Magnetic Resonance Imaging in Patients with Mechanical Low Back Pain Using a Novel Rapid-Acquisition Three-Dimensional SPACE Sequence at 1.5-T: A Pilot Study Comparing Lumbar Stenosis Assessment with Routine Two-Dimensional Magnetic Resonance Sequences
Bibliographic record
Abstract
PURPOSE: To minimize the burden of overutilisation of lumbar spine magnetic resonance imaging (MRI) on a resource-constrained public healthcare system, it may be helpful to image some patients with mechanical low-back pain (LBP) using a simplified rapid MRI screening protocol at 1.5-T. A rapid-acquisition 3-dimensional (3D) SPACE (Sampling Perfection with Application-optimized Contrasts using different flip angle Evolution) sequence can demonstrate common etiologies of LBP. We compared lumbar spinal canal stenosis (LSCS) and neural foraminal stenosis (LNFS) assessment on 3D SPACE against conventional 2-dimensional (2D) MRI. METHODS: We prospectively performed 3D SPACE and 2D spin-echo MRI sequences (axial or sagittal T1-weighted or T2-weighted) at 1.5-T in 20 patients. Two blinded readers assessed levels L3-4, L4-5 and L5-S1 using: 1) morphologic grading systems, 2) global impression on the presence or absence of clinically significant stenosis (n = 60 disc levels for LSCS, n = 120 foramina for LNFS). Reliability statistics were calculated. RESULTS: Acquisition time was ∼5 minutes for SPACE and ∼20 minutes for 2D MRI sequences. Interobserver agreement of LSCS was substantial to near perfect on both sequences (morphologic grading: kappa [k] = 0.71 SPACE, k = 0.69 T2-weighted; global impression: k = 0.85 SPACE, k = 0.78 T2-weighted). LNFS assessment had superior interobserver reliability using SPACE than T1-weighted (k = 0.54 vs 0.37). Intersequence agreement of findings between SPACE and 2D MRI was substantial to near perfect by global impression (LSCS: k = 0.78 Reader 1, k = 0.85 Reader 2; LNFS: k = 0.63 Reader 1, k = 0.66 Reader 2). CONCLUSIONS: 3D SPACE was acquired in one-quarter the time as the conventional 2D MRI protocol, had excellent agreement with 2D MRI for stenosis assessment, and had interobserver reliability superior to 2D MRI. These results justify future work to explore the role of 3D SPACE in a rapid MRI screening protocol at 1.5-T for mechanical LBP.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".