their confidence level, and complete surveys on usability, trust in AI, and cognitive workload.
Primary Outcomes
* Feasibility: Recruitment rate ≥70%, completion rate ≥85%, median decision time ≤3.5 minutes.
* Usability and Acceptability: System Usability Scale (SUS) score ≥70.
* Provider Trust: AI-Trust Scale score ≥6.
* Effectiveness: Within-provider diagnostic accuracy for significant fibrosis (≥F2) and clinically significant portal hypertension.
Secondary Outcomes
* Appropriate referral rates
* Net reclassification improvement (NRI)
* Calibration metrics (intercept, slope)
* Provider confidence and cognitive load (NASA-TLX)
* Intended downstream testing burden
* Adoption and fidelity to triage recommendations
* Override rates and reasons
* Fairness analysis across subgroups (age, sex, BMI, race/ethnicity)
All provider actions and decision times will be automatically logged. Post-period surveys and qualitative debriefs will explore barriers and facilitators to using FibroX.
Study Significance This pilot study will generate critical data to support a future multi-center trial and potential integration of FibroX into electronic health records. If successful, FibroX could enable scalable, guideline-concordant screening for significant liver fibrosis and portal hypertension in primary care, reducing missed diagnoses and unnecessary referrals. This aligns with national priorities for precision medicine and responsible AI implementation in healthcare.
