Pulmonary EmbolismNCT06526468
Chinese PE Multimodality Imaging Artificial Intelligence Study
An observational study of Pulmonary Embolism and Chronic Thromboembolic Pulmonary Hypertension, run by China-Japan Friendship Hospital at 1 site in China.
Trial summary
The CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study (CHOICE) is a prospective observational multi-center study that will collect imaging text data and raw data of patients with pulmonary embolism (PE) in China. Read more about this study
- Who is it for?
- Ages 14 years and older
- Conditions the study is for
- Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Chronic Thromboembolic Pulmonary Disease
- What is being tested?
- Artificial Intelligence
- Type of treatment
- Medical device
- How many people
- 1,500 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2010to 1 Sep 2028
- Phase
- Observational
- 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 14 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients suspected of PE in China
Who may be able to join
- 14 Years and older
- Patients suspected of PE
Who cannot join
- Pregnant women
- Refuse to follow up
- Incomplete or discontinued imaging scans
- Insufficient quality of image data to allow for analysis
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
China-Japan Frendship hospital
Beijing, 100029
Min Liu, PhD, +86-10-84205056, mikie0763@126.com
Zhenguo Zhai, PhD, +86-10-84206269, zhaizhenguo2011@126.com
About this study
Official title: CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study
The CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study (CHOICE) is a prospective observational multi-center study that will collect imaging text data and raw data of patients with pulmonary embolism (PE) in China. By combining artificial intelligence technology, it aims to identify imaging markers to assist in early diagnosis, differential diagnosis, risk stratification, and prognosis assessment of PE.
Read the detailed description
Pulmonary embolism (PE) represents a significant public health issue. Timely diagnosis and treatment during the acute phase, as well as appropriate long-term follow-up strategies, are crucial for the management of PE. PE is classified into three stages based on disease course: acute pulmonary embolism (APE), chronic thromboembolic pulmonary disease (CTEPD), and chronic thromboembolic pulmonary hypertension (CTEPH). APE can cause acute right ventricular failure and death if not diagnosed and treated early. CTEPD has the potential to significantly impair patients' quality of life. CTEPH is a rare and potentially life-threatening long-term sequelae of PE, characterized by persistent obstruction of pulmonary arteries by organized clots, leading to redistribution of blood flow and secondary remodeling of the pulmonary microvasculature. Early identification of PE and implementation of targeted treatment plans will significantly improve survival rates and prognosis.
Multimodal imaging tests play a crucial role in the management of PE (including computed tomography pulmonary angiography (CTPA), magnetic resonance imaging (MRI), echocardiography, and lung ventilation/perfusion (V/Q) scan). The guidelines have identified the right ventricle to left ventricle (RV:LV) ratio >1.0 on CTPA or right heart dysfunction signs from echocardiography as important indicators for risk stratification of APE. Patients stratified as high risk require closer monitoring in an inpatient setting. Whereas, those stratified as low risk are suitable for early discharge.
Therefore, exploring novel imaging markers and integrating these markers into radiology reports may have potential clinical significance. If no quantifiable evidence of right ventricular dysfunction is provided to clinicians to make treatment decisions, patients with high-risk APE may be considered "low-risk" and discharged home. In addition, patients with low-risk APE may require longer hospital stays and may not need to be hospitalized, which undoubtedly increases healthcare costs. For patients with CTEPD or CTEPH, treatment options are diverse, including multimodal therapies such as pulmonary endarterectomy, balloon pulmonary angioplasty and targeted medical therapy. Therefore, multimodal imaging evaluation is meaningful for clinical treatment decision-making and efficacy monitoring. Combined with artificial intelligence (AI) technology, it can provide a variety of metrics to assist in evaluating clots morphology, pulmonary ventilation-perfusion function, cardiac function, hemodynamics, and more. AI can not only assist in finding more clinically significant imaging biomarkers but also customize standardized radiology reports, which are expected to address the current challenges.
This study is a multi-center real-world study aimed at exploring novel imaging markers in combination with AI technology and integrating them into a software for clinical application to provide quantitative parameters, using imaging reports and raw data from Chinese patients with PE. It is hypothesized that AI technology can improve early diagnosis, differential diagnosis, risk stratification, and management of PE by increasing the ability to accurately evaluate PE in a real-world clinical setting. The researchers also hypothesized that the integration of AI technologies would be cost-effective and acceptable to radiologists and clinicians.
