Evidence map›Paper›PMID 40488185›Full record

ArticleJournal of vascular surgery cases and innovative techniques2025

Artificial intelligence-based machine learning protocols enable quicker assessment of aortic biomechanics: A case study.

Pete H Gueldner, Katherine E Kerr, Nathan Liang, Timothy K Chung, Tiziano Tallarita, Joe Wildenberg, Jason Beckermann, David A Vorp, Indrani Sen

Abstract read
In one paragraph

Article in Journal of vascular surgery cases and innovative techniques, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Reply.Journal of vascular surgery cases and innovative techniques · 2026
    Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Pete H GueldnerDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA.
Katherine E KerrDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA.
Nathan LiangDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA.
Timothy K ChungDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA.
Tiziano TallaritaDepartment of Vascular Surgery, Mayo Clinic Health Systems, Eau Claire, WI.
Joe WildenbergDepartment of Radiology, Mayo Clinic Health Systems, Eau Claire, WI.
Jason BeckermannDepartment of Vascular Surgery, Mayo Clinic Health Systems, Eau Claire, WI.
David A VorpDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA.
Indrani SenDepartment of Vascular Surgery, Mayo Clinic Health Systems, Eau Claire, WI.

Funding

Biomechanics in Regenerative Medicine (BiRM) Training ProgramT32EB034216 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI David Alan Vorp · 2023 to 2026
$855k
NIBIB NIH HHS T32 EB034216
6 · The paper itself

Abstract

Analyzing aortic biomechanical wall stresses for abdominal aortic aneurysms remains challenging. Clinical applications of biomechanical and morphological image-based analysis protocols have limited adoption owing to the time and expertise required. Our multidisciplinary and multi-institute team has demonstrated the feasibility of expediting advanced aortic image analysis on a single patient tracked longitudinally. We also demonstrate the utility of a previously trained artificial intelligence-based classifier that accurately predicts patient outcomes, a potential alternative to serial surveillance. This paper describes the overall workflow and processes performed in a 70-year-old man who was incidentally diagnosed to have a 5.4-cm juxtarenal aortic aneurysm in 2016 with successful fenestrated endovascular repair in 2023.

Indexed as

BiomechanicsFenestrated repairJuxtarenal aneurysmWall stress

Identifiers

PMID40488185
PMCPMC12141894

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.