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Record W1604042151 · doi:10.1002/jmri.24120

Analysis of quantitative magnetic resonance imaging and biomechanical parameters on human discs with different grades of degeneration

2013· article· en· W1604042151 on OpenAlexafffund
John Antoniou, Laura M. Epure, Arthur J. Michalek, Michael P. Grant, James C. Iatridis, Fackson Mwale

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2013
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsJewish General Hospital
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesCanadian Institutes of Health Research
KeywordsDegeneration (medical)Magnetic resonance imagingIntervertebral discMaterials scienceBiomedical engineeringNuclear magnetic resonanceMedicineAnatomyPhysicsPathologyRadiology

Abstract

fetched live from OpenAlex

PURPOSE: To establish relationships between quantitative MRI (qMRI) and biomechanical parameters in order to help inform and interpret alterations of human intervertebral discs (IVD) with different grades of degeneration. MATERIALS AND METHODS: The properties of the nucleus pulposus (NP) and annulus fibrosus (AF) of each IVD of 10 lumbar spines (range, 32-77 years) were analyzed by qMRI (relaxation times T1 and T2, magnetization transfer ratio [MTR], and apparent diffusion coefficient [ADC]), and tested in confined compression and dynamic shear. RESULTS: T1 and T2 significantly decreased in both the NP and AF with increasing degeneration grades while the MTR increased significantly with grade 4. In contrast to the other qMRI parameters, the ADC had a tendency to decrease with increasing grade. Disc degeneration caused a decrease in the aggregate modulus, hydraulic permeability and shear modulus magnitude along with an increase in phase angle in the AF. In contrast, disc degeneration of NPs demonstrated decreases in shear modulus and phase angle. CONCLUSION: Our studies indicate that qMRI can be used as a noninvasive diagnostic tool in the detection of IVD properties with the potential to help interpret and detect early, middle, and late stages of degeneration. QMRI of human IVD can therefore become a very important diagnostic assessment tool in determining the functional state of the disc.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.310
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations66
Published2013
Admission routes2
Has abstractyes

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