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Identification of Neoatherosclerosis in ISR Patients Based on Artifical Intelligence

NCT04220437 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 90

Last updated 2021-01-15

No results posted yet for this study

Summary

Based on the large population of patients, in-stent restenosis (ISR) is still an important problem in the field of cardiovascular disease. How to reduce the incidence of ISR and the treatment of ISR has become the focus and hot spot. The 2018 ESC Guidelines for Cardiovascular Intervention recommends treatment of ISR under the guidance of intravascular ultrasound (IVUS), or optical coherent tomography (OCT). Circulation published a new Waksman ISR classification based on mechanisms and components of the restenosis tissue, which provides guidance for treatment strategy. Because of its good resolution, OCT makes it more accurate to distinguish the components of vascular tissue, thus providing a decision-making basis for interventional therapy. OCT examination can obtain the characteristics of the ISR more precisely. Neoatherosclerosis (NA), is one of the ISR types and accounts for more stent failure and target lesion failure than other types. Identification NA is important for decision-making of interventional therapy. However, the acquisition and analysis of OCT images not only need the digital angiography machine (DSA) equipped with the majority of hospitals, but also need professional OCT imaging equipment and technicians. Patients with severely CKD cannot bear OCT examination because of the large amount of contrast agent. OCT catheter is more than ten times the price of the CAG catheter. Therefore, identification of NA by the use of artificial intelligence (AI) is of significance to set therapeutic strategy for ISR patients, especially in patients with CKD. Our study retrospectively analyzed CAG images and OCT images of ISR patients obtained from Jan 1st,2015 to Oct 31st,2020. Identify NA by analyzing OCT images, build up U-net and V-net to analyze the CAG and OCT images, and finally build up an identification system of NA based on CAG images by AI. This study has been approved by Ethics Committee of Chinese PLA General Hospital (S2018-033-01)

Conditions

  • In-stent Restenosis
  • Neo-atherosclerosis
  • Retrospective

Interventions

OTHER

no interventin

Our stusy analysed the images obtained from ISR patients, no extra intervention was given based on this study.

Sponsors & Collaborators

  • Chinese PLA General Hospital

    lead OTHER

Principal Investigators

  • Yundai Chen, M.D · Chinese PLA General Hospital

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2015-02-01
Primary Completion
2021-01-31
Completion
2021-02-28

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04220437 on ClinicalTrials.gov