Quantitative subsurface spatial frequency‐domain fluorescence imaging for enhanced glioma resection
Bibliographic record
Abstract
The rate of complete resection of glioma has improved with the introduction of 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) fluorescence image guidance. Surgical outcomes are further enhanced when the fluorescence signal is decoupled from the intrinsic tissue optical absorption and scattering obtained from diffuse reflectance measurements, yielding the absolute PpIX concentration, [PpIX]. Spatial frequency domain imaging was used previously to measure [PpIX] in near-surface tumors under blue fluorescence excitation. Here, we extend this to subsurface [PpIX] fluorescence under red-light excitation. The decay rate of the modulation amplitude of the fluorescence signal was used to calculate the PpIX depth, which was then applied in a forward diffusion model to estimate [PpIX] at depth. For brain-like optical properties in phantoms with PpIX fluorescent inclusions, the depth can be recovered up to depths of 9.5 mm ± 0.4 mm, with [PpIX] ranging from 5 to 15 μg/mL within an average deviation of 15% from the true [PpIX] value.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".