Pulmonary NodulesNCT07895277
Longitudinal AI-Assisted Management of Indeterminate Pulmonary Nodules
A study testing AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management in people with Pulmonary Nodules and Lung Neoplasms, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology at 1 site in China.
Trial summary
Patients with indeterminate lung nodules often face a choice between continued CT surveillance and invasive investigation. This trial compares management with or without access to an AI report that matches nodules across real serial CT scans, measures change, and estimates validated malignancy or invasiveness risks. Read more about this study
- Who is it for?
- Ages 35 years and older
- Conditions the study is for
- Pulmonary Nodules, Lung Neoplasms
- What is being tested?
- AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 6,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2025to 1 Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 35 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 1. At least one persistent indeterminate pulmonary nodule measuring 6 to 30 mm on the latest clinically obtained CT; solid, part-solid, and pure ground-glass nodules are eligible. 2. Two CT examinations in total are already available: the latest within 30 days before randomization and an earlier examination 3 to 24 months before it. Both meet the frozen image-quality requirements for longitudinal comparison. 3. The current decision between continued surveillance and further investigation remains unresolved, with no mandatory urgent procedure or committed definitive treatment before randomization.
- 4. The patient is potentially eligible for curative treatment if cancer is diagnosed, with an estimated life expectancy of at least five years independent of the study nodule. 5. Written informed consent and willingness to permit record retrieval and five-year contact.
Who cannot join
- 1.Definitive diagnosis or previous treatment of the target nodule; overt metastatic disease, suspicious adenopathy requiring urgent work-up, or another indication making delayed evaluation inappropriate. 2.Active malignancy or cancer treatment within the preceding five years, except definitively treated nonmelanoma skin cancer or in situ cervical cancer.
- 3. Clinically important immunocompromise or active pulmonary infection requiring a separate diagnostic pathway. 4. Current participation in an organized lung-cancer screening program with a mandated management pathway incompatible with this trial. 5. CT quality or acquisition differences prevent valid longitudinal evaluation; a clearly benign lesion does not require a diagnostic management decision. 6. Known pregnancy; a conflicting interventional trial; prior randomization in this study; or consent cannot be obtained.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, 466200
Xiaoyu Han, +8618202771604, xiaoyuhan1123@163.com
About this study
Official title: Study of Imaging Evolution of Pulmonary Nodules and Artificial Intelligence-Assisted Diagnostic and Management Strategies
Patients with indeterminate lung nodules often face a choice between continued CT surveillance and invasive investigation. This trial compares management with or without access to an AI report that matches nodules across real serial CT scans, measures change, and estimates validated malignancy or invasiveness risks. The principal question is whether offering the report reduces lung resections that yield benign pathology over 24 months. Diagnostic delay, cancer stage, treatment opportunity, complications, and longer-term cancer outcomes are also assessed.
Read the detailed description
This pragmatic superiority trial uses individual 1:1 randomization, concealed allocation, and blinded central outcome assessment. Eligible patients have persistent 6 to 30 mm nodules and at least two already available CT examinations. They are enrolled at an unresolved management decision before an invasive procedure or definitive treatment. A second CT must never be delayed or ordered solely to make an otherwise urgent case eligible.
Both arms receive structured longitudinal review, usual quantitative tools, the same nodule-management pathway, and the same appointment reminders. The intervention arm additionally receives the locked AI report. Clinicians retain responsibility for decisions and document patient preferences. Thus the comparison estimates the added effect of the AI-assisted strategy over an organized usual-care pathway, rather than over absent follow-up.
All randomized participants contribute to the primary analysis. Benign procedures are assessed per randomized patient rather than only among patients eventually classified as benign. This avoids making the primary denominator depend on postrandomization diagnostic work-up. Long-term surveillance also addresses the possibility that an apparent early reduction in surgery merely postpones diagnosis.
- Conditions
- Pulmonary Nodules, Lung Neoplasms
- Being tested
- AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management
- Keywords
- Longitudinal chest CT, artificial intelligence, pulmonary nodule surveillance, benign lung resection, diagnostic delay, randomized trial
- Medical subject headings
- Multiple Pulmonary Nodules, Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule ManagementDevice
AI software analyzes serial clinically acquired chest CT scans to match pulmonary nodules, quantify changes in volume and solid components, and provide malignancy or invasiveness risk estimates. Intervention-arm clinicians review the AI report alongside CT images during management consultations. The baseline report is targeted within one working day after randomization. The same locked model is reapplied to clinically indicated follow-up CT scans during the 24-month intervention period. Clinicians retain responsibility for final decisions; AI findings cannot independently override clinically indicated evaluation. If processing fails or images are unsuitable, usual care proceeds. Both arms follow the same structured nodule-management pathway, but the control arm has no access to trial AI reports.
| Study group | Role | What they receive |
|---|---|---|
| AI-Assisted Longitudinal Nodule Management | Experimental | Usual care plus the locked AI report reviewed with the actual CT images. Receives: Device: AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management |
| Structured Usual Nodule Management | No intervention | Serial CT comparison, clinical risk assessment, routine measurement tools, and guideline-based management without access to the trial AI report. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Lung Resection Yielding Benign Pathology Within 24 Months
Measured: Randomization through month 24. Procedures performed in this window are included even if their final pathology report is completed shortly afterward.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Oct 2026
- Study start1 Jan 2025
- Primary completion1 Nov 2027 (estimated)
- Study completion1 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary NodulesStudies of the same condition, open and under way.
