CI

At a glance

ClinicalIndex Comparison Record
N/ACompleted· 10,333 enrolled
Drug / intervention
AI-human collaboration for CE-CTs diagnosisother
Likely dose
Not stated in record
Structured eligibility isn't available for this trial yet — see the full criteria in the Eligibility tab below.

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Search/NCT07153783
NCT07153783N/ACompleted

AI-human Collaborative Diagnosis of Liver Tumors Using CE-CT

Shengjing Hospital·interventional·Posted Sep 4, 2025·Updated Nov 18, 2025

In Brief

A clinical study evaluating AI-human collaboration for CE-CTs diagnosis for Hepatocellular Carcinoma (HCC) and 5 related conditions. Completed, enrolled 10,333 participants across 1 site.

Detailed Summary

Recent advances in artificial intelligence (AI), particularly deep learning technology, have transformed medical imaging analysis. AI systems have demonstrated diagnostic performance comparable to or exceeding that of expert radiologists in specific tasks. Liver-focused AI diagnostic systems have achieved promising results in multi-center validations; however, these retrospective studies have not yet addressed two critical gaps. First, large-scale prospective trials are required to establish real-world clinical effectiveness. Second, it remains unclear whether AI can be organically embedded into clinical diagnostic workflows to reshape diagnostic and therapeutic pathways, particularly by enhancing the detection and follow-up of hepatic malignancies and ultimately improving patient outcomes.

Study Details

Study Typeinterventional
Allocation--
Masking--
Primary Purpose--
CountriesChina
Collaborators--

Timeline

N/ACompletedFinished
2026
First PostedSep 4, 2025
Enrollment StartSep 1, 2025
Primary CompletionOct 29, 2025
Study CompletionNov 7, 2025
TodayJul 2, 2026
Enrollment to primary: 2 monthsPosted 10 months ago

Interventions

AI-human collaboration for CE-CTs diagnosisother

The system automatically processes all eligible same-day scans and generates results for review the following day. To maintain efficient AI-human collaboration while preserving the standard clinical workflow, the conventional radiological interpretation process remains unchanged (first-line radiologists provide initial reports followed by senior radiologists' review). A dedicated senior radiologist then evaluates any discordances between AI findings and primary radiological report. For complex cases, the review process escalates to a consensus review panel (i.e., pre-designated senior radiologists, Multidisciplinary Team (MDT)). The MDT can recommend clinical interventions including follow-up (e.g., additional imaging examinations, active surveillance), surgical procedures, or adjustments to adjuvant therapy (initiation or modification of treatment regimens). All discordant cases and their outcomes are systematically documented for longitudinal tracking and follow-up analysis.