Sensitivity of MRI parameters within intervertebral discs to the severity of adolescent idiopathic scoliosis
Bibliographic record
Abstract
Purpose To measure magnetic resonance imaging (MRI) parameters including relaxation times (T1ρ, T2), magnetization transfer (MT) and diffusion parameters (mean diffusivity [MD], fractional anisotropy [FA]) of intervertebral discs in adolescents with idiopathic scoliosis, and to investigate the sensitivity of these MR parameters to the severity of the spine deformities. Materials and Methods Thirteen patients with adolescent idiopathic scoliosis and three control volunteers with no history of spine disease underwent an MRI acquisition at 3T including the mapping of T1ρ, T2, MT, MD, and FA. The apical zone included all discs within the scoliotic curve while the control zone was composed of other discs. The severity was analyzed through low (<32°) versus high (>40°) Cobb angles. One‐way analysis of variance (ANOVA) and agglomerative hierarchical clustering (AHC) were performed. Results Significant differences were found between the apical zone and the control zone for T2 (P = 0.047), and between low and high Cobb angles for T2 (P = 0.014) and MT (P = 0.002). AHC showed two distinct clusters, one with mainly low Cobb angles and one with mainly high Cobb angles, for the MRI parameters measured within the apical zone, with an accuracy of 0.9 and a Matthews correlation coefficient (MCC) of 0.8. Within the control zone, the AHC showed no clear classification (accuracy of 0.6 and MCC of 0.2). Conclusion We successfully performed an in vivo multiparametric MRI investigation of young patients with adolescent idiopathic scoliosis. The MRI parameters measured within the intervertebral discs were found to be sensitive to intervertebral disc degeneration occurring with scoliosis and to the severity of scoliosis. J. Magn. Reson. Imaging 2016;44:1123–1131.
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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 | 0.004 |
| 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".