Actively Recruiting
Phenotyping Left Ventricle Failure With Hemodynamic Biomarkers From 4D Flow Magnetic Resonance Imaging
Led by IRCCS Policlinico S. Donato · Updated on 2026-03-06
190
Participants Needed
2
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are investigating advanced MRI-based techniques to improve the automatic assessment of left ventricular (LV) dysfunction in patients, particularly those with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR). The study aims to develop a deep learning model to automatically segment the LV endocardial contours from cardiac MRI images, as well as to create non-invasive methods for reconstructing pressure-volume loops and evaluating hemodynamic forces in the heart. This research includes both retrospective and prospective study arms to support model training, clinical validation, and translation into clinical practice. The study's retrospective phase involves collecting and anonymizing cardiac MRI datasets to train and test a convolutional neural network for LV segmentation. The prospective phase enrolls patients scheduled for TAVR, who will undergo non-contrast 4D Flow MRI and routine invasive hemodynamic measurements during their procedure. MRI scans include standard cine sequences and 4D Flow acquisition, performed without contrast agents. Data from these imaging and hemodynamic assessments will be processed using specialized software to analyze LV blood flow and pressure dynamics, comparing non-invasive measurements with invasive catheter data. Participants will undergo MRI scans and have hemodynamic data collected during their routine clinical care without additional interventions or risks. Researchers will evaluate the accuracy of the automatic LV segmentation and compare MRI-based pressure-volume loop parameters and hemodynamic force measurements with invasive standards. The study also plans to develop a standalone, user-friendly software application for clinical use based on the findings. There are no extra follow-up visits, and participant involvement is limited to imaging, data collection, and analysis during the study period.
CONDITIONS
Brief Title
Phenotyping Left Ventricle Failure With Hemodynamic Biomarkers From 4D Flow Magnetic Resonance Imaging
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Adult patients (age > 18 years old)
- Diagnosis of severe aortic stenosis with indication for transcatheter aortic valve replacement (TAVR)
- Severe aortic stenosis in normal/high flow or low flow status
- Signed informed written consent
You will not qualify if you...
- Contraindication to cardiac MRI due to previous ferromagnetic implants
- Poor MRI quality impairing image post-processing
- Claustrophobia
- Unwilling to sign the informed consent
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - 1 day
Participants undergo cardiac magnetic resonance imaging, including standard cine imaging and non-contrast 4D Flow MRI acquisition prior to their scheduled transcatheter aortic valve replacement (TAVR).
1 imaging session (in-person)
Duration - Day of TAVR procedure
During the TAVR procedure, participants have invasive blood pressure measurements obtained as part of standard clinical practice without additional procedures.
1 procedural visit (in-person)
Duration - Up to 1 week after TAVR
No additional follow-up visits are planned; participants receive standard clinical care following the TAVR procedure.
No additional study visits; standard clinical care applies
Trial Site Locations
Total: 2 locations
1
IRCCS Policlinico San Donato
San Donato Milanese, Italy, 20097
Actively Recruiting
2
IRCCS Policlinico San Donato
San Donato Milanese, Italy, 20097
Actively Recruiting
Research Team
G
Giandomenico Disabato, MD
F
Francesco Sturla, PhD
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NA
Model
SINGLE_GROUP
Primary Purpose
DIAGNOSTIC
Number of Arms
1
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