Evidence map›Paper›PMID 41313393›Full record

Article3D printing in medicine2025

Uptake characteristics of MRI and CT contrast agents in 3D printing materials for vascular phantoms.

Annika C Dell, Celina Wist, Hanna Grasshoff, Malte M Sieren, Maria-Josephina Buhné, Constantin Schareck, Patricia Ulloa, Thorsten M Buzug, Roman Kloeckner, Jörg Barkhausen and 3 more

Abstract read
In one paragraph

Article in 3D printing in medicine, 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
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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.

Annika C Dell *Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany. annika.dell@imte.fraunhofer.de.
Celina Wist *Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany.
Hanna GrasshoffClinic of Rheumatology and Clinical Immunology, University Hospital Schleswig-Holstein, Lübeck, Germany.
Malte M SierenInstitute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany.
Maria-Josephina BuhnéInstitute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany.
Constantin SchareckInstitute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany.
Patricia UlloaInstitute of Neuroradiology, University Hospital Schleswig-Holstein, Lübeck, Germany.
Thorsten M BuzugFraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany.
Roman KloecknerInstitute of Interventional Radiology, University Hospital Schleswig-Holstein, Lübeck, Germany.
Jörg BarkhausenInstitute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany.
Alex FrydrychowiczInstitute of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Lübeck, Germany.
Thomas FriedrichFraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany.
Franz WegnerFraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo determine the reusability and robustness of three 3D-printing materials for anatomical vessels by evaluating their contrast agent uptake characteristics throughout different timeframes.

methodsThe tested samples were 3D-printed cylindrical samples that have the same diameter and wall thickness as a healthy adult aorta. Three different materials of varying degrees of Shore hardness were used to print these samples on a Stratasys J850 Prime PolyJet 3D printer (VeroClear, Agilus, and an Agilus/VeroClear mixture). Each sample was filled with one of three contrast agent dilutions or a control solution. Samples remained filled with their respective solution for one week, one day, or one hour. Computed tomography (CT) and magnetic resonance (MR) images were taken of all 54 samples. The CT and MR images were evaluated to determine the diameters of the samples, as well as the radiodensity/signal intensity of the samples. An Intraclass Correlation Coefficient (ICC) was calculated to determine the degree of measurement variation between the investigators. Sample mass increase was determined by weighing samples before and after exposure to the solutions. A generalized linear mixed model (GLMM) was used to evaluate the contrast agent uptake behavior of the materials based on CT and MR imaging data.

resultsA small relative mass increase in the 3D-printed materials was noted: VeroClear showed mass increases of between 1.1% and 2.5%, which is in line with the respective data sheet. Agilus showed mass increases of 2.9% to 4.4%. In CT images, very small, but statistically significant effects were detected for VeroClear in the measured diameters (t = −2.31, p = 0.02) and the signal intensity (t = 3.40, p < 0.001). All other tested material combinations revealed no significant effects in comparison to the reference sample.

conclusionsThis study suggests that the tested materials using the Stratasys J850 3D printer can produce structures that do not absorb clinically detectable amounts of CT or MR imaging contrast agent solutions. Thus, the tested materials are suitable for the 3D printing of vascular phantoms that are filled with contrast agent solutions and can be reused in the time periods evaluated.

Indexed as

3D printing3D printing materialsCompliant vascular modelsContrast agentCTMRIVascular modelVascular phantomVasculature

Identifiers

PMID41313393
PMCPMC12667169

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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.