
ANEURISK
Science & Technology
Delivering decades of science in a single click
This page offers a concise overview of Aneurisk’s scientific foundation and technological capabilities, serving as a digestible introduction to our work. For those interested in a deeper understanding, links to peer-reviewed journal articles are provided throughout.
The Biomechanics of Abdominal Aortic Aneurysm
Chief Scientific Officer David Vorp, PhD, is a world-leading expert in abdominal aortic aneurysms, with over $30 million in AAA research funding and more than 6,000 citations. He pioneered widely adopted computational and experimental biomechanic methods to assess AAA rupture risk. His development of the Rupture Potential Index (RPI) enables patient-specific risk profiling by comparing wall stress to aneurysm strength derived from ex-vivo testing.

Rupture Risk
Morphological Analyses: More than a Diameter

For over 60 years, AAA treatment decisions have relied on a single threshold - maximum diameter - despite many ruptures occurring below it. Through over 160 clinician interviews, the Aneurisk team confirmed that vascular surgeons find this one-dimensional approach insufficient. By leveraging CT imaging, Aneurisk extracts detailed 1D, 2D, and 3D morphological features from patient-specific AAA geometry to provide a more comprehensive risk assessment.
Artificial Intelligence Enters the Conversation
Artificial intelligence is transforming image-based aneurysm analysis. Timothy Chung, PhD, Aneurisk's CTO, developed an AI framework to predict wall stress directly from medical images, dramatically accelerating biomechanical analysis that can traditionally take up to 24 hours per patient. These models maintain high accuracy while eliminating the need for manual segmentation and complex simulations.

AI allows us to rapidly scale image analysis while improving model accuracy through ongoing validation with a growing dataset. The Aneurisk approach enables clinicians and patients to see wall stresses from medical images with the click of a button.
Classifying AAA Patient Outcomes with Machine Learning
Aneurisk's founding team was brought together through a Pittsburgh Health Data Alliance project that combined biomechanical, morphological, and clinical data to predict aneurysm outcomes (stability, repair, or rupture) over an average 5-year follow-up in 381 patients.
The classification model gives clinicians a high-level view of risk, enabling more precise treatment timing and personalized surveillance. By identifying high-risk patients earlier, Aneurisk has the potential to cut rupture events in half.
Select Biomechanics Publications
1) In Vivo 3D Surface Geometry of AAA (1999)
2) Toward a biomechanical tool to evaluate rupture potential of AAA (2000)
3) Wall stress distribution on 3D human AAA (2000)
4) Association of Intraluminal Thrombus in AAA with Local Hypoxia and wall weakening (2001)
5) Mechanical Properties and Microstructure of Intraluminal Thrombus from AAA (2001)
7) Biomechanical determinants of abdominal aortic aneurysm rupture (2005)
8) The effects of aneurysm on the biaxial mechanical behavior of human abdominal aorta (2006)
11) Biomechanics of Abdominal Aortic Aneurysm (2007)
Select Morphology Publications
1) Mechanical wall stress in abdominal aortic aneurysm: influence of diameter and asymmetry (1998)
2) In Vivo Three-Dimensional Surface Geometry of Abdominal Aortic Aneurysms (1999)
Select Artificial Intelligence Publications
1) Artificial Intelligence Framework to Predict Wall Stress in Abdominal Aortic Aneurysm (2022)