- Conditions
- Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Chronic Thromboembolic Pulmonary Disease
- Being tested
- Artificial Intelligence
- Keywords
- imaging, early diagnosis, differential diagnosis, risk stratification, prognosis assessment
- Medical subject headings
- Pulmonary Embolism, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial IntelligenceDevice
AI technology will provide novel imaging markers and generate a radiology report with relevant key slice imaging and evaluation results
| Study group | Role | What they receive |
|---|---|---|
| Acute pulmonary embolism cohort | 1. Patients objectively confirmed acute symptomatic PE or PE with deep vein thrombosis (DVT)
2. PE was confirmed by CTPA, lung V/Q scan or pulmonary angiography. Receives: Device: Artificial Intelligence | |
| Chronic thromboembolic pulmonary disease without pulmonary hypertension cohort | 1. Patients with functional impairment despite 3 months of adequate anticoagulation therapy after APE.
2. CTPA/ pulmonary angiography or V/Q scan showed unresolved thrombi in the pulmonary vessels.
3. Without pulmonary hypertension at rest(mean pulmonary arterial pressure (mPAP) <20 mmHg), as measured by right heart catheterization. Receives: Device: Artificial Intelligence | |
| Chronic thromboembolic pulmonary hypertension cohort | 1. Patients with functional impairment despite 3 months of adequate anticoagulation therapy
2. CTPA/ pulmonary angiography or V/Q scan showed unresolved thrombi in the pulmonary vessels.
3. With pulmonary hypertension at rest (mean pulmonary arterial pressure (mPAP) >20 mmHg), as measured by right heart catheterization. Receives: Device: Artificial Intelligence | |
| Other pulmonary vascular disease cohort | Patients diagnosed with other pulmonary vascular disease including Takayasu arteritis, pulmonary artery sarcoma, and fibrosing mediastinitis. Receives: Device: Artificial Intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic rate of PE
Comparison before and after AI technique.
Measured: 2 years
APE risk stratification rates (low, intermediate low, intermediate high and high risk)
Comparison before and after AI technique.
Measured: 2 years
Disease severity of chronic thromboembolic pulmonary disease (CTEPD)/chronic thromboembolic pulmonary hypertension (CTEPH)
Comparison before and after AI technique. Assessment of disease severity is comprehensive, referring to the comprehensive risk assessment in pulmonary arterial hypertension (three-strata model) [DOI: 10.1183/13993003.00879-2022], including clinical observations and modifiable variables. The higher the score, the more severe the condition.
Measured: 2 years
30 day mortality
Patient mortality (death) at 30-days post-PE diagnosis. Comparison before and after AI technique.
Measured: 2 years
Secondary outcomes (6)
Rate of discordant PE cases
False positive and false negative rate
Measured: 2 years
AI failure rate for PE detection
Proportion of scans unable to be interpreted by AI despite suitable CTPA acquisition
Measured: 2 years
12 month mortality
Patient mortality (death) at 12-months post-PE diagnosis. Comparison before and after AI technique.
Measured: 2 years
Length of hospital stay for PE
Comparison before and after AI technique. Measured as number of days from admission to time of discharge from hospital.
Measured: 2 years
Time from symptom onset to final diagnosis
Comparison before and after AI technique.
Measured: 3 months
Hospitalization cost for PE using Markov model
Comparison before and after AI technique.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jul 2024
- Study start1 Sep 2010
- Primary completion1 Sep 2027 (estimated)
- Study completion1 Sep 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Pulmonary EmbolismStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- China-Japan Friendship Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Zhenguo Zhai,MD,PhD, China-Japan Friendship Hospital
- Investigators
- Zhenguo Zhai, PhD, Study director, China-Japan Friendship Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06526468
- Sponsor's protocol ID
- CHOICE
- Status last verified
- Aug 2024
- First submitted
- 15 Jun 2024
- Last updated
- 28 Aug 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Information gathered for this study will not be disclosed to any other person or entity, or for other research.
