Principal Investigators
Regional Ultrasound Wall Strain Measurements to Predict Risk of Abdominal Aortic
Project Collaborators:
- Dr. Steven Day Rochester Institute of Technology
- Dr. Thomas Gaborski Rochester Institute of Technology
- Dr. Daniel Phillips Rochester Institute of Technology
Patient-specific AAA model and preliminary phantom.
Abdominal Aortic Aneurysm (AAA) is one of the largest preventable causes of death in the US. AAA rupture is due to material failure of the aortic wall, and the primary gap in knowledge in this area lies in the inability to predict the risk of AAA rupture based on aortic wall characteristics. This project aims to create a novel, cross-disciplinary diagnostic approach to assessing AAA rupture risk, based on enabling the further development of existing technology. This will result in a change in the clinical paradigm, and the approach to AAA diagnosis and treatment. This research is supported by, and involves collaboration from, two different institutions including two clinical, and three engineering departments.
This project involves the creation of patient-specific, echogenic AAA phantom models from 3D data collected from CT scans with the ability to capture images of the material properties of the human aorta through transcutaneous ultrasound.
GE Vivid-I strain package examining a normal human aorta.
The patient-specific phantom models are then used to create a strain fingerprint
with the potential to predict vulnerable, high risk AAA with transcutaneous ultrasound. To create this fingerprint
, failure of the phantom is tested on a hemodynamic simulator to determine hemodynamic parameters and likely anatomic locations for rupture. An ultrasound is used to measure the phantom AAA wall strain in order to characterize the changes in regional strain preceding rupture.
