Development and validation of a Fast Spine Protocol for Use in Paediatric Patients
Bibliographic record
Abstract
Abstract ObjectiveConventional pediatric spine MRI protocols have multiple sequences resulting in long acquisition times. Sedation is consequently required. This study evaluates the diagnostic capability of a limited MRI spine protocol for selected common pediatric indications. MethodsAfter REB approval, records of pediatric patients under 4 years of age who underwent a spine MRI at CHEO between 2017 and 2020 were reviewed. Two neuroradiologists blindly and retrospectively reviewed the T2 sagittal sequences from the craniocervical junction to sacrum and T1 axial sequence of the lumbar spine, to answer specific questions regarding cerebellar ectopia, syrinx, level of conus, filum <2mm, fatty filum, and spinal dysraphism. The results were independently compared to previously reported findings from the complete imaging series. Results105 studies were evaluated in 54 male and 51 female patients (mean age of 19.2 months). The average combined scan time of the limited sequences was 15 minutes compared to 35 minutes for conventional protocols (delta = 20 minutes). The average percent agreement between full and limited sequences was >95% in all but identifying a filum <2mm, where the percent agreement was 87%. Using limited MR sequences had high sensitivity (>0.91) and specificity (>0.99) for the detection of cerebellar ectopia, syrinx, fatty filum, and spinal dysraphism. ConclusionThis study demonstrates that selected spinal imaging sequences allows for consistent and accurate diagnosis of specific clinical conditions. A limited spine protocol reduces acquisition time, potentially avoiding sedation. Further work is needed to determine the utility of selected imaging for other clinical indications.
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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 | 0.025 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".