Bone and Gallium Single-Photon Emission Computed Tomography-Computed Tomography is Equivalent to Magnetic Resonance Imaging in the Diagnosis of Infectious Spondylodiscitis: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVES: Tc-methylene diphosphonate) and gallium-67 single-photon emission computed tomography-computed tomography (SPECT-CT). Their accuracies have not been adequately compared. The purpose of this study is to compare the sensitivities and specificities of bone and gallium SPECT-CT and MRI in infectious spondylodiscitis. METHODS: This retrospective study assessed all patients who underwent a bone or gallium SPECT-CT of the spine to assess for infectious spondylodiscitis from January 1, 2010, to May 2, 2012, at a single tertiary care centre. Thirty-four patients (23 men; average 62 ± 14 years of age) were included. The results of the bone or gallium SPECT-CT were compared against MRI for all patients in the cohort who underwent an MRI within 12 weeks of the SPECT-CT. A diagnosis of spondylodiscitis in the discharge summary was considered the reference standard, and was based on a combination of clinical scenario, response to therapy, imaging, or microbiology. RESULTS: Spondylodiscitis was diagnosed in 18 patients and excluded in 16. Bone or gallium SPECT-CT and MRI had similar (P > .05; κ = 0.74) sensitivities (0.94 vs 0.94), specificities (1.00 vs 1.00), positive predictive values (1.00 vs 1.00), negative predictive values (0.94 vs 0.80), and accuracies (0.97 vs 0.95) when compared to the reference standard. CONCLUSION: Although MRI remains the initial modality of choice in diagnosing spondylodiscitis, bone and gallium SPECT-CT appears diagnostically equivalent and should be considered a viable supplementary or alternative imaging modality particularly if there is contraindication or inaccessibility to MRI.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 0.001 |
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".