Ignite Creation Date:
2024-07-17 @ 11:57 AM
Last Modification Date:
2024-10-26 @ 3:34 PM
Study NCT ID:
NCT06498830
Status:
RECRUITING
Last Update Posted:
2024-07-12
First Post:
2024-07-06
Brief Title:
Application of CTA-based Radiomic Phenotyping of PCAT and Fluid Dynamics in Atherosclerotic Disease APPLE
Sponsor:
Jinling Hospital China
Organization:
Jinling Hospital China
Study Overview
Official Title:
Application of CTA-based Radiomic Phenotyping of Peri-coronary Adipose Tissue and Fluid Dynamics in Atherosclerotic Disease
Status:
RECRUITING
Status Verified Date:
2023-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This study APPLE study intends to retrospectively enroll more than 2000 patients who who underwent 2 coronary computed tomography angiography CCTA with 3 months interval from 11 hospitals in more than 4 provinces in China
Detailed Description:
A multicenter retrospective observational trial will be conducted APPLE study To investigate whether a combined model constructed on the basis of pericoronary adipose tissue PCAT radiomics fluid dynamics and clinical risk factors can predict the formation of atherosclerotic plaque It will be carried out in 11 hospitals in 4 provinces in China The Boruta algorithm and correlation proof clustering analysis were used to screen the imaging histological features and a random forest model was used to construct an imaging histological prediction model for PCAT and fluid dynamics and to construct radiomics score To investigate the incremental value of the radiomics score beyond the traditional prediction model the radiomics score was combined with the traditional logistic regression prediction model Receiver operating characteristic ROC curve analysis with integrated discrimination improvement IDI and category net reclassification index NRI were used to compare the performance of the predictive models A ML-prediction model incorporates FAI fluid dynamics and patient clinical characteristics to identify high-risk patients in advance for patients receiving routine CCTA and guide the more precise use of preventative treatments including anti-inflammatory therapies
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None