Publications
Xi L, Wang J, Liu A, Ni Y, Du J, Huang Q, Li Y, Wen J, Wang H, Zhang S, Zhang Y, Zhang Z, Wang D, Xie W, Gao Q, Cheng Y, Zhai Z, Liu M. Development of a lung perfusion automated quantitative model based on dual-energy CT pulmonary angiography in patients with chronic pulmonary thromboembolism. Insights Imaging. 2025 Aug 18;16(1):182. doi: 10.1186/s13244-025-02067-6.
PubMed 40825922
Study at a glance
From the registry record, last updated by the sponsor on 28 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study
- ClinicalTrials.gov ID
- NCT06526468
- Acronym / sponsor ID
- CHOICE
- Conditions
- Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Chronic Thromboembolic Pulmonary Disease
- Keywords
- imaging, early diagnosis, differential diagnosis, risk stratification, prognosis assessment
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- China-Japan Friendship HospitalUniversity, hospital or other
- Study start
- 1 Sep 2010 (actual)
- Primary completion
- 1 Sep 2027 (estimated)
- Study completion
- 1 Sep 2028 (estimated)
- First posted
- 29 Jul 2024 (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.
The CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study (CHOICE) is a prospective observational multi-center study that will collect imaging text data and raw data of patients with pulmonary embolism (PE) in China. By combining artificial intelligence technology, it aims to identify imaging markers to assist in early diagnosis, differential diagnosis, risk stratification, and prognosis assessment of PE.
Detailed description
Pulmonary embolism (PE) represents a significant public health issue. Timely diagnosis and treatment during the acute phase, as well as appropriate long-term follow-up strategies, are crucial for the management of PE. PE is classified into three stages based on disease course: acute pulmonary embolism (APE), chronic thromboembolic pulmonary disease (CTEPD), and chronic thromboembolic pulmonary hypertension (CTEPH). APE can cause acute right ventricular failure and death if not diagnosed and treated early. CTEPD has the potential to significantly impair patients' quality of life. CTEPH is a rare and potentially life-threatening long-term sequelae of PE, characterized by persistent obstruction of pulmonary arteries by organized clots, leading to redistribution of blood flow and secondary remodeling of the pulmonary microvasculature. Early identification of PE and implementation of targeted treatment plans will significantly improve survival rates and prognosis.
Multimodal imaging tests play a crucial role in the management of PE (including computed tomography pulmonary angiography (CTPA), magnetic resonance imaging (MRI), echocardiography, and lung ventilation/perfusion (V/Q) scan). The guidelines have identified the right ventricle to left ventricle (RV:LV) ratio >1.0 on CTPA or right heart dysfunction signs from echocardiography as important indicators for risk stratification of APE. Patients stratified as high risk require closer monitoring in an inpatient setting. Whereas, those stratified as low risk are suitable for early discharge.
Therefore, exploring novel imaging markers and integrating these markers into radiology reports may have potential clinical significance. If no quantifiable evidence of right ventricular dysfunction is provided to clinicians to make treatment decisions, patients with high-risk APE may be considered "low-risk" and discharged home. In addition, patients with low-risk APE may require longer hospital stays and may not need to be hospitalized, which undoubtedly increases healthcare costs. For patients with CTEPD or CTEPH, treatment options are diverse, including multimodal therapies such as pulmonary endarterectomy, balloon pulmonary angioplasty and targeted medical therapy. Therefore, multimodal imaging evaluation is meaningful for clinical treatment decision-making and efficacy monitoring. Combined with artificial intelligence (AI) technology, it can provide a variety of metrics to assist in evaluating clots morphology, pulmonary ventilation-perfusion function, cardiac function, hemodynamics, and more. AI can not only assist in finding more clinically significant imaging biomarkers but also customize standardized radiology reports, which are expected to address the current challenges.
