Analysis of quantitative magnetic resonance imaging and biomechanical parameters on human discs with different grades of degeneration
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".