Autofluorescence Bronchoscopy – A Comparison of Two Systems (LIFE and D-Light)
Bibliographic record
Abstract
BACKGROUND: Autofluorescense (AF) bronchoscopy is an established method to detect dysplasia and carcinoma in situ (CIS). Several different systems are currently available. OBJECTIVES: This study aimed to directly compare the LIFE system (Xillix Technologies, Vancouver, Canada) and the D-light system (Storz, Tuttlingen, Germany). METHODS: In a prospective study performed between May 1999 and October 2000, we examined patients with risk factors for lung cancer that underwent bronchoscopy with both (LIFE and D-light) systems in a crossover design. The findings were classified into normal, abnormal and suspicious lesions by independent investigators and then compared. RESULTS: This study comprised 332 patients (220 males, 112 females, mean age 62.7 years, range 40-85); 1,117 biopsies were studied (mean biopsy rate 3.4/patient). In 817 biopsies, mucosal areas were classified as normal with respect to control biopsy specimens, 113 as abnormal and 187 as suspicious using AF bronchoscopy. The histological examination showed normal tissue in 850 cases, in 55 cases scarring or inflammation, in 62 meta- or dysplasias, in 11 carcinomas in situ and in 127 invasive tumors. In only 5 cases, classifications were found to be different between the two systems (2 normal, 2 dysplasias, 1 invasive tumor). The mean time for the LIFE system examination amounted to 11.7 min (range 6.2-19.5) and for the D-light system to 7.4 min (range 4.3-11.9). This difference was statistically significant (p < 0.001). CONCLUSION: Both systems yielded comparable results. The examination time was significantly shorter with the D-light system, which may be explained by the more comfortable handling and the direct switch between white light and AF imaging. Different trials using either methodology could be compared directly.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".