Ignite Creation Date:
2024-10-26 @ 3:36 PM
Last Modification Date:
2024-10-26 @ 3:36 PM
Study NCT ID:
NCT06526468
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-06-15
Brief Title:
Chinese PE Multimodality Imaging Artificial Intelligence Study
Sponsor:
None
Organization:
None
Study Overview
Official Title:
CHinese pulmOnary Embolism Multimodality Imaging-artifiCial intelligencE Study
Status:
RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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 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 ventilationperfusion VQ scan The guidelines have identified the right ventricle to left ventricle RVLV ratio 10 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
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 ventilationperfusion VQ scan The guidelines have identified the right ventricle to left ventricle RVLV ratio 10 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 Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None