Evidence map›Paper›PMID 39794807›Full record

ArticleJournal of orthopaedic surgery and research2025

Patient-specific spine digital twins: a computational characterization of the idiopathic scoliosis.

David Landinez, Carlos Francisco Rodríguez, Christian Cifuentes De la Portilla

Abstract readValidation Study
In one paragraph

Article in Journal of orthopaedic surgery and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

3 authors.

David LandinezBiomedical Engineering Department, Universidad de los Andes, Bogotá, Colombia.
Carlos Francisco RodríguezMechanical Engineering Department, Universidad de los Andes, Bogotá, Colombia.
Christian Cifuentes De la PortillaBiomedical Engineering Department, Universidad de los Andes, Bogotá, Colombia. cc.cifuentes@uniandes.edu.co.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScoliosis is an idiopathic three-dimensional spine strain. The orthopedic parameter used to diagnose and evaluate the severity of the strain is Cobb's angle. This study proposes using this clinical parameter to reproduce a digital twin of the spine, calculate biomechanical stress changes, and characterize idiopathic scoliosis deformity through symmetrical degeneration of intervertebral discs, relying on patient-specific radiological measurements of the scoliotic curves.

methodsA three-dimensional computational model of the spine was developed, where patient-specific curves were generated by modifying intervertebral disc mechanical properties via a mathematical model derived from radiological data. Validation of the model was performed by comparing the resultant scoliotic curves with patient radiological images. Finite element analysis was then used to elucidate the biomechanical effects on the spine due to the deformity.

resultsThe model successfully replicated patient-specific thoracic scoliotic deformities, revealing a discernible relationship between disc strain and its proximity to the apex, indicating a heightened risk of disc stress closer to the apex. Moreover, "type-C" curves exhibited a greater risk of herniation compared to "type-S" curves due to differences in compressive stress distribution.

conclusionThis modeling approach enhances the understanding of scoliosis biomechanics, facilitating risk assessment for disc prolapse and aiding in treatment selection, including the design of condition-specific orthotics. Furthermore, it establishes a quantitative link between scoliosis severity and disc strain, integrating Cobb's angle and other orthopedic parameters into computational models to approximate patient-specific conditions.

Indexed as

Patient-Specific ModelingScoliosisSpineBiomechanical PhenomenaHumansBiomechanicsCobb angleComputational modelingFinite elements analysisScoliosis

Identifiers

PMID39794807
PMCPMC11724562

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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.