Flow diverters: inter and intra-rater reliability of porosity and pore density measurements
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Porosity and pore density (PD) are important characteristics of flow diverters (FDs), because they may influence device efficacy and safety. Reliable measurement of these parameters would seem to be required for comparisons between devices, device selection at the time of clinical usage, as well as for research purposes. Because there is no standard method of measurement, our aim was to assess the intra-rater and inter-rater reliability of PD measurements and of three different ways of measuring porosity. METHODS: Six microphotographs of two fully deployed FDs were taken overlying two different millimetric reference grids: one flat and the other corrected to match the cylindrical stent. Standardized protocols for independently measuring PD and porosity according to three different methods were used by three trained observers and by the same observer twice. Bland-Altman plots and intra-class correlation coefficients (ICC) were used to study the reliability of the measurements. RESULTS: For porosity, satisfactory agreement occurred only when the same method of measurement was performed by the same observer. Intra-observer and inter-observer agreement were poor for measures of porosity when different methods were used (with differences in the range of 5-10%, ICC <0.6 for all methods). Measurement of PD was more reliable within (ICC 0.991 (0.946 to 0.999)) and between (ICC 0.945 (0.781 to 0.991)) observers. CONCLUSIONS: Without standardization, the porosity of different devices cannot reliably be compared because use of different methods or different observers substantially changes results. Pore density seems to be more reliably measured than porosity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".