Prospective Registry of Patients Undergoing Cardiac CT With NAEOTOM Alpha PCD-CT Before TAVI Procedure
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorSemmelweis University
About this trial
The clinical and demographic characteristics of patients undergoing transcatheter aortic valve implantation (TAVI) pose unique challenges for coronary computed tomography (CT) imaging, as this patient population is mainly composed of elderly, frail individuals with severe aortic stenosis, multiple comorbidities, high prevalence of heavily calcified coronary artery disease (CAD) and revascularized coronary arteries. Such vulnerable patients could benefit from a more precise assessment and characterization of their CAD with ultra-high resolution (UHR) photon-counting detector (PCD) CT that would potentially avoid the need for pre-implantation invasive coronary angiography (ICA). This international multicenter prospective registry study aims to investigate the feasibility and diagnostic accuracy of PCD-CT in the assessment of CAD in the high-risk population of patients undergoing TAVI, as compared to ICA.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Clinically indicated TAVI
Clinically indicated CT and invasive coronary angiography
There are no contraindications to CT angiography.
Understanding and signing the consent form
Disqualifiers
Pregnancy or breastfeeding
Chronic renal failure (eGFR <30 ml/m2)
Active oncological treatment
Any condition for which TAVI is contraindicated and therefore no prior radiological investigation of TAVI is indicated
Trial population
Consecutive patients with aortic valve stenosis for whom TAVI is indicated and who present for pre-operative investigation.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Ultra-High Resolution Photon Counting Detector Coronary Computed Tomography Angiography
Diagnostic testClinically indicated Ultra-High Resolution Photon-Counting Detector Coronary Computed Tomography Angiography (UHR PCD-CT CCTA) for the pre-procedural evaluation of patients scheduled to undergo transcatheter aortic valve implantation.
Treatment groups
1,000 Participants
are divided into 1 treatment groupGroup A: Aortic stenosis1 intervention
Trial outcomes
Primary outcomes
1
Diagnostic Accuracy of Ultra-High Resolution Photon-Counting Detector Coronary Computed Tomography Angiography (UHR PCD-CT CCTA)
Assessment of the diagnostic accuracy (sensitivity, specificity, PPV, NPV) of UHR PCD-CT coronary angiography as compared to invasive coronary angiography (ICA) within three months of PCD-CT
Time frame
through study completion, an average of 2 yearsSecondary outcomes
1
Image Noise Analysis Across Reconstruction Parameters
Quantitative assessment of image noise (measured in HU) in CT images reconstructed with varying parameters, including reconstruction kernel type, quantum iterative reconstruction (QIR) levels, and slice thickness.
Time frame
through study completion, an average of 2 years2
Correlation of Image Noise and Body Mass Index
Correlation of image noise (measured in HU) and body mass index (kg/m2) across different image reconstruction parameters, including kernel type, quantum iterative reconstruction (QIR) level, and slice thickness.
Time frame
through study completion, an average of 2 years3
Correlation of Image Noise and Heart Rate
Correlation of image noise (measured in HU) and heart rate (bpm) across different image reconstruction parameters, including kernel type, quantum iterative reconstruction (QIR) level, and slice thickness.
Time frame
through study completion, an average of 2 years4
Contrast-to-Noise Ratio (CNR) Analysis Across Reconstruction Parameters
Quantitative assessment of contrast-to-noise ratio (unitless) in CT images reconstructed with varying parameters, including reconstruction kernel type, quantum iterative reconstruction (QIR) levels, and slice thickness.
Time frame
through study completion, an average of 2 yearsSponsors and contacts
Click on the lead sponsor to view all of their trials.
Semmelweis University
Lead sponsor
Siemens Corporation, Corporate Technology
Collaborator
Source ClinicalTrials.gov