Status
Conditions
About
This study aims to investigate the pathogenesis of Peripheral Artery Disease (PAD) and Carotid Artery Stenosis (CAS) using a comprehensive multi-omics and multi-modal imaging approach. The study will enroll patients diagnosed with PAD or CAS and perform advanced imaging techniques, including NIR-II Imaging, DUS-based V-flow Imaging, and Laser Speckle Imaging, to assess vascular structure and function. Simultaneously, single-cell transcriptomics, metabolomics, lipidomics, and proteomics analyses will be conducted on patient samples to identify key molecular targets and pathways involved in disease progression. Machine learning algorithms will be employed to integrate imaging and multi-omics data, enabling the development of predictive models for more accurate disease diagnosis and stratification. The findings from this study are expected to provide novel insights into the molecular mechanisms underlying PAD and CAS and contribute to the development of personalized therapeutic strategies.
Full description
Background and Rationale Peripheral Artery Disease (PAD) and Carotid Artery Stenosis (CAS) are prevalent vascular disorders associated with significant morbidity and mortality. Despite advances in diagnostic and therapeutic approaches, the molecular mechanisms driving these diseases remain poorly understood. This study leverages cutting-edge multi-omics technologies and advanced imaging modalities to unravel the complex pathogenesis of PAD and CAS, with the ultimate goal of identifying novel biomarkers and therapeutic targets.
Study Objectives Primary Objective: To integrate multi-modal imaging data (NIR-II Imaging, DUS-based V-flow Imaging, and Laser Speckle Imaging) with multi-omics data using machine learning algorithms for improved disease prediction and stratification.
Study Design
This is a prospective, observational study involving patients diagnosed with PAD or CAS. The study will include the following components:
Imaging Analysis:
Multi-Omics Analysis:
Imaging and multi-omics data will be integrated using advanced machine learning algorithms to develop predictive models for disease diagnosis, progression, and therapeutic response.
Study Population The study will enroll patients diagnosed with PAD or CAS, along with age- and sex-matched healthy controls. Inclusion and exclusion criteria will be applied to ensure a homogeneous study population.
Expected Outcomes
Ethical Considerations The study protocol has been reviewed and approved by the Institutional Review Board (IRB) to ensure the protection of human subjects. Informed consent will be obtained from all participants prior to their enrollment in the study.
Significance This study represents a pioneering effort to integrate multi-omics and multi-modal imaging data for a comprehensive understanding of PAD and CAS. The findings are expected to advance the field of vascular biology and contribute to the development of precision medicine approaches for these debilitating diseases.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Loading...
Central trial contact
Yijie Ning; Liuming Shi
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal