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Computer Prediction of Restenosis Following Peripheral Angioplasty

This study has suspended participant recruitment.
(lack of funding)
Sponsor:
ClinicalTrials.gov Identifier:
NCT01202344
First Posted: September 15, 2010
Last Update Posted: October 25, 2016
The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
Information provided by (Responsible Party):
Dheeraj Rajan, University Health Network, Toronto
  Purpose
The purpose of this study is to develop a computer program that might be able to accurately assess the risk of artery re-narrowing following angioplasty or stenting based on computer images. After angioplasty (a procedure to re-open narrowed or blocked blood vessels) the patients will have extra images taken in order to assess the results of the procedure; which will then be used to see whether or not these images can help predict outcomes such as the patient having to come back to the hospital to have the procedure done again.

Condition Intervention
Peripheral Angioplasty Other: Additional x-ray images

Study Type: Interventional
Study Design: Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Diagnostic
Official Title: Computer Prediction of Restenosis Following Peripheral Angioplasty

Resource links provided by NLM:


Further study details as provided by Dheeraj Rajan, University Health Network, Toronto:

Primary Outcome Measures:
  • Simulation Accuracy [ Time Frame: less than 6 hours after the procedure ]
    From the pre-intervention CT-scans, the target artery, calcium and lumen will be segmented, meshed and used to simulate the angioplasty steps. Simulation accuracy will be evaluated by comparing geometrical descriptors of the artery and lumen size and shape calculated in the simulation to those measured on the post-intervention CT scan images.


Secondary Outcome Measures:
  • Logistic Regression Analysis [ Time Frame: 6 months ]

    Logistic regression analysis will be performed using NCSS statistical software to identify which explanatory variable(s), selected from the simulation results, can be used to predict binary restenosis, the categorical dependent variable.

    Binary restenosis will be determined by comparing the CT-scan images obtained 1 hour post-intervention to those obtained at the 6 month follow-up study.



Estimated Enrollment: 15
Study Start Date: September 2010
Estimated Primary Completion Date: December 2017 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
Restenosis
Patients who have restinosis immediately following angioplasty.
Other: Additional x-ray images
Approximately 3 additional x-ray images following angioplasty (within 1 hour)
No Restenosis
Patients who do not have restinosis immediately following angioplasty.
Other: Additional x-ray images
Approximately 3 additional x-ray images following angioplasty (within 1 hour)

Detailed Description:

The study involves medical imaging of patients undergoing an angioplasty intervention in a peripheral artery. It is similar to an observational study, except that additional imaging is performed which is above the standard-of-care. Some risks may be associated with the additional imaging due to a small increase in radiation exposure and intravenous contrast administration. No investigational drug or device will be tested in this study. No control group will be used.

Logistic regression analysis will be performed using NCSS statistical software to identify which explanatory variable(s), selected from the simulation results, can be used to predict binary restenosis, the categorical dependent variable.

For each subject, binary restenosis will be determined by comparing the CT-scan images obtained 1 hour post-intervention to those obtained at the 6 month follow-up study. The CT-scan images will be segmented and a mesh of the target vessel will be reconstructed as described in objective 1. The lumen area will be measured in every cross-section of the mesh perpendicular to the vessel centerline, with 2 mm steps between cross-sections. The minimum lumen diameter will be calculated from the minimum lumen area. If the minimum lumen diameter at follow-up is less than 50% of the minimum lumen diameter post-intervention, then the binary restenosis is positive. Otherwise it is negative.

Objective 1: Evaluate the accuracy of computer predictions of artery dilatation and stent implantation from CT-scan images. This information is hypothesized to be indicative of the accuracy of other quantities predicted by computer simulation of angioplasty, such as those used as independent variables in objective 2.

Objective 2: Establish a regression model with 80% sensitivity and 80% specificity for predicting binary restenosis based on one or several injury parameters in patients undergoing angioplasty. The candidate injury parameters are:

  • endothelium denudation (in % of total endothelium area)
  • descriptors of the magnitude and spatial distribution of stretch ratio in the arterial wall
  • descriptors of the magnitude and spatial distribution of intramural stress in the arterial wall All injury parameters are predicted by computer simulation of angioplasty.
  Eligibility

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • scheduled for percutaneous dilation of a peripheral artery;
  • age more than 18 years;
  • informed consent signed by the subject;
  • target lesion in native artery;
  • baseline lumen diameter greater than 4 mm.

Exclusion Criteria:

  • previous revascularization of the target lesion;
  • subject undergoing chemotherapy.
  Contacts and Locations
Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01202344


Locations
Canada, Ontario
University Health Network
Toronto, Ontario, Canada, M5G 2C4
Sponsors and Collaborators
Dheeraj Rajan
Investigators
Principal Investigator: Dheeraj Rajan, MD University Health Network, Toronto
  More Information

Publications:

Responsible Party: Dheeraj Rajan, Associate Professor, University Health Network, Toronto
ClinicalTrials.gov Identifier: NCT01202344     History of Changes
Other Study ID Numbers: 08-0335-BE
First Submitted: September 10, 2010
First Posted: September 15, 2010
Last Update Posted: October 25, 2016
Last Verified: October 2016

Keywords provided by Dheeraj Rajan, University Health Network, Toronto:
Angioplasty
Stenosis
Restenosis
Elastic Recoil
cheduled for percutaneous dilation of a peripheral artery
Target lesion in native artery
Baseline lumen diameter greater than 4 mm