Evidence map›Paper›PMID 42008042›Full record

Article3D printing in medicine2026

Optimizing the design and production of custom 3D-printed knee orthoses.

Jakub Szary, Małgorzata Kowalczyk, Mateusz Zwierzycki, Piotr Knysak, Anna Nowak, Katarzyna Janczak, Cyprian Kornacki, Marcin Domżalski

Abstract read
In one paragraph

Article in 3D printing in medicine, 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

8 authors.

Jakub SzaryMdh sp. z o.o, Maratonska Str. 104, Lodz, 94-007, Poland. jszary@meyragroup.com.ORCID http://orcid.org/0000-0003-3208-8214
Małgorzata KowalczykMdh sp. z o.o, Maratonska Str. 104, Lodz, 94-007, Poland.
Mateusz ZwierzyckiBiuro projektowe Mateusz Zwierzycki "Object", Lipowa Str. 19, Rogalinek, 62-022, Poland.
Piotr KnysakMdh sp. z o.o, Maratonska Str. 104, Lodz, 94-007, Poland.
Anna NowakMdh sp. z o.o, Maratonska Str. 104, Lodz, 94-007, Poland.
Katarzyna JanczakDepartment of Orthopedics and Trauma, Medical University of Lodz, University Hospital of Lodz No. 2, Zeromskiego 113 St., Lodz, 90-549, Poland.
Cyprian KornackiMdh sp. z o.o, Maratonska Str. 104, Lodz, 94-007, Poland.
Marcin DomżalskiDepartment of Orthopedics and Trauma, Medical University of Lodz, University Hospital of Lodz No. 2, Zeromskiego 113 St., Lodz, 90-549, Poland.ORCID http://orcid.org/0000-0003-1915-0773

Funding

Narodowe Centrum Badań i Rozwoju Rzeczy są dla ludzi/0013/2020
6 · The paper itself

Abstract

backgroundTraditional methods for producing custom-made orthoses are often time-consuming, labor-intensive, and reliant on manual processes, which limit both scalability and the degree of individualization. The development of 3D scanning technologies, computer-aided design (CAD), and additive manufacturing offers a promising alternative enabling patient-specific solutions with greater precision, speed, and efficiency. This study aimed to create an algorithm for automating the design process of personalized knee orthoses based on 3D scanning and intended for 3D printing production.

methodsA parametric modeling workflow was developed in the Rhino environment using the Grasshopper plug-in to streamline personalized knee orthoses creation. The process began with acquiring high-quality 3D scans using Structure Sensor Mark II scanner mounted on an iPad with 3DsizeMe software. The parametric algorithm was transformed into an autonomous Rhino plug-in using C# language and RhinoCommon API. As part of Post-Market Clinical Follow-up (PMCF), three participants with knee joint disorders used orthoses for one month. Assessment used a 5-point scale (1 = poor, 5 = excellent). Personalized orthoses were manufactured using powder-bed fusion technology with PA11 CF nylon powder reinforced with carbon fibers.

resultsDesign time was reduced from approximately 8 h to 10,3 ± 1,4 min. In Grasshopper prototype phase, average design time was 26,7 ± 4,5 min. Following the implementation of the Rhino plug-in, the design time was further reduced to approximately 10 min. The tool was shown to meet user requirements and fulfill its intended purpose. All three PMCF participants rated orthoses positively, reporting high comfort, effective stabilization, increased physical activity, and overall satisfaction with functionality and appearance. Participants P1 and P2 noted a large increase in physical activity, with P1 indicating pain reduction that increased mobility.

conclusionsThis study demonstrates that the combined use of Rhino and Grasshopper provides an effective platform for parametric design of personalized knee orthoses based on patient-specific 3D scans. The workflow reduced design time to approximately 10,3 ± 1,4 min, highlighting potential for routine clinical applications. This reduction is economically significant, lowering labor costs and implementation thresholds for personalized orthotic solutions in clinical practice.

Indexed as

3D printAdditive manufacturingClinical follow-upCustomized devicesKnee orthosisParametric design

Identifiers

PMID42008042
PMCPMC13169548

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LicenceCC BY-NC-ND
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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.