A Phase 1 interventional study of Experimental: EvoXRare AI-Assisted Chest Radiograph Interpretation. in Emergency and Critical Care, Chest Radiography and Diagnostic Error, sponsored by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Not yet recruiting. Open to participants aged 18 Years to 90 Years. Per ClinicalTrials.gov, last updated 2026-11-09.
Sponsored by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology · Phase 1, Interventional, and Diagnostic
Chest radiography is widely used in emergency departments, resuscitation rooms, intensive care units, and other acute-care settings. Clinically important abnormalities may be missed because findings are subtle, uncommon, obscured by overlapping anatomy, or encountered under high workload. This pragmatic randomized trial evaluates whether EvoXRare, an artificial intelligence system that provides a draft chest radiograph report and high-risk alerts for uncommon or clinically important abnormalities, reduces clinically important diagnostic misses compared with routine physician interpretation alone. Approximately 70,000 adults will be randomized 1:1 across 15-20 hospitals in China. The primary endpoint is the patient-level rate of clinically important abnormalities present on the reference standard but not reported in the initial clinical interpretation. Key secondary outcomes include detection of rare or easily missed findings, time to recognition of critical abnormalities, report turnaround time, false-positive alerts, additional imaging, recall/communication events, and selected short-term clinical outcomes.
This is a nationwide, multicenter, prospective, parallel-group, superiority randomized controlled trial with individual participant-level 1:1 allocation and blinded central endpoint adjudication. Eligible participants are adults undergoing clinically indicated chest radiography in emergency or critical-care settings. Only one index radiograph encounter per participant contributes to the primary randomized analysis.
In the control arm, physicians interpret the chest radiograph using the participating hospital's usual workflow without access to EvoXRare trial output. In the intervention arm, EvoXRare processes the same image on an independent AI workstation and provides a pre-generated report and/or high-risk prompts. The physician must review the original image, verify or edit the AI output, and remains responsible for the final report and all clinical communication. Both arms retain routine senior review and local critical-result procedures.
The AI model version, weights, preprocessing, thresholds, supported finding set, and report format are frozen before formal enrollment. No online learning or outcome-driven recalibration occurs during the randomized trial. If AI processing fails or images do not meet technical requirements, clinical care proceeds without delay and the participant remains in the assigned group for intention-to-treat analysis.
The reference standard is established by a blinded adjudication process using the index radiograph together with clinically available follow-up information, which may include subsequent CT, ultrasound, pathology, surgery, laboratory findings, clinical course, discharge diagnosis, or follow-up imaging. Adjudicators do not use the randomized assignment or EvoXRare output when determining whether a prespecified abnormality was present on the index radiograph.
The trial is designed primarily to test clinical diagnostic performance and workflow impact, not to retrain the AI system. It specifically emphasizes uncommon, high-consequence, and easily missed chest radiograph findings while also evaluating overall report quality and efficiency.
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology is the lead sponsor of 181 studies on the registry; 144 are open to participants now.
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Exclusion Criteria:
Usual chest radiograph interpretation plus access to EvoXRare-generated draft report and high-risk prompts. The physician reviews the original image, accepts/rejects/edits AI suggestions, submits the final report, and follows local critical-result communication procedures.
Device: Experimental: EvoXRare AI-Assisted Chest Radiograph Interpretation.
Routine physician interpretation according to the participating hospital's usual workflow, without access to EvoXRare trial output. Routine nontrial tools already in use may continue only if documented before site activation and applied consistently.
EvoXRare is an artificial intelligence software system that analyzes chest radiographs and provides draft reports and high-risk prompts to the interpreting physician. The physician reviews the original images and AI outputs and accepts, rejects, or edits the suggestions before finalizing the radiology report.
Patient-Level Clinically Important Abnormality Miss Rate on the Index Chest Radiograph
Proportion of randomized participants with at least one prespecified clinically important abnormality (Category A or B) judged present on the reference standard but absent from the initial finalized chest radiograph report produced under the assigned strategy.
Time frame: From index radiograph interpretation through completion of blinded endpoint adjudication, using clinically available information obtained during the index encounter and prespecified follow-up window (target: within 30 days when available).
No study locations are listed for this record.
PDFs hosted by the registry, ClinicalTrials.gov.
Plan to share: Yes — Yes, through controlled access subject to compatible consent/ethics approval and institutional authorization.
Supporting information: Study protocol, Statistical analysis plan, Informed consent form, Clinical study report, Analytic code
Start is estimated for Nov 2026; primary completion for Nov 2027, 12 months later.
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From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
This study is not yet recruiting, as verified in Nov 2026. You cannot join it, but the record below documents what was studied.
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