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Record W4406710867 · doi:10.1186/s41205-025-00249-y

Development and biomechanical evaluation of a 3D printed analogue of the human lumbar spine

2025· article· en· W4406710867 on OpenAlexafffund
Siril Teja Dukkipati, Mark Driscoll

Bibliographic record

Venue3D Printing in Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsMcGill UniversityMontreal General Hospital
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaFaculty of Engineering, McGill UniversityMcGill University
KeywordsCadaveric spasmBiomechanicsBiomedical engineeringStiffnessMaterials scienceLumbarIntervertebral discOrthodonticsAnatomyEngineeringMedicineComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: There exists a need for validated lumbar spine models in spine biomechanics research. Although cadaveric testing is the current gold standard for spinal implant development, it poses significant issues related to reliability and repeatability due to the wide variability in cadaveric physiologies. Moreover, there are increasing ethical concerns with human dissection practices. Analogue models can act as cost saving alternatives to human tissue with better repeatability. The current study proposes a new methodology of spinal biomechanics testing using 3D printable surrogates and characterized its multi-dimensional stiffness in displacement-controlled loading scenarios. METHODS: The model consisted of L1 to S1 vertebrae, intervertebral discs (IVD), intertransverse, interspinous, anterior and posterior longitudinal ligaments. The vertebrae and the IVDs were derived from an open-source 3D MRI anatomography database, while the ligaments were modeled based on literature incorporating mounting points on the spinous and transverse processes. Stereolithography 3D printing along with a combination of stiff and soft photopolymer resins were used to manufacture the vertebrae and the soft tissues in the model. Thereafter, displacement-controlled pure moments were applied in the range of ± 15° at 0.5°/sec in all bending modes using a torsion testing machine and a custom pure bending jig. Model rotation and resisting moment under loading were recorded to quantify the rotational stiffness and hysteresis in the model. RESULTS: The model reached a maximum of 5.66Nm and 3.53Nm at 15° flexion-extension, 3.84Nm and 3.93Nm at 15° right and left lateral bending, and 2.45Nm and 2.59Nm at 15° right and left axial rotation respectively. Model RMS error against ex vivo human response was estimated to be 1.57°, 1.64°, 0.82° in flexion-extension, lateral bending and axial rotation respectively. Bilateral symmetry in model stiffness was observed in lateral bending and axial rotation directions. CONCLUSIONS: This study presents a reproducible 3D printable L1-S1 lumbar spine and validated it in all three orthogonal bending modes in the range of ± 15° against ex vivo and in silico data. The 3D printed analogue spine model described herein shows promising results, suggesting this model, with further validation, could have potential as a human cadaveric tissue substitute within the explored contexts of use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.377
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes2
Has abstractyes

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