Raman spectroscopy of monosodium urate crystals: A novel tool for non-invasive gout diagnosis
Bibliographic record
Abstract
Gout is the most common form of inflammatory arthritis. It results in the deposition of monosodium urate crystals (MSU) at the surface of a joint or the articular cartilage. The gold standard for gout diagnosis is synovial fluid (SF) analysis which requires aspiration of the fluid and subsequent analysis by polarized light microscopy (PLM). This has poor reproducibility, is invasive and requires trained personal to perform the analysis. Raman spectroscopy (RS) has the potential to be a non-invasive diagnostic tool that can detect the presence of MSU crystals. The purpose of the research was to determine whether Raman spectroscopy applied onto the surface of a joint could detect MSU crystals through the skin. Two clinical studies were conducted, entitled the Pilot study (Pilot) and the sons of gout study (SOG). Pilot (n=20) considered ten clinically diagnosed gout sufferers and ten clinically diagnosed Osteoarthritis (OA) patients that acted as control. SOG (n=25) considered nine asymptomatic patients where gout was confirmed by clinicians at time of experiment by ultrasound, and 16 Non-Gouty patients, which did not show any signs of gout. An algorithm was implemented in Matlab® 2016 that removed background florescence, performed denoising and identified the presence or absence of MSU peaks. The comparisons were made against Raman peaks that are known to relate to MSU according to the literature. Three peak combinations, entitled C1, C2 and C3 were evaluated based on their resulting sensitivities and specificities for both studies. C1 was chosen as it provided the highest sensitivity for both studies. Pilot was found to have a sensitivity and specificity of 0.8 and 0.7, respectively. SOG had a sensitivity and specificity of 1 and 0.5, respectively. The results indicated that RS diagnosis is able to achieve good to high sensitivity comparable to other gout detection techniques but a moderate to good specificity. The results also show that RS is fully capable of detecting MSU crystals in-vivo, but results in a high number of false positives, 2 for Pilot and 7 for SOG. However, the false positives in Pilot may be attributed to the control subjects suffering from osteoarthritis, which can be a precursor of gout, and the false positives in the SOG study may be a result of ultrasound (US) being used as the confirmatory diagnostic technique that RS is being compared to. US is known to have sensitivity as low as 0.22 and is operator-dependent. Larger population studies are needed to confirm the ability of RS as a diagnostic tool for detecting gout.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".