ClinicalTrials.Veeva

Menu

Classification of Carotid Plaque With Computed Tomography With Fast kVp (Kilovolt Peak)-Switching Technique

Karolinska Institute logo

Karolinska Institute

Status

Completed

Conditions

Carotid Stenosis
Atherosclerosis

Treatments

Other: Carotid endarterectomy in clinical healthcare.

Study type

Observational

Funder types

Other

Identifiers

NCT02436967
SN 020 DECTA

Details and patient eligibility

About

Classification of carotid plaque vessel wall changes in carotid stenosis accordingly to AHA classification (American Heart Association)- comparison between histology and CT. The CT is performed with a fast kVp-switching dual energy technique.

To compare the ability to detect iodine contrast enhancement in the carotid plaque compared with 3T MRI with gadolinium.

Full description

Patients planned for CEA (carotid endarterectomy) due to carotid stenosis will be examined with one extra CT and MRI before surgery. The CEA specimen is stored in the BiKE-registry (a biobank of operated carotid plaque at the Karolinska Institute). In that registry the patients will be given a personal code which is used to identify the CT, MRI and histology data further on.

Approved by regional ethical review board in Stockholm and local radiation comity at Karolinska University Hospital Solna (Dnr K2435-2014). Informed consent from the participating patients.

Enrollment

31 patients

Sex

All

Ages

50+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • 50% stenosis (NASCET) or more based on CTA (CT-angiography),
  • MRI or US,
  • Scheduled for CEA
  • 50 years or older,
  • Normal kidney function (estimated GFR (glomerular filtration rate) 60 ml/min or more).

Exclusion criteria

  • Contraindications to iodine contrast media,
  • Contraindications to MRI or gadolinium contrast media.

Trial contacts and locations

1

Loading...

Central trial contact

Staffan Holmin, Professor

Data sourced from clinicaltrials.gov

Clinical trials

Find clinical trialsTrials by location
© Copyright 2026 Veeva Systems