- More trials run by Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 6,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xiaoyu Han, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07895277
- Sponsor's protocol ID
- WHUH-PN-AI-RCT-2026-01
- Status last verified
- Oct 2026
- First submitted
- 19 Oct 2026
- Last updated
- 26 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Through controlled access under compatible consent and institutional authorization
Study at a glance
From the registry record, last updated by the sponsor on 26 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Study of Imaging Evolution of Pulmonary Nodules and Artificial Intelligence-Assisted Diagnostic and Management Strategies
- ClinicalTrials.gov ID
- NCT07895277
- Acronym / sponsor ID
- WHUH-PN-AI-RCT-2026-01
- Conditions
- Pulmonary Nodules, Lung Neoplasms
- Keywords
- Longitudinal chest CT, artificial intelligence, pulmonary nodule surveillance, benign lung resection, diagnostic delay, randomized trial
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 6,000 participants (estimated)
- Lead sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyUniversity, hospital or other
- Study start
- 1 Jan 2025 (actual)
- Primary completion
- 1 Nov 2027 (estimated)
- Study completion
- 1 Dec 2027 (estimated)
- First posted
- 26 Oct 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Patients with indeterminate lung nodules often face a choice between continued CT surveillance and invasive investigation. This trial compares management with or without access to an AI report that matches nodules across real serial CT scans, measures change, and estimates validated malignancy or invasiveness risks. The principal question is whether offering the report reduces lung resections that yield benign pathology over 24 months. Diagnostic delay, cancer stage, treatment opportunity, complications, and longer-term cancer outcomes are also assessed.
Detailed description
This pragmatic superiority trial uses individual 1:1 randomization, concealed allocation, and blinded central outcome assessment. Eligible patients have persistent 6 to 30 mm nodules and at least two already available CT examinations. They are enrolled at an unresolved management decision before an invasive procedure or definitive treatment. A second CT must never be delayed or ordered solely to make an otherwise urgent case eligible.
Both arms receive structured longitudinal review, usual quantitative tools, the same nodule-management pathway, and the same appointment reminders. The intervention arm additionally receives the locked AI report. Clinicians retain responsibility for decisions and document patient preferences. Thus the comparison estimates the added effect of the AI-assisted strategy over an organized usual-care pathway, rather than over absent follow-up.
All randomized participants contribute to the primary analysis. Benign procedures are assessed per randomized patient rather than only among patients eventually classified as benign. This avoids making the primary denominator depend on postrandomization diagnostic work-up. Long-term surveillance also addresses the possibility that an apparent early reduction in surgery merely postpones diagnosis.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-Assisted Longitudinal Nodule Management | Experimental | Device: AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule ManagementUsual care plus the locked AI report reviewed with the actual CT images. |
| Structured Usual Nodule Management | No intervention | –Serial CT comparison, clinical risk assessment, routine measurement tools, and guideline-based management without access to the trial AI report. |
Who may qualify
- Ages
- 35 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- 1. At least one persistent indeterminate pulmonary nodule measuring 6 to 30 mm on the latest clinically obtained CT; solid, part-solid, and pure ground-glass nodules are eligible. 2. Two CT examinations in total are already available: the latest within 30 days before randomization and an earlier examination 3 to 24 months before it. Both meet the frozen image-quality requirements for longitudinal comparison. 3. The current decision between continued surveillance and further investigation remains unresolved, with no mandatory urgent procedure or committed definitive treatment before randomization.
- 4. The patient is potentially eligible for curative treatment if cancer is diagnosed, with an estimated life expectancy of at least five years independent of the study nodule. 5. Written informed consent and willingness to permit record retrieval and five-year contact.
Key exclusion criteria (2 listed)
- 1.Definitive diagnosis or previous treatment of the target nodule; overt metastatic disease, suspicious adenopathy requiring urgent work-up, or another indication making delayed evaluation inappropriate. 2.Active malignancy or cancer treatment within the preceding five years, except definitively treated nonmelanoma skin cancer or in situ cervical cancer.
- 3. Clinically important immunocompromise or active pulmonary infection requiring a separate diagnostic pathway. 4. Current participation in an organized lung-cancer screening program with a mandated management pathway incompatible with this trial. 5. CT quality or acquisition differences prevent valid longitudinal evaluation; a clearly benign lesion does not require a diagnostic management decision. 6. Known pregnancy; a conflicting interventional trial; prior randomization in this study; or consent cannot be obtained.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule ManagementAI software analyzes serial clinically acquired chest CT scans to match pulmonary nodules, quantify changes in volume and solid components, and provide malignancy or invasiveness risk estimates. Intervention-arm clinicians review the AI report alongside CT images during management consultations. The baseline report is targeted within one working day after randomization. The same locked model is reapplied to clinically indicated follow-up CT scans during the 24-month intervention period. Clinicians retain responsibility for final decisions; AI findings cannot independently override clinically indicated evaluation. If processing fails or images are unsuitable, usual care proceeds. Both arms follow the same structured nodule-management pathway, but the control arm has no access to trial AI reports. | Device | AI-Assisted Longitudinal Nodule Management |
Primary outcome
Lung Resection Yielding Benign Pathology Within 24 Months
Time frame: Randomization through month 24. Procedures performed in this window are included even if their final pathology report is completed shortly afterward.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2026.
- Individual participant dataSharing planned: Yes. Through controlled access under compatible consent and institutional authorization
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management in people with Pulmonary Nodules and Lung Neoplasms, run by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 26 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Xiaoyu Han (+86 18202771604, xiaoyuhan1123@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Lung Resection Yielding Benign Pathology Within 24 Months (time frame: Randomization through month 24. Procedures performed in this window are included even if their final pathology report is completed shortly afterward.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Oct 2026.