This study is a multi-center real-world study aimed at exploring novel imaging markers in combination with AI technology and integrating them into a software for clinical application to provide quantitative parameters, using imaging reports and raw data from Chinese patients with PE. It is hypothesized that AI technology can improve early diagnosis, differential diagnosis, risk stratification, and management of PE by increasing the ability to accurately evaluate PE in a real-world clinical setting. The researchers also hypothesized that the integration of AI technologies would be cost-effective and acceptable to radiologists and clinicians.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Acute pulmonary embolism cohort | – | Device: Artificial Intelligence1. Patients objectively confirmed acute symptomatic PE or PE with deep vein thrombosis (DVT) 2. PE was confirmed by CTPA, lung V/Q scan or pulmonary angiography. |
| Chronic thromboembolic pulmonary disease without pulmonary hypertension cohort | – | Device: Artificial Intelligence1. Patients with functional impairment despite 3 months of adequate anticoagulation therapy after APE. 2. CTPA/ pulmonary angiography or V/Q scan showed unresolved thrombi in the pulmonary vessels. 3. Without pulmonary hypertension at rest(mean pulmonary arterial pressure (mPAP) <20 mmHg), as measured by right heart catheterization. |
| Chronic thromboembolic pulmonary hypertension cohort | – | Device: Artificial Intelligence1. Patients with functional impairment despite 3 months of adequate anticoagulation therapy 2. CTPA/ pulmonary angiography or V/Q scan showed unresolved thrombi in the pulmonary vessels. 3. With pulmonary hypertension at rest (mean pulmonary arterial pressure (mPAP) >20 mmHg), as measured by right heart catheterization. |
| Other pulmonary vascular disease cohort | – | Device: Artificial IntelligencePatients diagnosed with other pulmonary vascular disease including Takayasu arteritis, pulmonary artery sarcoma, and fibrosing mediastinitis. |
Who may qualify
- Ages
- 14 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients suspected of PE in China
Key inclusion criteria (2 listed)
- 14 Years and older
- Patients suspected of PE
Key exclusion criteria (4 listed)
- Pregnant women
- Refuse to follow up
- Incomplete or discontinued imaging scans
- Insufficient quality of image data to allow for analysis
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 |
|---|---|---|
| Artificial IntelligenceAI technology will provide novel imaging markers and generate a radiology report with relevant key slice imaging and evaluation results | Device | Acute pulmonary embolism cohort, Chronic thromboembolic pulmonary disease without pulmonary hypertension cohort, Chronic thromboembolic pulmonary hypertension cohort, Other pulmonary vascular disease cohort |
Primary outcome
Diagnostic rate of PE
Time frame: 2 years
Comparison before and after AI technique.
APE risk stratification rates (low, intermediate low, intermediate high and high risk)
Time frame: 2 years
Comparison before and after AI technique.
Disease severity of chronic thromboembolic pulmonary disease (CTEPD)/chronic thromboembolic pulmonary hypertension (CTEPH)
Time frame: 2 years
Comparison before and after AI technique. Assessment of disease severity is comprehensive, referring to the comprehensive risk assessment in pulmonary arterial hypertension (three-strata model) [DOI: 10.1183/13993003.00879-2022], including clinical observations and modifiable variables. The higher the score, the more severe the condition.
30 day mortality
Time frame: 2 years
Patient mortality (death) at 30-days post-PE diagnosis. Comparison before and after AI technique.
6 secondary outcomes
Rate of discordant PE cases
Time frame: 2 years
AI failure rate for PE detection
Time frame: 2 years
12 month mortality
Time frame: 2 years
Length of hospital stay for PE
Time frame: 2 years
Time from symptom onset to final diagnosis
Time frame: 3 months
Hospitalization cost for PE using Markov model
Time frame: 2 years
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 28 Aug 2024.
- Derived from this study: PubMed 40825922Xi L, Wang J, Liu A, Ni Y, Du J, Huang Q, Li Y, Wen J, Wang H, Zhang S, Zhang Y, Zhang Z, Wang D, Xie W, Gao Q, Cheng Y, Zhai Z, Liu M. Development of a lung perfusion automated quantitative model based on dual-energy CT pulmonary angiography in patients with chronic pulmonary thromboembolism. Insights Imaging. 2025 Aug 18;16(1):182. doi: 10.1186/s13244-025-02067-6.
- Individual participant dataSharing planned: No. Information gathered for this study will not be disclosed to any other person or entity, or for other research.
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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.
Zhenguo Zhai, PhD study director
China-Japan Friendship Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Embolism and Chronic Thromboembolic Pulmonary Hypertension, run by China-Japan Friendship Hospital 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 4 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 28 Aug 2024. 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 Min Liu, PhD (+86-10-84205056, mikie0763@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic rate of PE (time frame: 2 years). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06526468, which also lists 1 linked publication.
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 28 Aug 2024.