An observational study in Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension and Chronic Thromboembolic Pulmonary Disease, sponsored by China-Japan Friendship Hospital. Recruiting at 1 site in China. Open to participants aged 14 Years and older. Per ClinicalTrials.gov, last updated 2024-08-28.
Sponsored by China-Japan Friendship Hospital · Observational
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.
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.
832 studies on the registry are indexed under Pulmonary Embolism; 171 are open to participants now.
This study's planned enrollment of 1,500 is above the median of 361 across 366 observational studies indexed under Pulmonary Embolism.
Browse Pulmonary Embolism studies →China-Japan Friendship Hospital is the lead sponsor of 178 studies on the registry; 111 are open to participants now.
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Patients suspected of PE in China
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
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.
Device: Artificial Intelligence
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.
Device: Artificial Intelligence
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.
Device: Artificial Intelligence
Patients diagnosed with other pulmonary vascular disease including Takayasu arteritis, pulmonary artery sarcoma, and fibrosing mediastinitis.
Device: Artificial Intelligence
AI technology will provide novel imaging markers and generate a radiology report with relevant key slice imaging and evaluation results
Diagnostic rate of PE
Comparison before and after AI technique.
Time frame: 2 years
APE risk stratification rates (low, intermediate low, intermediate high and high risk)
Comparison before and after AI technique.
Time frame: 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.
Time frame: 2 years
30 day mortality
Patient mortality (death) at 30-days post-PE diagnosis. Comparison before and after AI technique.
Time frame: 2 years
Rate of discordant PE cases
False positive and false negative rate
Time frame: 2 years
AI failure rate for PE detection
Proportion of scans unable to be interpreted by AI despite suitable CTPA acquisition
Time frame: 2 years
12 month mortality
Patient mortality (death) at 12-months post-PE diagnosis. Comparison before and after AI technique.
Time frame: 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.
Time frame: 2 years
Time from symptom onset to final diagnosis
Comparison before and after AI technique.
Time frame: 3 months
Hospitalization cost for PE using Markov model
Comparison before and after AI technique.
Time frame: 2 years
Plan to share: No — Information gathered for this study will not be disclosed to any other person or entity, or for other research.
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