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Record W2073775623 · doi:10.1088/0031-9155/53/9/014

Mechanical characterization of articular cartilage by combining magnetic resonance imaging and finite-element analysis—a potential functional imaging technique

2008· article· en· W2073775623 on OpenAlexaff
Petro Julkunen, Rami K. Korhonen, Mikko J. Nissi, Jukka S. Jurvelin

Bibliographic record

VenuePhysics in Medicine and Biology · 2008
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Calgary
FundersSuomen Kulttuurirahasto
KeywordsCartilageMaterials scienceBiomedical engineeringMagnetic resonance imagingFibrilModulusProteoglycanMatrix (chemical analysis)Articular cartilageElastic modulusOsteoarthritisAnatomyBiophysicsComposite materialPathologyMedicineBiologyRadiology

Abstract

fetched live from OpenAlex

Magnetic resonance imaging (MRI) provides a method for non-invasive characterization of cartilage composition and structure. We aimed to see whether T(1) and T(2) relaxation times are related to proteoglycan (PG) and collagen-specific mechanical properties of articular cartilage. Specifically, we analyzed whether variations in the depthwise collagen orientation, as assessed by the laminae obtained from T(2) profiles, affect the mechanical characteristics of cartilage. After MRI and unconfined compression tests of human and bovine patellar cartilage samples, fibril-reinforced poroviscoelastic finite-element models (FEM), with depthwise collagen orientations implemented from quantitative T(2) maps (3 laminae for human, 3-7 laminae for bovine), were constructed to analyze the non-fibrillar matrix modulus (PG specific), fibril modulus (collagen specific) and permeability of the samples. In bovine cartilage, the non-fibrillar matrix modulus (R = -0.64, p < 0.05) as well as the initial permeability (R = 0.70, p < 0.05) correlated with T(1). In bovine cartilage, T(2) correlated positively with the initial fibril modulus (R = 0.62, p = 0.05). In human cartilage, the initial fibril modulus correlated negatively (R = -0.61, p < 0.05) with T(2). Based on the simulations, cartilage with a complex collagen architecture (5 or 7 laminae), leading to high bulk T(2) due to magic angle effects, provided higher compressive stiffness than tissue with a simple collagen architecture (3 laminae). Our results suggest that T(1) reflects PG-specific mechanical properties of cartilage. High T(2) is characteristic to soft cartilage with a classical collagen architecture. Contradictorily, high bulk T(2) can also be found in stiff cartilage with a multilaminar collagen fibril network. By emerging MRI and FEM, the present study establishes a step toward functional imaging of articular cartilage.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations57
Published2008
Admission routes1
Has abstractyes

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