Randomizing by site and by day, not by patient — a 40,000-patient pragmatic trial of AI-assisted liver CT reading with missed lesions as the primary measure — a clinical trial (ClinicalTrials.gov)
A multicenter pragmatic randomized trial that switches AI assistance for liver contrast-enhanced CT reading on and off by center and by day. The primary measure is missed clinically significant malignant liver lesions, with the non-inferiority margin prespecified in the statistical analysis plan before enrollment. AI results are revealed only after the radiologist has saved an unaided initial assessment. Target enrollment is 40,000.
Trial overview (primary data)
- StatusNot yet recruiting
- ConditionsHepatocellular Carcinoma (HCC), Intrahepatic Cholangiocarcinoma (Icc), Hepatic Metastasis, Hepatic Hemangioma, Cyst, Focal Nodular Hyperplasia
- InterventionsOTHER: AI-assisted abdominal CE-CT reporting, OTHER: Standard abdominal CE-CT reporting without AI assistance
- SponsorShengjing Hospital
- Target enrollment40,000 participants
- Period2026-08-17 〜 2027-12-31
Key points
- A multicenter pragmatic randomized trial of AI-assisted reading for multiphasic liver contrast-enhanced CT, switching assistance on and off by center-day, with a target enrollment of 40,000.
- Randomizing by center and day rather than by patient lets the whole reading workflow be compared as it is actually run.
- AI results appear only after the first-line radiologist has saved an unaided initial assessment, so the unaided judgment stays in the record.
- The primary measure is missed clinically significant malignant liver lesions, with the non-inferiority margin prespecified in the statistical analysis plan before enrollment.
- Secondary measures include lesion detection and characterization, downstream clinical management and reporting efficiency.
1You cannot switch it case by case
Turning AI on for one patient and off for the next is not something a reading room can actually do. Once a radiologist has read with the overlay in view, the next unaided read is no longer purely unaided. So this trial moves the unit of randomization from the patient to the center and the day. On one day a site reads with AI assistance, on another without it, and the whole workflow switches together. That is what a trial calling itself pragmatic looks like.
2Fixing the order in which AI appears
- 1Initial readThe first-line radiologist assesses the study without assistance
- 2SaveThat initial assessment is finalized and saved
- 3RevealOnly then are the AI results shown
- 4Final reportThe final report may be revised as needed
The order is a guard against the pull toward changing one's own judgment to match what the machine shows. See the AI first and the unaided read never enters the record at all. Fix the order, and both judgments survive: the one made alone and the one made after seeing the output, so what changed and where can be checked afterwards.
Of the 803 records this site holds as of 2026-09-04, only 5 (0.6%) describe finalizing an unaided read before the assistance appears.
3The primary measure is not benefit but misses
The primary measure is whether clinically significant malignant liver lesions are missed more often. Not a favorable metric like the number of lesions found, but an unfavorable one placed at the center. If assistance raises detection while also raising misses, the point of deploying it is gone. And the non-inferiority margin, per the record, is fixed in the statistical analysis plan before enrollment opens.
A non-inferiority trial whose margin can be chosen afterwards can be made to conclude almost anything.
4What a target of 40,000 buys
A target of 40,000 sits in the top 2% of the 797 records that state one. Missing a clinically significant malignancy is a rare event to begin with, and showing that a rare event does not become more frequent takes a large denominator. Secondary measures cover lesion detection and characterization, and then downstream clinical management and reporting efficiency.
Measuring whether reporting gets faster shows the trial has moved past the rung of accuracy and into the rung that asks whether it holds up inside daily operations.
Why it matters
Randomizing by site and day rather than by patient allows a workflow to be compared as it actually runs and avoids the carry-over of having seen the assistance. Finalizing the unaided judgment before the AI is revealed, and fixing the non-inferiority margin before enrollment, are both devices for keeping the conclusion from moving after the fact, and both transfer to evaluations of deployments far outside medicine.
FAQ
Why not randomize patient by patient?
Why make misses the primary measure?
When is the margin decided?
Sources (primary)
Source: ClinicalTrials.gov (U.S. NIH/NLM, public domain). This site does not provide medical advice. Verify the latest and exact details with the official source. This site is not endorsed or certified by the NIH/NLM.
- ClinicalTrials.gov (study record, original)
- NCT ID: NCT07768085