Journal of vascular surgery
June 2, 2026 · via Europe PMC
Anatomic feasibility of off-the-shelf fenestrated endovascular aneurysm repair devices: An anatomic study.
Hofmann A, Leinweber M, Kliewer M, Taher F, Assadian A, Plimon M.
AI summary — for doctors, generated from the abstract only
A standardized off-the-shelf dual-fenestrated device covering the celiac and SMA appears anatomically feasible for most patients, but renal artery variability limits multivessel standardization.
What was studied
Retrospective anatomic study of CTA data from 8238 patients evaluated for fenestrated EVAR (2018-2023), using a set-cover algorithm to identify minimal OTS configurations.
Key findings
- Eight configurations covered 81.9% of SMA, 49.7% of left renal and 52.9% of right renal anatomies
- 16 designs exceeded 90% SMA coverage; 20 configurations needed per renal artery for 80% coverage
- No clustering of vessel origin by aortic diameter
Clinical relevance
This informs device development, suggesting OTS fenestrated platforms may best combine fixed visceral fenestrations with renal branches.
Who should care
Limitations
Exploratory descriptive anatomic analysis; SMA data available in only 57.1% of cases; no clinical outcomes.
Off-the-shelf fenestrated grafts can match most celiac/SMA anatomy, but kidneys vary too much for one-size-fits-all.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Objective
Fenestrated endovascular aneurysm repair enables treatment of complex aortic aneurysms involving visceral branches but is limited by patient-specific anatomical variability. Off-the-shelf (OTS) devices may reduce manufacturing delay; however, their feasibility depends on anatomic compatibility across populations.
Design
A large multicenter dataset was analyzed to evaluate the anatomic feasibility of standardized OTS fenestrated stent-graft configurations for juxtarenal and pararenal abdominal aortic aneurysms in this retrospective anatomic study.
Methods
Computed tomography angiography data from a sample of 8238 patients evaluated for fenestrated endovascular aneurysm repair between January 2018 and December 2023 were analyzed. Measurements of the celiac axis (CA), superior mesenteric artery (SMA), left renal artery (LRA), and right renal artery (RRA) included ostial distance and branching angle relative to the CA. A greedy set-cover algorithm identified the smallest number of OTS configurations achieving fenestration target vessel alignment (FTVA). Cumulative coverage and clustering by aortic diameter were assessed. Analyses were exploratory and descriptive.
Results
Anatomic data were available in 57.1% of cases for the SMA, 96.1% for the LRA, and 96.8% for the RRA. The CA served as the reference point for all analyses. Eight configurations covered 81.9% of SMA, 49.7% of LRA, and 52.9% of RRA anatomies. SMA coverage exceeded 90% with 16 designs, whereas 20 configurations were required for each renal artery to reach 80% coverage. No clustering of vessel origin by aortic diameter (median, 28 mm; interquartile range, 26-30.5 mm) was observed. Below 70% coverage for three-vessel and <25% for four-vessel combinations was achieved with the top 100 configurations.
Conclusions
A standardized dual-fenestrated OTS platform incorporating the CA and SMA appears anatomically feasible for most patients, whereas renal artery variability limits multivessel standardization. Dual-fenestrated devices with renal branches could also circumvent these constraints.
DOI
10.1016/j.jvs.2026.05.038
PMID
42235837
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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