Evidence map›Paper›PMID 40880468›Full record

ArticleScience advances2025

3D printed anisotropic tissue simulants with embedded fluid capsules for medical simulation and training.

Adarsh Somayaji, Matthew S Lawler, Alex T Gong, Zachary J Fuenning, Victoria A Roach, Athira B S, David J Traina, Jason R Speich, Ruikang K Wang, Matthew G Hackett and 3 more

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In one paragraph

Article in Science advances, 2025. 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

13 authors.

Adarsh SomayajiDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.ORCID 0009-0007-9357-1724
Matthew S LawlerDepartment of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.ORCID 0000-0002-8604-9600
Alex T GongDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0001-6519-8458
Zachary J FuenningDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.ORCID 0009-0002-0389-6140
Victoria A RoachDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.
Athira B SDepartment of Bioengineering, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-6251-1856
David J TrainaDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.
Jason R SpeichDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.
Ruikang K WangDepartment of Bioengineering, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0001-5169-8822
Matthew G HackettArmy Research Laboratory, Orlando, FL 32826, USA.
David M HananelDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-2611-6437
Robert M SweetDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-2275-6795
Michael C McAlpineDepartment of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.ORCID 0000-0001-7869-7598

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human tissues are primarily composed of collagen and elastin fiber networks that exhibit directional mechanical properties that are not replicable by conventional tissue simulants manufactured via casting. Here, we 3D print tissue simulants that incorporate anisotropic mechanical properties through the manipulation of infill voxel shape and dimensions. A mathematical model for predicting the anisotropy of single- and multimaterial structures with orthogonal infill patterns is developed. We apply this methodology to generate conformal printing toolpaths for replicating the structure and directional mechanics observed in native tissue within 3D printed tissue simulants. Further, a method to embed fluid-filled capsules within the infill structure of these tissue simulants to mimic blood is also presented. The improvements in simulation quality when using 3D printed anisotropic tissue simulants over conventional tissue simulants are demonstrated via a comparative acceptability study. These advances open avenues for the manufacture of next-generation tissue simulants with high mechanical fidelity for enhanced medical simulation and training.

Indexed as

Printing, Three-DimensionalAnisotropyComputer SimulationHumans

Identifiers

PMID40880468
PMCPMC12396343

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Registered trials

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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.