Quantitative fluorescence using 5-aminolevulinic acid-induced protoporphyrin IX biomarker as a surgical adjunct in low-grade glioma surgery
Bibliographic record
Abstract
OBJECT: Previous studies in high-grade gliomas (HGGs) have indicated that protoporphyrin IX (PpIX) accumulates in higher concentrations in tumor tissue, and, when used to guide surgery, it has enabled improved resection leading to increased progression-free survival. Despite the benefits of complete resection and the advances in fluorescence-guided surgery, few studies have investigated the use of PpIX in low-grade gliomas (LGGs). Here, the authors describe their initial experience with 5-aminolevulinic acid (ALA)-induced PpIX fluorescence in a series of patients with LGG. METHODS: Twelve patients with presumed LGGs underwent resection of their tumors after receiving 20 mg/kg of ALA approximately 3 hours prior to surgery under an institutional review board-approved protocol. Intraoperative assessments of the resulting PpIX emissions using both qualitative, visible fluorescence and quantitative measurements of PpIX concentration were obtained from tissue locations that were subsequently biopsied and evaluated histopathologically. Mixed models for random effects and receiver operating characteristic curve analysis for diagnostic performance were performed on the fluorescence data relative to the gold-standard histopathology. RESULTS: Five of the 12 LGGs (1 ganglioglioma, 1 oligoastrocytoma, 1 pleomorphic xanthoastrocytoma, 1 oligodendroglioma, and 1 ependymoma) demonstrated at least 1 instance of visible fluorescence during surgery. Visible fluorescence evaluated on a specimen-by-specimen basis yielded a diagnostic accuracy of 38.0% (cutoff threshold: visible fluorescence score ≥ 1, area under the curve = 0.514). Quantitative fluorescence yielded a diagnostic accuracy of 67% (for a cutoff threshold of the concentration of PpIX [CPpIX] > 0.0056 μg/ml, area under the curve = 0.66). The authors found that 45% (9/20) of nonvisibly fluorescent tumor specimens, which would have otherwise gone undetected, accumulated diagnostically significant levels of CPpIX that were detected quantitatively. CONCLUSIONS: The authors' initial experience with ALA-induced PpIX fluorescence in LGGs concurs with other literature reports that the resulting visual fluorescence has poor diagnostic accuracy. However, the authors also found that diagnostically significant levels of CPpIX do accumulate in LGGs, and the resulting fluorescence emissions are very often below the detection threshold of current visual fluorescence imaging methods. Indeed, at least in the authors' initial experience reported here, if quantitative detection methods are deployed, the diagnostic performance of ALA-induced PpIX fluorescence in LGGs approaches the accuracy associated with visual fluorescence in HGGs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".