Evidence map›Paper›PMID 42007622›Full record

ArticleSICOT-J2026

Development of a knee joint magnetic resonance imaging (MRI)-based model for finite element analysis (FEA) applications.

Angelo V Vasiliadis, Kalliopi Valsamidou, Alexandros Chortis, Dimitrios Chytas, George Noussios, George Paraskevas, Konstantinos Katakalos, Aikaterini Vassiou

Abstract read
In one paragraph

Article in SICOT-J, 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
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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

8 authors.

Angelo V VasiliadisDepartment of Anatomy, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece - Orthopaedic Surgery and Sports Medicine Department, FIFA Medical Center of Excellence, Croix-Rousse Hospital, Lyon University Hospital, Lyon, France - Department of Physical Education and Sports Sciences at Serres, Aristotle University of Thessaloniki, 62110 Agios Ioannis-, Serres, Greece.ORCID 0000-0002-6155-8898
Kalliopi ValsamidouDepartment of Architecture, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Alexandros ChortisLaboratory for Experimental Strength of Materials and Structures, Department of Civil Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Dimitrios ChytasBasic Sciences Laboratory, Department of Physiotherapy, University of Peloponnese, 23100 Sparta, Greece - School of Medicine, European University of Cyprus, 2404 Nicosia, Cyprus.
George NoussiosDepartment of Physical Education and Sports Sciences at Serres, Aristotle University of Thessaloniki, 62110 Agios Ioannis-, Serres, Greece.
George ParaskevasDepartment of Anatomy and Surgical Anatomy, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Konstantinos KatakalosLaboratory for Experimental Strength of Materials and Structures, Department of Civil Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Aikaterini VassiouDepartment of Anatomy, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe knee is a biomechanically complex joint supported by multiple anatomical structures, making it vulnerable to multiple injuries. Finite element analysis is a valuable tool for studying joint biomechanics, particularly in pre-operative planning and injury evaluation. However, most models are based on computed tomography, which limits soft tissue visualization. Thus, a magnetic resonance imaging-based finite element model of the knee, incorporating bones, ligaments, tendons, cartilage, and menisci, was developed to improve realism and clinical relevance in biomechanical simulations. MATERIALS AND

methodsMagnetic resonance imaging data were obtained from a healthy adult male using a 1.5T scanner and processed using RETOMO and Rhinoceros software for 3D reconstruction and modeling. Meshes were cleaned, optimized, and anatomically validated. All major knee structures were modeled, including the femur, tibia, fibula, patella, cruciate and collateral ligaments, patellofemoral ligaments, quadriceps and patellar tendons, menisci, and articular cartilage.

resultsThe resulting model reconstructed both hard and soft tissues of the knee joint with high anatomical fidelity, based on direct MRI segmentation and literature-supported anatomical definitions. The use of magnetic resonance imaging enabled high-resolution identification of soft tissues, while advanced mesh refinement preserved anatomical detail with optimized file management. The inclusion of structures like the anterolateral ligament and patellofemoral ligaments expands the model's clinical relevance in addressing a wider range of knee pathologies.

conclusionThis magnetic resonance imaging-based finite element analysis model provides a detailed and comprehensive, representation of the healthy human knee, including bones, cartilage, menisci, and tendons. While some ligament attachment points were derived from literature rather than MRI data, the model provides a foundation for future biomechanical studies, surgical planning and personalized treatment simulations.

Indexed as

Finite element analysisKnee joint biomechanicsLigamentsMagnetic resonance imagingMeniscus

Identifiers

PMID42007622
PMCPMC13094345

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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.