Publications

For a full list of Dr. Vorp's publications, please visit Dr. Vorp's Google Scholar page

Selected publications (stats as of July 2025):

  1. Toward a Biomechanical Tool to Evaluate Rupture Potential of Abdominal Aortic Aneurysm: Identification of a Finite Strain Constitutive Model and Evaluation of Its Applicability. ML Raghavan, DA Vorp, Journal of biomechanics 33 (4), 475-482, 2000 (803 citations as of July 2025).
    This paper was the first to identify a realistic biomechanical response model for abdominal aortic aneurysm (AAA) wall tissue. The “Raghavan & Vorp Model” still serves as the norm in the literature for biomechanical analyses of aortic aneurysms.
  2. Association of Intraluminal Thrombus in Abdominal Aortic Aneurysm with Local Hypoxia and Wall Weakening. DA Vorp, PC Lee, DHJ Wang, MS Makaroun, EM Nemoto, S Ogawa, MW Webster, Journal of Vascular Surgery 34 (2), 291-299, 2001. (667 citations as of July 2025).
    This paper was the first to demonstrate that the presence of the commonly found intraluminal thrombus (ILT) in AAA has pathophysiological impact on the aortic wall by causing hypoxia and degenerative tissue weakening. It served as the premise for many follow-on studies assessing the role of the ILT on the natural history of the disease.
  3. Wall Stress Distribution on Three-Dimensionally Reconstructed Models of Human Abdominal Aortic Aneurysm. ML Raghavan, DA Vorp, MP Federle, MS Makaroun, MW Webster. Journal of vascular surgery 31 (4), 760-769, 2000 (548 citations as of July 2025).
    This paper was the first to assess the 3D distribution of mechanical wall stress in patient-specific reconstructions of AAA and gave rise to a still-growing international field of AAA biomechanics.
  4. Effect of Intraluminal Thrombus on Wall Stress in Patient-Specific Models of Abdominal Aortic Aneurysm. DHJ Wang, MS Makaroun, MW Webster, DA Vorp, Journal of Vascular Surgery 36 (3), 598-604, 2002. (527 citations as of July 2025).
    This article demonstrated that the ILT was not only biologically active and has a profound effect on the degenerative pathology associated with AAA, but also plays a role in modulating the wall stresses acting on the AAA wall. We thus were the first to characterize that ILT acted in a “Jekyll & Hyde” manner, in a beneficial way in terms of reducing wall stress, but in a detrimental way in terms of also reducing wall strength.
  5. Development of a Tissue-Engineered Vascular Graft Combining a Biodegradable Scaffold, Muscle-Derived Stem Cells and Rotational Vacuum Seeding Technique. A Nieponice, L Soletti, J Guan, BM Deasy, J Huard, WR Wagner, DA Vorp. Biomaterials 29 (7), 825-833, 2008 (285 citations as of July 2025).
    In this paper, we described a new paradigm for the fabrication of a novel stem cell-based vascular graft which served as the basis for a major new research direction in the lab.
  6. Towards A Noninvasive Method for Determination of Patient-Specific Wall Strength Distribution in Abdominal Aortic Aneurysms. JP Vande Geest, DHJ Wang, SR Wisniewski, MS Makaroun, DA Vorp. Annals of Biomedical Engineering 34 (7), 1098-1106, 2006. (300 citations as of July 2025).
    This article reported on a technique to estimate the other biomechanical quantity that is important in assessing severity of AAA, the counterpart to wall stress, wall tensile strength. The technique essentially used a machine-learning approach to predict wall strength and any location on the AAA wall, allowing for spatial and patient-specific variations. This then allowed us to define the Rupture Potential Index (RPI), defined as the ratio of wall stress to wall strength at any point on the AAA wall. The RPI has been adopted and utilized by other investigators throughout the world and is the basis of a start-up company spun out of the Karolinska Institute in Stockholm, Sweden.
  7. An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes. TK Chung, PH Gueldner, OU Aloziem, NL Liang, DA Vorp. An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes. Sci Rep.14 (1), 3390, 2024. (17 citations as of July 2025) 
    This article demonstrated that machine learning models trained on clinical, morphological, and biomechanical data predict AAA patient outcomes with better discriminability than diameter alone. This work is the basis of Aneurisk, Inc., a spin-out of the lab that utilizes artificial intelligence to advance abdominal aortic aneurysm diagnostics and prediction.