Evidence map›Paper›PMID 41948005›Full record

ArticleFrontiers in surgery2026

In silico workflow for validation of patient-specific 3D-printed casts in forearm fracture immobilization.

Marton Bartos, Agoston Jakab Pokorni, Benjamin Hajnal, Mate Turbucz, Laszlo Horvath-Szekely, Karsa Ferenc Molnár, Nándor Orosz, Sebastian Frederick Bigdon, Peter Endre Eltes

Abstract read
In one paragraph

Article in Frontiers in surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Marton Bartos *School of PhD Studies, Semmelweis University, Budapest, Hungary.
Agoston Jakab Pokorni *School of PhD Studies, Semmelweis University, Budapest, Hungary.
Benjamin HajnalSchool of PhD Studies, Semmelweis University, Budapest, Hungary.
Mate TurbuczIn Silico Biomechanics Laboratory, National Center for Spinal Disorders, Buda Health Center, Budapest, Hungary.
Laszlo Horvath-SzekelySchool of PhD Studies, Semmelweis University, Budapest, Hungary.
Karsa Ferenc MolnárSchool of PhD Studies, Semmelweis University, Budapest, Hungary.
Nándor OroszIn Silico Biomechanics Laboratory, National Center for Spinal Disorders, Buda Health Center, Budapest, Hungary.
Sebastian Frederick BigdonDepartment of Orthopaedic Surgery and Traumatology, Inselspital, University Hospital, University of Bern, Bern, Switzerland.
Peter Endre EltesIn Silico Biomechanics Laboratory, National Center for Spinal Disorders, Buda Health Center, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This paper aims to establish an in silico workflow for biomechanical assessment of patient-specific 3D-printed forearm casts using finite element analysis, and to apply this workflow to compare a novel computationally designed point-of-care cast with a commercially available state-of-the-art cast. Methods: A finite element model of a human forearm was generated from CT data, incorporating bones, soft tissues, and a simulated distal radius and ulna fracture. Two cast designs were virtually applied: a commercial cast (AA_CAST) and a point-of-care cast (POC_CAST) featuring a hexagonal lattice. The POC_CAST was simulated with three 3D-printing materials: Acrylonitrile Butadiene Styrene, Resin, and Polyamide. Six physiological loading conditions were assessed with the proximal end constrained: flexion, extension, radial and ulnar deviation (400 N load), and pronation and supination (1 Nm moment). Maximum von Mises stress in the casts and at the fracture surfaces, as well as maximum fracture displacement, were evaluated. Results: The AA_CAST model demonstrated superior fracture stabilization, showing consistently lower maximum von Mises stresses and displacements across all loading conditions. The POC_CAST exhibited its highest internal stresses during extension (36-37 MPa) and the largest fracture displacements during radial deviation (0.28-0.36 mm). In the POC_CAST simulations, printing material influenced fracture displacement but had negligible effect on maximum cast stress. All simulated configurations maintained fracture displacement below 0.4 mm, indicating adequate immobilization performance. Conclusion: The in silico workflow proved effective for biomechanical evaluation of patient-specific 3D-printed casts and enabled direct comparison between a novel POC design and a commercial standard. While the commercial cast provided superior stabilization in simulation, the POC_CAST also demonstrated mechanically sound performance. These findings support the workflow as a robust tool for preclinical assessment, iterative design, and material selection for orthopedic devices.

Indexed as

3D-printedbiomechanicsfinite element analysisforearm fracturepatient-specific cast

Identifiers

PMID41948005
PMCPMC13050870

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.