The Application of Raman Spectroscopic Analysis for the Evaluation of Hepatic Steatosis
Bibliographic record
Abstract
Background: Livers with significant steatosis are considered extended criteria organs for transplantation because of increased rate of non-function and reduced survival in recipients. The evaluation of steatosis, and decision to use an organ, is most often made by the retrieving surgeon, but is accurate only 30-70% of the time. Raman spectroscopy is an imaging technique with the potential to allow for accurate real-time evaluation of steatosis at the time of retrieval. Methods: Male C57BL/6 mice were fed either a control or a methionine and choline deficient (MCD) diet to induce steatosis. At 2, 3 and 4 weeks, mice were sacrificed and livers harvested. Livers samples were analyzed by: 1) Oil Red O staining and scored by a histopathologist; 2) Biochemical determination of triglyceride and cholesterol content; 3) Raman spectroscopic analysis using a 515 nm-laser confocal microscope, or 785 nm-laser Raman probe; 4) intensity of triglyceride-specific Raman spectra were correlated with the degree of steatosis as determined by 1) and 2). Results: Pathology for all control mice revealed no steatosis, whereas MCD-fed mice were all scored as positive. Triglyceride content for MCD-fed mice was significantly elevated at all time-points, compared with controls, and correlated with the length of time the mice were fed an MCD diet. Upon Raman spectroscopic analysis, control livers did not show any consistent shift in the Raman spectra from 1000cm-1 to 4000cm-1, whereas MCD-fed mouse livers demonstrated shifts at 1146 cm-1, 1313 cm-1, 1460 cm-1, 1664cm-1 and 2896 cm-1, consistent with that of adipocytes and triglyceride. Conclusion: Livers with significant steatosis, as demonstrated by pathology and biochemical analysis, can be distinguished from non-fatty livers by a Raman spectral signature consistent with that of triglycerides and adipocytes. Raman spectra from mouse livers can be obtained immediately after the organ is retrieved, or while still inside the animal with the use of a portable, hand-held Raman spectrometer, which we hope to employ in future in vivo experiments. Further work will optimise the conditions for quantitative analysis of liver fat content which might be applied in the operating room. This is a promising technique for real-time evaluation organ quality at the time of retrieval.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".