University of Pittsburgh researchers are developing an augmented reality (AR) approach that will allow clinicians and patients to visualize the biomechanical wall stresses related to cardiovascular disease (CVD) in real time. This novel technology would allow clinicians to assess the risk of aneurysm in patients, improve clinical decision-making, and reduce the risk of fatal wall rupture.
Description
Aneurysms, (irreversible dilation of an artery) can rupture, leading to death and other catastrophic consequences for the patient. Clinicians currently use medical imaging to assess the risk of rupture based on thresholds for the diameter of the blood vessel, but nearly a quarter of abdominal aortic aneurysms can rupture below these thresholds. AR is increasingly used in various areas of medicine, from training to surgical planning. Allowing enhanced human-computer interactions, AR users can manipulate images using gestures, speech, clicks, and physical objects for a 360 visualization of structures. These visualizations offer additional sensory feedback regarding patient status. With the pressing clinical need to develop more accurate and timely methods to assess the risk of aneurysm rupture, AR offers the potential to improve clinical decision-making for patients with CVD and additionally provide them with a better understanding of their condition, thus empowering their health decisions.
Applications
- Brain aneurysm
- Abdominal aortic aneurysm
- Cardiovascular disease
- Other vascular diseases
Advantages
Clinicians currently have some tools to predict risk of rupture, but they are time- and resource-intensive. These tools require manual segmentation of computerized tomography angiography (CTA) images of the artery of interest, meshing reconstructed geometries, manually inputting data, and performing computation simulations—requiring time, resources, and expertise.
This novel AR approach builds on a newly developed prediction tool that can use medical images to reconstruct the surface of the blood vessel of interest and determine biomechanical wall stress. Based on this information and machine learning, the resulting AR imagery will allow clinicians to analyze the condition of the blood vessel and predict the risk of rupture. This detailed imagery can also be shared with the patient. Given that patients prefer to visualize their diagnosis, AR is ideal for helping them to understand their condition so they can make well-informed health decisions.
Invention Readiness
Previous research and development have led to an AI-based risk prediction tool for aneurysm rupture using millions of distinct data points to create medical images. Data from an updated version of this prediction tool was used to develop a prototype multimodal AR system. Images containing heat maps of wall stress are viewed in 3D, allowing clinicians to assess the artery and improve clinical decision-making. Work is now required to further optimize this approach.
IP Status
https://patents.google.com/patent/US20240303804A1
